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Sample records for model parameter choices

  1. Parameter Estimation for Thurstone Choice Models

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    Vojnovic, Milan [London School of Economics (United Kingdom); Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-04-24

    We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one or more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.

  2. Modeling decisions from experience: How models with a set of parameters for aggregate choices explain individual choices

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    Neha Sharma

    2017-10-01

    Full Text Available One of the paradigms (called “sampling paradigm” in judgment and decision-making involves decision-makers sample information before making a final consequential choice. In the sampling paradigm, certain computational models have been proposed where a set of single or distribution parameters is calibrated to the choice proportions of a group of participants (aggregate and hierarchical models. However, currently little is known on how aggregate and hierarchical models would account for choices made by individual participants in the sampling paradigm. In this paper, we test the ability of aggregate and hierarchical models to explain choices made by individual participants. Several models, Ensemble, Cumulative Prospect Theory (CPT, Best Estimation and Simulation Techniques (BEAST, Natural-Mean Heuristic (NMH, and Instance-Based Learning (IBL, had their parameters calibrated to individual choices in a large dataset involving the sampling paradigm. Later, these models were generalized to two large datasets in the sampling paradigm. Results revealed that the aggregate models (like CPT and IBL accounted for individual choices better than hierarchical models (like Ensemble and BEAST upon generalization to problems that were like those encountered during calibration. Furthermore, the CPT model, which relies on differential valuing of gains and losses, respectively, performed better than other models during calibration and generalization on datasets with similar set of problems. The IBL model, relying on recency and frequency of sampled information, and the NMH model, relying on frequency of sampled information, performed better than other models during generalization to a challenging dataset. Sequential analyses of results from different models showed how these models accounted for transitions from the last sample to final choice in human data. We highlight the implications of using aggregate and hierarchical models in explaining individual choices

  3. Optimization of a centrifugal compressor impeller using CFD: the choice of simulation model parameters

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    Neverov, V. V.; Kozhukhov, Y. V.; Yablokov, A. M.; Lebedev, A. A.

    2017-08-01

    Nowadays the optimization using computational fluid dynamics (CFD) plays an important role in the design process of turbomachines. However, for the successful and productive optimization it is necessary to define a simulation model correctly and rationally. The article deals with the choice of a grid and computational domain parameters for optimization of centrifugal compressor impellers using computational fluid dynamics. Searching and applying optimal parameters of the grid model, the computational domain and solver settings allows engineers to carry out a high-accuracy modelling and to use computational capability effectively. The presented research was conducted using Numeca Fine/Turbo package with Spalart-Allmaras and Shear Stress Transport turbulence models. Two radial impellers was investigated: the high-pressure at ψT=0.71 and the low-pressure at ψT=0.43. The following parameters of the computational model were considered: the location of inlet and outlet boundaries, type of mesh topology, size of mesh and mesh parameter y+. Results of the investigation demonstrate that the choice of optimal parameters leads to the significant reduction of the computational time. Optimal parameters in comparison with non-optimal but visually similar parameters can reduce the calculation time up to 4 times. Besides, it is established that some parameters have a major impact on the result of modelling.

  4. The Multiple-Choice Model: Some Solutions for Estimation of Parameters in the Presence of Omitted Responses

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    Abad, Francisco J.; Olea, Julio; Ponsoda, Vicente

    2009-01-01

    This article deals with some of the problems that have hindered the application of Samejima's and Thissen and Steinberg's multiple-choice models: (a) parameter estimation difficulties owing to the large number of parameters involved, (b) parameter identifiability problems in the Thissen and Steinberg model, and (c) their treatment of omitted…

  5. Modeling the dynamics of choice.

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    Baum, William M; Davison, Michael

    2009-06-01

    A simple linear-operator model both describes and predicts the dynamics of choice that may underlie the matching relation. We measured inter-food choice within components of a schedule that presented seven different pairs of concurrent variable-interval schedules for 12 food deliveries each with no signals indicating which pair was in force. This measure of local choice was accurately described and predicted as obtained reinforcer sequences shifted it to favor one alternative or the other. The effect of a changeover delay was reflected in one parameter, the asymptote, whereas the effect of a difference in overall rate of food delivery was reflected in the other parameter, rate of approach to the asymptote. The model takes choice as a primary dependent variable, not derived by comparison between alternatives-an approach that agrees with the molar view of behaviour.

  6. A practical test for the choice of mixing distribution in discrete choice models

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; Bierlaire, Michel

    2007-01-01

    The choice of a specific distribution for random parameters of discrete choice models is a critical issue in transportation analysis. Indeed, various pieces of research have demonstrated that an inappropriate choice of the distribution may lead to serious bias in model forecast and in the estimated...... means of random parameters. In this paper, we propose a practical test, based on seminonparametric techniques. The test is analyzed both on synthetic and real data, and is shown to be simple and powerful. (c) 2007 Elsevier Ltd. All rights reserved....

  7. Multiobjective constraints for climate model parameter choices: Pragmatic Pareto fronts in CESM1

    Science.gov (United States)

    Langenbrunner, B.; Neelin, J. D.

    2017-09-01

    Global climate models (GCMs) are examples of high-dimensional input-output systems, where model output is a function of many variables, and an update in model physics commonly improves performance in one objective function (i.e., measure of model performance) at the expense of degrading another. Here concepts from multiobjective optimization in the engineering literature are used to investigate parameter sensitivity and optimization in the face of such trade-offs. A metamodeling technique called cut high-dimensional model representation (cut-HDMR) is leveraged in the context of multiobjective optimization to improve GCM simulation of the tropical Pacific climate, focusing on seasonal precipitation, column water vapor, and skin temperature. An evolutionary algorithm is used to solve for Pareto fronts, which are surfaces in objective function space along which trade-offs in GCM performance occur. This approach allows the modeler to visualize trade-offs quickly and identify the physics at play. In some cases, Pareto fronts are small, implying that trade-offs are minimal, optimal parameter value choices are more straightforward, and the GCM is well-functioning. In all cases considered here, the control run was found not to be Pareto-optimal (i.e., not on the front), highlighting an opportunity for model improvement through objectively informed parameter selection. Taylor diagrams illustrate that these improvements occur primarily in field magnitude, not spatial correlation, and they show that specific parameter updates can improve fields fundamental to tropical moist processes—namely precipitation and skin temperature—without significantly impacting others. These results provide an example of how basic elements of multiobjective optimization can facilitate pragmatic GCM tuning processes.

  8. Hybrid discrete choice models: Gained insights versus increasing effort

    Energy Technology Data Exchange (ETDEWEB)

    Mariel, Petr, E-mail: petr.mariel@ehu.es [UPV/EHU, Economía Aplicada III, Avda. Lehendakari Aguire, 83, 48015 Bilbao (Spain); Meyerhoff, Jürgen [Institute for Landscape Architecture and Environmental Planning, Technical University of Berlin, D-10623 Berlin, Germany and The Kiel Institute for the World Economy, Duesternbrooker Weg 120, 24105 Kiel (Germany)

    2016-10-15

    Hybrid choice models expand the standard models in discrete choice modelling by incorporating psychological factors as latent variables. They could therefore provide further insights into choice processes and underlying taste heterogeneity but the costs of estimating these models often significantly increase. This paper aims at comparing the results from a hybrid choice model and a classical random parameter logit. Point of departure for this analysis is whether researchers and practitioners should add hybrid choice models to their suite of models routinely estimated. Our comparison reveals, in line with the few prior studies, that hybrid models gain in efficiency by the inclusion of additional information. The use of one of the two proposed approaches, however, depends on the objective of the analysis. If disentangling preference heterogeneity is most important, hybrid model seems to be preferable. If the focus is on predictive power, a standard random parameter logit model might be the better choice. Finally, we give recommendations for an adequate use of hybrid choice models based on known principles of elementary scientific inference. - Highlights: • The paper compares performance of a Hybrid Choice Model (HCM) and a classical Random Parameter Logit (RPL) model. • The HCM indeed provides insights regarding preference heterogeneity not gained from the RPL. • The RPL has similar predictive power as the HCM in our data. • The costs of estimating HCM seem to be justified when learning more on taste heterogeneity is a major study objective.

  9. Hybrid discrete choice models: Gained insights versus increasing effort

    International Nuclear Information System (INIS)

    Mariel, Petr; Meyerhoff, Jürgen

    2016-01-01

    Hybrid choice models expand the standard models in discrete choice modelling by incorporating psychological factors as latent variables. They could therefore provide further insights into choice processes and underlying taste heterogeneity but the costs of estimating these models often significantly increase. This paper aims at comparing the results from a hybrid choice model and a classical random parameter logit. Point of departure for this analysis is whether researchers and practitioners should add hybrid choice models to their suite of models routinely estimated. Our comparison reveals, in line with the few prior studies, that hybrid models gain in efficiency by the inclusion of additional information. The use of one of the two proposed approaches, however, depends on the objective of the analysis. If disentangling preference heterogeneity is most important, hybrid model seems to be preferable. If the focus is on predictive power, a standard random parameter logit model might be the better choice. Finally, we give recommendations for an adequate use of hybrid choice models based on known principles of elementary scientific inference. - Highlights: • The paper compares performance of a Hybrid Choice Model (HCM) and a classical Random Parameter Logit (RPL) model. • The HCM indeed provides insights regarding preference heterogeneity not gained from the RPL. • The RPL has similar predictive power as the HCM in our data. • The costs of estimating HCM seem to be justified when learning more on taste heterogeneity is a major study objective.

  10. Parameter choice in Banach space regularization under variational inequalities

    International Nuclear Information System (INIS)

    Hofmann, Bernd; Mathé, Peter

    2012-01-01

    The authors study parameter choice strategies for the Tikhonov regularization of nonlinear ill-posed problems in Banach spaces. The effectiveness of any parameter choice for obtaining convergence rates depends on the interplay of the solution smoothness and the nonlinearity structure, and it can be expressed concisely in terms of variational inequalities. Such inequalities are link conditions between the penalty term, the norm misfit and the corresponding error measure. The parameter choices under consideration include an a priori choice, the discrepancy principle as well as the Lepskii principle. For the convenience of the reader, the authors review in an appendix a few instances where the validity of a variational inequality can be established. (paper)

  11. Meta-analysis of choice set generation effects on route choice model estimates and predictions

    DEFF Research Database (Denmark)

    Prato, Carlo Giacomo

    2012-01-01

    are applied for model estimation and results are compared to the ‘true model estimates’. Last, predictions from the simulation of models estimated with objective choice sets are compared to the ‘postulated predicted routes’. A meta-analytical approach allows synthesizing the effect of judgments......Large scale applications of behaviorally realistic transport models pose several challenges to transport modelers on both the demand and the supply sides. On the supply side, path-based solutions to the user assignment equilibrium problem help modelers in enhancing the route choice behavior...... modeling, but require them to generate choice sets by selecting a path generation technique and its parameters according to personal judgments. This paper proposes a methodology and an experimental setting to provide general indications about objective judgments for an effective route choice set generation...

  12. Influence of choice of null network on small-world parameters of structural correlation networks.

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    S M Hadi Hosseini

    Full Text Available In recent years, coordinated variations in brain morphology (e.g., volume, thickness have been employed as a measure of structural association between brain regions to infer large-scale structural correlation networks. Recent evidence suggests that brain networks constructed in this manner are inherently more clustered than random networks of the same size and degree. Thus, null networks constructed by randomizing topology are not a good choice for benchmarking small-world parameters of these networks. In the present report, we investigated the influence of choice of null networks on small-world parameters of gray matter correlation networks in healthy individuals and survivors of acute lymphoblastic leukemia. Three types of null networks were studied: 1 networks constructed by topology randomization (TOP, 2 networks matched to the distributional properties of the observed covariance matrix (HQS, and 3 networks generated from correlation of randomized input data (COR. The results revealed that the choice of null network not only influences the estimated small-world parameters, it also influences the results of between-group differences in small-world parameters. In addition, at higher network densities, the choice of null network influences the direction of group differences in network measures. Our data suggest that the choice of null network is quite crucial for interpretation of group differences in small-world parameters of structural correlation networks. We argue that none of the available null models is perfect for estimation of small-world parameters for correlation networks and the relative strengths and weaknesses of the selected model should be carefully considered with respect to obtained network measures.

  13. Influence of Choice of Null Network on Small-World Parameters of Structural Correlation Networks

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    Hosseini, S. M. Hadi; Kesler, Shelli R.

    2013-01-01

    In recent years, coordinated variations in brain morphology (e.g., volume, thickness) have been employed as a measure of structural association between brain regions to infer large-scale structural correlation networks. Recent evidence suggests that brain networks constructed in this manner are inherently more clustered than random networks of the same size and degree. Thus, null networks constructed by randomizing topology are not a good choice for benchmarking small-world parameters of these networks. In the present report, we investigated the influence of choice of null networks on small-world parameters of gray matter correlation networks in healthy individuals and survivors of acute lymphoblastic leukemia. Three types of null networks were studied: 1) networks constructed by topology randomization (TOP), 2) networks matched to the distributional properties of the observed covariance matrix (HQS), and 3) networks generated from correlation of randomized input data (COR). The results revealed that the choice of null network not only influences the estimated small-world parameters, it also influences the results of between-group differences in small-world parameters. In addition, at higher network densities, the choice of null network influences the direction of group differences in network measures. Our data suggest that the choice of null network is quite crucial for interpretation of group differences in small-world parameters of structural correlation networks. We argue that none of the available null models is perfect for estimation of small-world parameters for correlation networks and the relative strengths and weaknesses of the selected model should be carefully considered with respect to obtained network measures. PMID:23840672

  14. The drift diffusion model as the choice rule in reinforcement learning.

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    Pedersen, Mads Lund; Frank, Michael J; Biele, Guido

    2017-08-01

    Current reinforcement-learning models often assume simplified decision processes that do not fully reflect the dynamic complexities of choice processes. Conversely, sequential-sampling models of decision making account for both choice accuracy and response time, but assume that decisions are based on static decision values. To combine these two computational models of decision making and learning, we implemented reinforcement-learning models in which the drift diffusion model describes the choice process, thereby capturing both within- and across-trial dynamics. To exemplify the utility of this approach, we quantitatively fit data from a common reinforcement-learning paradigm using hierarchical Bayesian parameter estimation, and compared model variants to determine whether they could capture the effects of stimulant medication in adult patients with attention-deficit hyperactivity disorder (ADHD). The model with the best relative fit provided a good description of the learning process, choices, and response times. A parameter recovery experiment showed that the hierarchical Bayesian modeling approach enabled accurate estimation of the model parameters. The model approach described here, using simultaneous estimation of reinforcement-learning and drift diffusion model parameters, shows promise for revealing new insights into the cognitive and neural mechanisms of learning and decision making, as well as the alteration of such processes in clinical groups.

  15. A simplified model of choice behavior under uncertainty

    Directory of Open Access Journals (Sweden)

    Ching-Hung Lin

    2016-08-01

    Full Text Available The Iowa Gambling Task (IGT has been standardized as a clinical assessment tool (Bechara, 2007. Nonetheless, numerous research groups have attempted to modify IGT models to optimize parameters for predicting the choice behavior of normal controls and patients. A decade ago, most researchers considered the expected utility (EU model (Busemeyer and Stout, 2002 to be the optimal model for predicting choice behavior under uncertainty. However, in recent years, studies have demonstrated the prospect utility (PU models (Ahn et al., 2008 to be more effective than the EU models in the IGT. Nevertheless, after some preliminary tests, we propose that Ahn et al. (2008 PU model is not optimal due to some incompatible results between our behavioral and modeling data. This study aims to modify Ahn et al. (2008 PU model to a simplified model and collected 145 subjects’ IGT performance as the benchmark data for comparison. In our simplified PU model, the best goodness-of-fit was found mostly while α approaching zero. More specifically, we retested the key parameters α, λ , and A in the PU model. Notably, the power of influence of the parameters α, λ, and A has a hierarchical order in terms of manipulating the goodness-of-fit in the PU model. Additionally, we found that the parameters λ and A may be ineffective when the parameter α is close to zero in the PU model. The present simplified model demonstrated that decision makers mostly adopted the strategy of gain-stay-loss-shift rather than foreseeing the long-term outcome. However, there still have other behavioral variables that are not well revealed under these dynamic uncertainty situations. Therefore, the optimal behavioral models may not have been found. In short, the best model for predicting choice behavior under dynamic-uncertainty situations should be further evaluated.

  16. Exclusive queueing model including the choice of service windows

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    Tanaka, Masahiro; Yanagisawa, Daichi; Nishinari, Katsuhiro

    2018-01-01

    In a queueing system involving multiple service windows, choice behavior is a significant concern. This paper incorporates the choice of service windows into a queueing model with a floor represented by discrete cells. We contrived a logit-based choice algorithm for agents considering the numbers of agents and the distances to all service windows. Simulations were conducted with various parameters of agent choice preference for these two elements and for different floor configurations, including the floor length and the number of service windows. We investigated the model from the viewpoint of transit times and entrance block rates. The influences of the parameters on these factors were surveyed in detail and we determined that there are optimum floor lengths that minimize the transit times. In addition, we observed that the transit times were determined almost entirely by the entrance block rates. The results of the presented model are relevant to understanding queueing systems including the choice of service windows and can be employed to optimize facility design and floor management.

  17. An adaptive regularization parameter choice strategy for multispectral bioluminescence tomography

    Energy Technology Data Exchange (ETDEWEB)

    Feng Jinchao; Qin Chenghu; Jia Kebin; Han Dong; Liu Kai; Zhu Shouping; Yang Xin; Tian Jie [Medical Image Processing Group, Institute of Automation, Chinese Academy of Sciences, P. O. Box 2728, Beijing 100190 (China); College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124 (China); Medical Image Processing Group, Institute of Automation, Chinese Academy of Sciences, P. O. Box 2728, Beijing 100190 (China); Medical Image Processing Group, Institute of Automation, Chinese Academy of Sciences, P. O. Box 2728, Beijing 100190 (China) and School of Life Sciences and Technology, Xidian University, Xi' an 710071 (China)

    2011-11-15

    Purpose: Bioluminescence tomography (BLT) provides an effective tool for monitoring physiological and pathological activities in vivo. However, the measured data in bioluminescence imaging are corrupted by noise. Therefore, regularization methods are commonly used to find a regularized solution. Nevertheless, for the quality of the reconstructed bioluminescent source obtained by regularization methods, the choice of the regularization parameters is crucial. To date, the selection of regularization parameters remains challenging. With regards to the above problems, the authors proposed a BLT reconstruction algorithm with an adaptive parameter choice rule. Methods: The proposed reconstruction algorithm uses a diffusion equation for modeling the bioluminescent photon transport. The diffusion equation is solved with a finite element method. Computed tomography (CT) images provide anatomical information regarding the geometry of the small animal and its internal organs. To reduce the ill-posedness of BLT, spectral information and the optimal permissible source region are employed. Then, the relationship between the unknown source distribution and multiview and multispectral boundary measurements is established based on the finite element method and the optimal permissible source region. Since the measured data are noisy, the BLT reconstruction is formulated as l{sub 2} data fidelity and a general regularization term. When choosing the regularization parameters for BLT, an efficient model function approach is proposed, which does not require knowledge of the noise level. This approach only requests the computation of the residual and regularized solution norm. With this knowledge, we construct the model function to approximate the objective function, and the regularization parameter is updated iteratively. Results: First, the micro-CT based mouse phantom was used for simulation verification. Simulation experiments were used to illustrate why multispectral data were used

  18. Iterative choice of the optimal regularization parameter in TV image deconvolution

    International Nuclear Information System (INIS)

    Sixou, B; Toma, A; Peyrin, F; Denis, L

    2013-01-01

    We present an iterative method for choosing the optimal regularization parameter for the linear inverse problem of Total Variation image deconvolution. This approach is based on the Morozov discrepancy principle and on an exponential model function for the data term. The Total Variation image deconvolution is performed with the Alternating Direction Method of Multipliers (ADMM). With a smoothed l 2 norm, the differentiability of the value of the Lagrangian at the saddle point can be shown and an approximate model function obtained. The choice of the optimal parameter can be refined with a Newton method. The efficiency of the method is demonstrated on a blurred and noisy bone CT cross section

  19. THE INFLUENCE OF CONVERSION MODEL CHOICE FOR EROSION RATE ESTIMATION AND THE SENSITIVITY OF THE RESULTS TO CHANGES IN THE MODEL PARAMETER

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    Nita Suhartini

    2010-06-01

    Full Text Available A study of soil erosion rates had been done on a slightly and long slope of cultivated area in Ciawi - Bogor, using 137Cs technique. The objective of the present study was to evaluate the applicability of the 137Cs technique in obtaining spatially distributed information of soil redistribution at small catchment. This paper reports the result of the choice of conversion model for erosion rate estimates and the sensitive of the changes in the model parameter. For this purpose, small site was selected, namely landuse I (LU-I. The top of a slope was chosen as a reference site. The erosion/deposit rate of individual sampling points was estimated using the conversion models, namely Proportional Model (PM, Mass Balance Model 1 (MBM1 and Mass Balance Model 2 (MBM2. A comparison of the conversion models showed that the lowest value is obtained by the PM. The MBM1 gave values closer to MBM2, but MBM2 gave a reliable values. In this study, a sensitivity analysis suggest that the conversion models are sensitive to changes in parameters that depend on the site conditions, but insensitive to changes in  parameters that interact to the onset of 137Cs fallout input.   Keywords: soil erosion, environmental radioisotope, cesium

  20. A nested recursive logit model for route choice analysis

    DEFF Research Database (Denmark)

    Mai, Tien; Frejinger, Emma; Fosgerau, Mogens

    2015-01-01

    choices and the model does not require any sampling of choice sets. Furthermore, the model can be consistently estimated and efficiently used for prediction.A key challenge lies in the computation of the value functions, i.e. the expected maximum utility from any position in the network to a destination....... The value functions are the solution to a system of non-linear equations. We propose an iterative method with dynamic accuracy that allows to efficiently solve these systems.We report estimation results and a cross-validation study for a real network. The results show that the NRL model yields sensible......We propose a route choice model that relaxes the independence from irrelevant alternatives property of the logit model by allowing scale parameters to be link specific. Similar to the recursive logit (RL) model proposed by Fosgerau et al. (2013), the choice of path is modeled as a sequence of link...

  1. Street Choice Logit Model for Visitors in Shopping Districts

    Science.gov (United States)

    Kawada, Ko; Yamada, Takashi; Kishimoto, Tatsuya

    2014-01-01

    In this study, we propose two models for predicting people’s activity. The first model is the pedestrian distribution prediction (or postdiction) model by multiple regression analysis using space syntax indices of urban fabric and people distribution data obtained from a field survey. The second model is a street choice model for visitors using multinomial logit model. We performed a questionnaire survey on the field to investigate the strolling routes of 46 visitors and obtained a total of 1211 street choices in their routes. We proposed a utility function, sum of weighted space syntax indices, and other indices, and estimated the parameters for weights on the basis of maximum likelihood. These models consider both street networks, distance from destination, direction of the street choice and other spatial compositions (numbers of pedestrians, cars, shops, and elevation). The first model explains the characteristics of the street where many people tend to walk or stay. The second model explains the mechanism underlying the street choice of visitors and clarifies the differences in the weights of street choice parameters among the various attributes, such as gender, existence of destinations, number of people, etc. For all the attributes considered, the influences of DISTANCE and DIRECTION are strong. On the other hand, the influences of Int.V, SHOPS, CARS, ELEVATION, and WIDTH are different for each attribute. People with defined destinations tend to choose streets that “have more shops, and are wider and lower”. In contrast, people with undefined destinations tend to choose streets of high Int.V. The choice of males is affected by Int.V, SHOPS, WIDTH (positive) and CARS (negative). Females prefer streets that have many shops, and couples tend to choose downhill streets. The behavior of individual persons is affected by all variables. The behavior of people visiting in groups is affected by SHOP and WIDTH (positive). PMID:25379274

  2. Street Choice Logit Model for Visitors in Shopping Districts

    Directory of Open Access Journals (Sweden)

    Ko Kawada

    2014-07-01

    Full Text Available In this study, we propose two models for predicting people’s activity. The first model is the pedestrian distribution prediction (or postdiction model by multiple regression analysis using space syntax indices of urban fabric and people distribution data obtained from a field survey. The second model is a street choice model for visitors using multinomial logit model. We performed a questionnaire survey on the field to investigate the strolling routes of 46 visitors and obtained a total of 1211 street choices in their routes. We proposed a utility function, sum of weighted space syntax indices, and other indices, and estimated the parameters for weights on the basis of maximum likelihood. These models consider both street networks, distance from destination, direction of the street choice and other spatial compositions (numbers of pedestrians, cars, shops, and elevation. The first model explains the characteristics of the street where many people tend to walk or stay. The second model explains the mechanism underlying the street choice of visitors and clarifies the differences in the weights of street choice parameters among the various attributes, such as gender, existence of destinations, number of people, etc. For all the attributes considered, the influences of DISTANCE and DIRECTION are strong. On the other hand, the influences of Int.V, SHOPS, CARS, ELEVATION, and WIDTH are different for each attribute. People with defined destinations tend to choose streets that “have more shops, and are wider and lower”. In contrast, people with undefined destinations tend to choose streets of high Int.V. The choice of males is affected by Int.V, SHOPS, WIDTH (positive and CARS (negative. Females prefer streets that have many shops, and couples tend to choose downhill streets. The behavior of individual persons is affected by all variables. The behavior of people visiting in groups is affected by SHOP and WIDTH (positive.

  3. Modeling Stochastic Route Choice Behaviors with Equivalent Impedance

    Directory of Open Access Journals (Sweden)

    Jun Li

    2015-01-01

    Full Text Available A Logit-based route choice model is proposed to address the overlapping and scaling problems in the traditional multinomial Logit model. The nonoverlapping links are defined as a subnetwork, and its equivalent impedance is explicitly calculated in order to simply network analyzing. The overlapping links are repeatedly merged into subnetworks with Logit-based equivalent travel costs. The choice set at each intersection comprises only the virtual equivalent route without overlapping. In order to capture heterogeneity in perception errors of different sizes of networks, different scale parameters are assigned to subnetworks and they are linked to the topological relationships to avoid estimation burden. The proposed model provides an alternative method to model the stochastic route choice behaviors without the overlapping and scaling problems, and it still maintains the simple and closed-form expression from the MNL model. A link-based loading algorithm based on Dial’s algorithm is proposed to obviate route enumeration and it is suitable to be applied on large-scale networks. Finally a comparison between the proposed model and other route choice models is given by numerical examples.

  4. How the twain can meet: Prospect theory and models of heuristics in risky choice.

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    Pachur, Thorsten; Suter, Renata S; Hertwig, Ralph

    2017-03-01

    Two influential approaches to modeling choice between risky options are algebraic models (which focus on predicting the overt decisions) and models of heuristics (which are also concerned with capturing the underlying cognitive process). Because they rest on fundamentally different assumptions and algorithms, the two approaches are usually treated as antithetical, or even incommensurable. Drawing on cumulative prospect theory (CPT; Tversky & Kahneman, 1992) as the currently most influential instance of a descriptive algebraic model, we demonstrate how the two modeling traditions can be linked. CPT's algebraic functions characterize choices in terms of psychophysical (diminishing sensitivity to probabilities and outcomes) as well as psychological (risk aversion and loss aversion) constructs. Models of heuristics characterize choices as rooted in simple information-processing principles such as lexicographic and limited search. In computer simulations, we estimated CPT's parameters for choices produced by various heuristics. The resulting CPT parameter profiles portray each of the choice-generating heuristics in psychologically meaningful ways-capturing, for instance, differences in how the heuristics process probability information. Furthermore, CPT parameters can reflect a key property of many heuristics, lexicographic search, and track the environment-dependent behavior of heuristics. Finally, we show, both in an empirical and a model recovery study, how CPT parameter profiles can be used to detect the operation of heuristics. We also address the limits of CPT's ability to capture choices produced by heuristics. Our results highlight an untapped potential of CPT as a measurement tool to characterize the information processing underlying risky choice. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Random regret-based discrete-choice modelling: an application to healthcare.

    Science.gov (United States)

    de Bekker-Grob, Esther W; Chorus, Caspar G

    2013-07-01

    A new modelling approach for analysing data from discrete-choice experiments (DCEs) has been recently developed in transport economics based on the notion of regret minimization-driven choice behaviour. This so-called Random Regret Minimization (RRM) approach forms an alternative to the dominant Random Utility Maximization (RUM) approach. The RRM approach is able to model semi-compensatory choice behaviour and compromise effects, while being as parsimonious and formally tractable as the RUM approach. Our objectives were to introduce the RRM modelling approach to healthcare-related decisions, and to investigate its usefulness in this domain. Using data from DCEs aimed at determining valuations of attributes of osteoporosis drug treatments and human papillomavirus (HPV) vaccinations, we empirically compared RRM models, RUM models and Hybrid RUM-RRM models in terms of goodness of fit, parameter ratios and predicted choice probabilities. In terms of model fit, the RRM model did not outperform the RUM model significantly in the case of the osteoporosis DCE data (p = 0.21), whereas in the case of the HPV DCE data, the Hybrid RUM-RRM model outperformed the RUM model (p implied by the two models can vary substantially. Differences in model fit between RUM, RRM and Hybrid RUM-RRM were found to be small. Although our study did not show significant differences in parameter ratios, the RRM and Hybrid RUM-RRM models did feature considerable differences in terms of the trade-offs implied by these ratios. In combination, our results suggest that RRM and Hybrid RUM-RRM modelling approach hold the potential of offering new and policy-relevant insights for health researchers and policy makers.

  6. Choice of the parameters of the cusum algorithms for parameter estimation in the markov modulated poisson process

    OpenAIRE

    Burkatovskaya, Yuliya Borisovna; Kabanova, T.; Khaustov, Pavel Aleksandrovich

    2016-01-01

    CUSUM algorithm for controlling chain state switching in the Markov modulated Poissonprocess was investigated via simulation. Recommendations concerning the parameter choice were givensubject to characteristics of the process. Procedure of the process parameter estimation was described.

  7. Incorporating Responsiveness to Marketing Efforts in Brand Choice Modeling

    Directory of Open Access Journals (Sweden)

    Dennis Fok

    2014-02-01

    Full Text Available We put forward a brand choice model with unobserved heterogeneity that concerns responsiveness to marketing efforts. We introduce two latent segments of households. The first segment is assumed to respond to marketing efforts, while households in the second segment do not do so. Whether a specific household is a member of the first or the second segment at a specific purchase occasion is described by household-specific characteristics and characteristics concerning buying behavior. Households may switch between the two responsiveness states over time. When comparing the performance of our model with alternative choice models that account for various forms of heterogeneity for three different datasets, we find better face validity for our parameters. Our model also forecasts better.

  8. Cognitive Models of Risky Choice: Parameter Stability and Predictive Accuracy of Prospect Theory

    Science.gov (United States)

    Glockner, Andreas; Pachur, Thorsten

    2012-01-01

    In the behavioral sciences, a popular approach to describe and predict behavior is cognitive modeling with adjustable parameters (i.e., which can be fitted to data). Modeling with adjustable parameters allows, among other things, measuring differences between people. At the same time, parameter estimation also bears the risk of overfitting. Are…

  9. TAFV Alternative Fuels and Vehicles Choice Model Documentation; TOPICAL

    International Nuclear Information System (INIS)

    Greene, D.L.

    2001-01-01

    A model for predicting choice of alternative fuel and among alternative vehicle technologies for light-duty motor vehicles is derived. The nested multinomial logit (NML) mathematical framework is used. Calibration of the model is based on information in the existing literature and deduction based on assuming a small number of key parameters, such as the value of time and discount rates. A spreadsheet model has been developed for calibration and preliminary testing of the model

  10. Models for estimating photosynthesis parameters from in situ production profiles

    Science.gov (United States)

    Kovač, Žarko; Platt, Trevor; Sathyendranath, Shubha; Antunović, Suzana

    2017-12-01

    The rate of carbon assimilation in phytoplankton primary production models is mathematically prescribed with photosynthesis irradiance functions, which convert a light flux (energy) into a material flux (carbon). Information on this rate is contained in photosynthesis parameters: the initial slope and the assimilation number. The exactness of parameter values is crucial for precise calculation of primary production. Here we use a model of the daily production profile based on a suite of photosynthesis irradiance functions and extract photosynthesis parameters from in situ measured daily production profiles at the Hawaii Ocean Time-series station Aloha. For each function we recover parameter values, establish parameter distributions and quantify model skill. We observe that the choice of the photosynthesis irradiance function to estimate the photosynthesis parameters affects the magnitudes of parameter values as recovered from in situ profiles. We also tackle the problem of parameter exchange amongst the models and the effect it has on model performance. All models displayed little or no bias prior to parameter exchange, but significant bias following parameter exchange. The best model performance resulted from using optimal parameter values. Model formulation was extended further by accounting for spectral effects and deriving a spectral analytical solution for the daily production profile. The daily production profile was also formulated with time dependent growing biomass governed by a growth equation. The work on parameter recovery was further extended by exploring how to extract photosynthesis parameters from information on watercolumn production. It was demonstrated how to estimate parameter values based on a linearization of the full analytical solution for normalized watercolumn production and from the solution itself, without linearization. The paper complements previous works on photosynthesis irradiance models by analysing the skill and consistency of

  11. Climate change decision-making: Model & parameter uncertainties explored

    Energy Technology Data Exchange (ETDEWEB)

    Dowlatabadi, H.; Kandlikar, M.; Linville, C.

    1995-12-31

    A critical aspect of climate change decision-making is uncertainties in current understanding of the socioeconomic, climatic and biogeochemical processes involved. Decision-making processes are much better informed if these uncertainties are characterized and their implications understood. Quantitative analysis of these uncertainties serve to inform decision makers about the likely outcome of policy initiatives, and help set priorities for research so that outcome ambiguities faced by the decision-makers are reduced. A family of integrated assessment models of climate change have been developed at Carnegie Mellon. These models are distinguished from other integrated assessment efforts in that they were designed from the outset to characterize and propagate parameter, model, value, and decision-rule uncertainties. The most recent of these models is ICAM 2.1. This model includes representation of the processes of demographics, economic activity, emissions, atmospheric chemistry, climate and sea level change and impacts from these changes and policies for emissions mitigation, and adaptation to change. The model has over 800 objects of which about one half are used to represent uncertainty. In this paper we show, that when considering parameter uncertainties, the relative contribution of climatic uncertainties are most important, followed by uncertainties in damage calculations, economic uncertainties and direct aerosol forcing uncertainties. When considering model structure uncertainties we find that the choice of policy is often dominated by model structure choice, rather than parameter uncertainties.

  12. Improving behavioral realism in hybrid energy-economy models using discrete choice studies of personal transportation decisions

    International Nuclear Information System (INIS)

    Horne, M.; Jaccard, M.; Tiedemann, K.

    2005-01-01

    Hybrid energy-economy models combine top-down and bottom-up approaches to explore behaviorally realistic responses to technology-focused policies. This research uses empirically derived discrete choice models to inform key behavioral parameters in CIMS, a hybrid model. The discrete choice models are estimated for vehicle and commuting decisions from a survey of 1150 Canadians. With the choice models integrated into CIMS, we simulate carbon taxes, gasoline vehicle disincentives, and single occupancy vehicle disincentives to show how different policy levers can motivate technological change. We also use the empirical basis for the choice models to portray uncertainty in technological change, costs, and emissions. (author)

  13. Sequential and simultaneous choices: testing the diet selection and sequential choice models.

    Science.gov (United States)

    Freidin, Esteban; Aw, Justine; Kacelnik, Alex

    2009-03-01

    We investigate simultaneous and sequential choices in starlings, using Charnov's Diet Choice Model (DCM) and Shapiro, Siller and Kacelnik's Sequential Choice Model (SCM) to integrate function and mechanism. During a training phase, starlings encountered one food-related option per trial (A, B or R) in random sequence and with equal probability. A and B delivered food rewards after programmed delays (shorter for A), while R ('rejection') moved directly to the next trial without reward. In this phase we measured latencies to respond. In a later, choice, phase, birds encountered the pairs A-B, A-R and B-R, the first implementing a simultaneous choice and the second and third sequential choices. The DCM predicts when R should be chosen to maximize intake rate, and SCM uses latencies of the training phase to predict choices between any pair of options in the choice phase. The predictions of both models coincided, and both successfully predicted the birds' preferences. The DCM does not deal with partial preferences, while the SCM does, and experimental results were strongly correlated to this model's predictions. We believe that the SCM may expose a very general mechanism of animal choice, and that its wider domain of success reflects the greater ecological significance of sequential over simultaneous choices.

  14. Choice of pesticide fate models

    International Nuclear Information System (INIS)

    Balderacchi, Matteo; Trevisan, Marco; Vischetti, Costantino

    2006-01-01

    The choice of a pesticide fate model at field scale is linked to the available input data. The article describes the available pesticide fate models at a field scale and the guidelines for the choice of the suitable model as function of the data input requested [it

  15. Stated Choice Experiments with Complex Ecosystem Changes: The Effect of Information Formats on Estimated Variances and Choice Parameters

    OpenAIRE

    Hoehn, John P.; Lupi, Frank; Kaplowitz, Michael D.

    2010-01-01

    Stated choice experiments about ecosystem changes involve complex information. This study examines whether the format in which ecosystem information is presented to respondents affects stated choice outcomes. Our analysis develops a utility-maximizing model to describe respondent behavior. The model shows how alternative questionnaire formats alter respondents’ use of filtering heuristics and result in differences in preference estimates. Empirical results from a large-scale stated choice e...

  16. Metro passengers’ route choice model and its application considering perceived transfer threshold

    Science.gov (United States)

    Jin, Fanglei; Zhang, Yongsheng; Liu, Shasha

    2017-01-01

    With the rapid development of the Metro network in China, the greatly increased route alternatives make passengers’ route choice behavior and passenger flow assignment more complicated, which presents challenges to the operation management. In this paper, a path sized logit model is adopted to analyze passengers’ route choice preferences considering such parameters as in-vehicle time, number of transfers, and transfer time. Moreover, the “perceived transfer threshold” is defined and included in the utility function to reflect the penalty difference caused by transfer time on passengers’ perceived utility under various numbers of transfers. Next, based on the revealed preference data collected in the Guangzhou Metro, the proposed model is calibrated. The appropriate perceived transfer threshold value and the route choice preferences are analyzed. Finally, the model is applied to a personalized route planning case to demonstrate the engineering practicability of route choice behavior analysis. The results show that the introduction of the perceived transfer threshold is helpful to improve the model’s explanatory abilities. In addition, personalized route planning based on route choice preferences can meet passengers’ diversified travel demands. PMID:28957376

  17. A constraints-induced model of park choice

    NARCIS (Netherlands)

    Stemerding, M.P.; Oppewal, H.; Timmermans, H.J.P.

    1999-01-01

    Conjoint choice models have been used widely in the consumer-choice literature as an approach to measure and predict consumer-choice behavior. These models typically assume that consumer preferences and choice rules are independent from any constraints that might impact the behavior of interest.

  18. The importance of regret minimization in the choice for renewable energy programmes: Evidence from a discrete choice experiment

    International Nuclear Information System (INIS)

    Boeri, Marco; Longo, Alberto

    2017-01-01

    This study provides a methodologically rigorous attempt to disentangle the impact of various factors – unobserved heterogeneity, information and environmental attitudes – on the inclination of individuals to exhibit either a utility maximization or a regret minimization behaviour in a discrete choice experiment for renewable energy programmes described by four attributes: greenhouse gas emissions, power outages, employment in the energy sector, and electricity bill. We explore the ability of different models – multinomial logit, random parameters logit, and hybrid latent class – and of different choice paradigms – utility maximization and regret minimization – in explaining people's choices for renewable energy programmes. The “pure” random regret random parameters logit model explains the choices of our respondents better than other models, indicating that regret is an important choice paradigm, and that choices for renewable energy programmes are mostly driven by regret, rather than by rejoice. In particular, we find that our respondents' choices are driven more by changes in greenhouse gas emissions than by reductions in power outages. Finally, we find that changing the level of information to one attribute has no effect on choices, and that being a member of an environmental organization makes a respondent more likely to be associated with the utility maximization choice framework. - Highlights: • The first paper to use the Random Regret Minimization choice paradigm in energy economics • With a hybrid latent class model, choices conform to either utility or pure random regret. • The pure random regret random parameters logit model outperforms other models. • Reducing greenhouse gas emissions is more important than reducing power outages.

  19. Dynamics in the Parameter Space of a Neuron Model

    Science.gov (United States)

    Paulo, C. Rech

    2012-06-01

    Some two-dimensional parameter-space diagrams are numerically obtained by considering the largest Lyapunov exponent for a four-dimensional thirteen-parameter Hindmarsh—Rose neuron model. Several different parameter planes are considered, and it is shown that depending on the combination of parameters, a typical scenario can be preserved: for some choice of two parameters, the parameter plane presents a comb-shaped chaotic region embedded in a large periodic region. It is also shown that there exist regions close to these comb-shaped chaotic regions, separated by the comb teeth, organizing themselves in period-adding bifurcation cascades.

  20. Value of time determination for the city of Alexandria based on a disaggregate binary mode choice model

    Directory of Open Access Journals (Sweden)

    Mounir Mahmoud Moghazy Abdel-Aal

    2017-12-01

    Full Text Available In the travel demand modeling field, mode choice is the most important decision that affects the resulted road congestion. The behavioral nature of the disaggregate models and the associated advantages of such models over aggregate models have led to their extensive use. This paper proposes a framework to determine the value of time (VoT for the city of Alexandria through calibrating a disaggregate linear-in parameter utility-based binary logit mode choice model of the city. The mode attributes (travel time and travel cost along with traveler attributes (car ownership and income were selected as the utility attributes of the basic model formulation which included 5 models. Three additional alternative utility formulations based on the transformation of the mode attributes including relative travel cost (cost divided by income and log (travel time and the combination of the two transformations together were introduced. The parameter estimation procedure was based on the likelihood maximization technique and was performed in EXCEL. Out of 20 models estimated, only 2 models are considered successful in terms of the parameters estimates correct signs and the magnitude of their significance (t-statistics value. The determination of the VoT serves also in the model validation. The best two models estimated the value of time at LE 11.30/hr and LE 14.50/hr with a relative error of +3.7% and +33.0%, respectively, of the hourly salary of LE 10.9/hr. The proposed two models prove to be sensitive to trip time and income levels as factors affecting the choice mechanism. The sensitivity analysis was performed and proved the model with higher relative error is marginally more robust. Keywords: Transportation modeling, Binary mode choice, Parameter estimation, Value of time, Likelihood maximization, Sensitivity analysis

  1. Choice of primary transducers of beam parameters for measuring and control systems of charged particle accelerators

    International Nuclear Information System (INIS)

    Rybin, V.M.

    1981-01-01

    Investigations on classification of primary transducers (pT) of the main parameters of charged particle beams are conducted for development of the common series on the base of program- controlled module systems for measuring the parameters of charged particle beams. The PT classification is exercised by: the physical principle of single transformation, the degree of effect on the beam, principle of operation, design, performance, location. It is shown that the optimal choice of PT and their parameters should be necessarily executed in several stages: estimation of the limiting possibilities of PT; choice of PT by time and metrological characteristics as well as sensitivity for the determined operation conditions; choice of the PT by the degree of effect on the beam: choice of the PT type with account of its design performance and location, determination of PT parameters with account of possibility of information, energy and design compatibility of the used standard. The classification results of magnetoinduction and acoustic transducers have shown that the number of their modifications does not exceed 100 [ru

  2. The restricted stochastic user equilibrium with threshold model: Large-scale application and parameter testing

    DEFF Research Database (Denmark)

    Rasmussen, Thomas Kjær; Nielsen, Otto Anker; Watling, David P.

    2017-01-01

    Equilibrium model (DUE), by combining the strengths of the Boundedly Rational User Equilibrium model and the Restricted Stochastic User Equilibrium model (RSUE). Thereby, the RSUET model reaches an equilibrated solution in which the flow is distributed according to Random Utility Theory among a consistently...... model improves the behavioural realism, especially for high congestion cases. Also, fast and well-behaved convergence to equilibrated solutions among non-universal choice sets is observed across different congestion levels, choice model scale parameters, and algorithm step sizes. Clearly, the results...... highlight that the RSUET outperforms the MNP SUE in terms of convergence, calculation time and behavioural realism. The choice set composition is validated by using 16,618 observed route choices collected by GPS devices in the same network and observing their reproduction within the equilibrated choice sets...

  3. Dynamics of a neuron model in different two-dimensional parameter-spaces

    Science.gov (United States)

    Rech, Paulo C.

    2011-03-01

    We report some two-dimensional parameter-space diagrams numerically obtained for the multi-parameter Hindmarsh-Rose neuron model. Several different parameter planes are considered, and we show that regardless of the combination of parameters, a typical scenario is preserved: for all choice of two parameters, the parameter-space presents a comb-shaped chaotic region immersed in a large periodic region. We also show that exist regions close these chaotic region, separated by the comb teeth, organized themselves in period-adding bifurcation cascades.

  4. Endogenous Reactivity in a Dynamic Model of Consumer’s Choice

    Directory of Open Access Journals (Sweden)

    Ahmad K. Naimzada

    2012-01-01

    Full Text Available We move from a boundedly rational consumer model (Naimzada and Tramontana, 2008, 2010 characterized by a gradient-like decisional process in which, under particular parameters conditions, the asymptotical convergence to the optimal choice does not happen but it does under a least squared learning mechanism. In the present paper, we prove that even a less sophisticated learning mechanism leads to convergence to the rational choice and also prove that convergence is ensured when both learning mechanisms are available. The stability results that we obtain give more strength to the rational behavior assumption of the original model; in fact, the less demanding is the learning mechanism ensuring convergence to the rational behavior, the higher is the probability that even quite naive consumers will learn the composition of their optimum consumption bundles.

  5. Assessing robustness of designs for random effects parameters for nonlinear mixed-effects models.

    Science.gov (United States)

    Duffull, Stephen B; Hooker, Andrew C

    2017-12-01

    Optimal designs for nonlinear models are dependent on the choice of parameter values. Various methods have been proposed to provide designs that are robust to uncertainty in the prior choice of parameter values. These methods are generally based on estimating the expectation of the determinant (or a transformation of the determinant) of the information matrix over the prior distribution of the parameter values. For high dimensional models this can be computationally challenging. For nonlinear mixed-effects models the question arises as to the importance of accounting for uncertainty in the prior value of the variances of the random effects parameters. In this work we explore the influence of the variance of the random effects parameters on the optimal design. We find that the method for approximating the expectation and variance of the likelihood is of potential importance for considering the influence of random effects. The most common approximation to the likelihood, based on a first-order Taylor series approximation, yields designs that are relatively insensitive to the prior value of the variance of the random effects parameters and under these conditions it appears to be sufficient to consider uncertainty on the fixed-effects parameters only.

  6. Hybrid Compensatory-Noncompensatory Choice Sets in Semicompensatory Models

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Bekhor, Shlomo; Shiftan, Yoram

    2013-01-01

    Semicompensatory models represent a choice process consisting of an elimination-based choice set formation on satisfaction of criterion thresholds and a utility-based choice. Current semicompensatory models assume a purely noncompensatory choice set formation and therefore do not support multinom...

  7. The methodology of choice Cam-Clay model parameters for loess subsoil

    Science.gov (United States)

    Nepelski, Krzysztof; Błazik-Borowa, Ewa

    2018-01-01

    The paper deals with the calibration method of FEM subsoil model described by the constitutive Cam-Clay model. The four-storey residential building and solid substrate are modelled. Identification of the substrate is made using research drilling, CPT static tests, DMT Marchetti dilatometer, and laboratory tests. Latter are performed on the intact soil specimens which are taken from the wide planning trench at the depth of foundation. The real building settlements was measured as the vertical displacement of benchmarks. These measurements were carried out periodically during the erection of the building and its operation. Initially, the Cam Clay model parameters were determined on the basis of the laboratory tests, and later, they were corrected by taking into consideration numerical analyses results (whole building and its parts) and real building settlements.

  8. A likelihood-based biostatistical model for analyzing consumer movement in simultaneous choice experiments.

    Science.gov (United States)

    Zeilinger, Adam R; Olson, Dawn M; Andow, David A

    2014-08-01

    Consumer feeding preference among resource choices has critical implications for basic ecological and evolutionary processes, and can be highly relevant to applied problems such as ecological risk assessment and invasion biology. Within consumer choice experiments, also known as feeding preference or cafeteria experiments, measures of relative consumption and measures of consumer movement can provide distinct and complementary insights into the strength, causes, and consequences of preference. Despite the distinct value of inferring preference from measures of consumer movement, rigorous and biologically relevant analytical methods are lacking. We describe a simple, likelihood-based, biostatistical model for analyzing the transient dynamics of consumer movement in a paired-choice experiment. With experimental data consisting of repeated discrete measures of consumer location, the model can be used to estimate constant consumer attraction and leaving rates for two food choices, and differences in choice-specific attraction and leaving rates can be tested using model selection. The model enables calculation of transient and equilibrial probabilities of consumer-resource association, which could be incorporated into larger scale movement models. We explore the effect of experimental design on parameter estimation through stochastic simulation and describe methods to check that data meet model assumptions. Using a dataset of modest sample size, we illustrate the use of the model to draw inferences on consumer preference as well as underlying behavioral mechanisms. Finally, we include a user's guide and computer code scripts in R to facilitate use of the model by other researchers.

  9. Modeling Intercity Mode Choice and Airport Choice in the United States

    OpenAIRE

    Ashiabor, Senanu Y.

    2007-01-01

    The aim of this study was to develop a framework to model travel choice behavior in order to estimate intercity travel demand at nation-level in the United States. Nested and mixed logit models were developed to study national-level intercity transportation in the United States. A separate General Aviation airport choice model to estimates General Aviation person-trips and number of aircraft operations though more than 3000 airports was also developed. The combination of the General Aviati...

  10. Variable selection and model choice in geoadditive regression models.

    Science.gov (United States)

    Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard

    2009-06-01

    Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.

  11. Dynamics of a neuron model in different two-dimensional parameter-spaces

    International Nuclear Information System (INIS)

    Rech, Paulo C.

    2011-01-01

    We report some two-dimensional parameter-space diagrams numerically obtained for the multi-parameter Hindmarsh-Rose neuron model. Several different parameter planes are considered, and we show that regardless of the combination of parameters, a typical scenario is preserved: for all choice of two parameters, the parameter-space presents a comb-shaped chaotic region immersed in a large periodic region. We also show that exist regions close these chaotic region, separated by the comb teeth, organized themselves in period-adding bifurcation cascades. - Research highlights: → We report parameter-spaces obtained for the Hindmarsh-Rose neuron model. → Regardless of the combination of parameters, a typical scenario is preserved. → The scenario presents a comb-shaped chaotic region immersed in a periodic region. → Periodic regions near the chaotic region are in period-adding bifurcation cascades.

  12. Process and Context in Choice Models

    DEFF Research Database (Denmark)

    Ben-Akiva, Moshe; Palma, André de; McFadden, Daniel

    2012-01-01

    . The extended choice framework includes more behavioral richness through the explicit representation of the planning process preceding an action and its dynamics and the effects of context (family, friends, and market) on the process leading to a choice, as well as the inclusion of new types of subjective data...... in choice models. We discuss the key issues involved in applying the extended framework, focusing on richer data requirements, theories, and models, and present three partial demonstrations of the proposed framework. Future research challenges include the development of more comprehensive empirical tests...

  13. Modelling the evolution and consequences of mate choice

    OpenAIRE

    Tazzyman, S. J.

    2010-01-01

    This thesis considers the evolution and the consequences of mate choice across a variety of taxa, using game theoretic, population genetic, and quantitative genetic modelling techniques. Part I is about the evolution of mate choice. In chapter 2, a population genetic model shows that mate choice is even beneficial in self-fertilising species such as Saccharomyces yeast. In chapter 3, a game theoretic model shows that female choice will be strongly dependent upon whether the benefi...

  14. Engineering method of calculation and choice of main parameters of the linear induction accelerator inductors

    Directory of Open Access Journals (Sweden)

    В.Т. Чемерис

    2006-04-01

    Full Text Available  There is a method of simplified calculation and design parameters choice elaborated in this article with corresponding basing for the induction system of electron-beam sterilizer on the base of linear induction accelerator taking into account the parameters of magnetic material for production of cores and parameters of pulsed voltage.

  15. Nonlinear model-based control of the Czochralski process III: Proper choice of manipulated variables and controller parameter scheduling

    Science.gov (United States)

    Neubert, M.; Winkler, J.

    2012-12-01

    This contribution continues an article series [1,2] about the nonlinear model-based control of the Czochralski crystal growth process. The key idea of the presented approach is to use a sophisticated combination of nonlinear model-based and conventional (linear) PI controllers for tracking of both, crystal radius and growth rate. Using heater power and pulling speed as manipulated variables several controller structures are possible. The present part tries to systematize the properties of the materials to be grown in order to get unambiguous decision criteria for a most profitable choice of the controller structure. For this purpose a material specific constant M called interface mobility and a more process specific constant S called system response number are introduced. While the first one summarizes important material properties like thermal conductivity and latent heat the latter one characterizes the process by evaluating the average axial thermal gradients at the phase boundary and the actual growth rate at which the crystal is grown. Furthermore these characteristic numbers are useful for establishing a scheduling strategy for the PI controller parameters in order to improve the controller performance. Finally, both numbers give a better understanding of the general thermal system dynamics of the Czochralski technique.

  16. Choice experiments versus revealed choice models : a before-after study of consumer spatial shopping behavior

    NARCIS (Netherlands)

    Timmermans, H.J.P.; Borgers, A.W.J.; Waerden, van der P.J.H.J.

    1992-01-01

    The purpose of this article is to compare a set of multinomial logit models derived from revealed choice data and a decompositional choice model derived from experimental data in terms of predictive success in the context of consumer spatial shopping behavior. Data on consumer shopping choice

  17. SPOTting Model Parameters Using a Ready-Made Python Package.

    Directory of Open Access Journals (Sweden)

    Tobias Houska

    Full Text Available The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool, an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI. We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.

  18. Brand Choice Modeling Modeling Toothpaste Brand Choice: An Empirical Comparison of Artificial Neural Networks and Multinomial Probit Model

    Directory of Open Access Journals (Sweden)

    Tolga Kaya

    2010-11-01

    Full Text Available The purpose of this study is to compare the performances of Artificial Neural Networks (ANN and Multinomial Probit (MNP approaches in modeling the choice decision within fast moving consumer goods sector. To do this, based on 2597 toothpaste purchases of a panel sample of 404 households, choice models are built and their performances are compared on the 861 purchases of a test sample of 135 households. Results show that ANN's predictions are better while MNP is useful in providing marketing insight.

  19. Choices Matter, but How Do We Model Them?

    Science.gov (United States)

    Brelsford, C.; Dumas, M.

    2017-12-01

    Quantifying interactions between social systems and the physical environment we live within has long been a major scientific challenge. Humans have had such a large influence on our environment that it is no longer reasonable to consider the behavior of an ecological or hydrological system from a purely `physical' perspective: imagining a system that excludes the influence of human choices and behavior. Understanding the role that human social choices play in the energy water nexus is crucial for developing accurate models in that space. The relatively new field of socio-hydrology is making progress towards understanding the role humans play in hydrological systems. While this fact is now widely recognized across the many academic fields that study water systems, we have yet to develop a coherent set of theories for how to model the behavior of these complex and highly interdependent socio-hydrological systems. How should we conceptualize hydrological systems as socio-ecological systems (i.e. system with variables, states, parameters, actors who can control certain variables and a sense of the desirability of states) within which the rigorous study of feedbacks becomes possible? This talk reviews the state of knowledge of how social decisions around water consumption, allocation, and transport influence and are influenced by the physical hydrology that water also moves within. We cover recent papers in socio-hydrology, engineering, water law, and institutional analysis. There have been several calls within socio-hydrology to model human social behavior endogenously along with the hydrology. These improvements are needed across a range of spatial and temporal scales. We suggest two potential strategies for coupled models that allow endogenous water consumption behavior: a social first model which looks for empirical relationships between water consumption and allocation choices and the hydrological state, and a hydrology first model in which we look for regularities

  20. The Dependent Poisson Race Model and Modeling Dependence in Conjoint Choice Experiments

    Science.gov (United States)

    Ruan, Shiling; MacEachern, Steven N.; Otter, Thomas; Dean, Angela M.

    2008-01-01

    Conjoint choice experiments are used widely in marketing to study consumer preferences amongst alternative products. We develop a class of choice models, belonging to the class of Poisson race models, that describe a "random utility" which lends itself to a process-based description of choice. The models incorporate a dependence structure which…

  1. A study on regularization parameter choice in near-field acoustical holography

    DEFF Research Database (Denmark)

    Gomes, Jesper; Hansen, Per Christian

    2008-01-01

    a regularization parameter. These parameter choice methods (PCMs) are attractive, since they require no a priori knowledge about the noise. However, there seems to be no clear understanding of when one PCM is better than the other. This paper presents comparisons of three PCMs: GCV, L-curve and Normalized......), and the Equivalent Source Method (ESM). All combinations of the PCMs and the NAH methods are investigated using simulated measurements with different types of noise added to the input. Finally, the comparisons are carried out for a practical experiment. This aim of this work is to create a better understanding...... of which mechanisms that affect the performance of the different PCMs....

  2. A day in the city : using conjoint choice experiments to model urban tourists' choice of activity packages

    NARCIS (Netherlands)

    Dellaert, B.G.C.; Borgers, A.W.J.; Timmermans, H.J.P.

    1995-01-01

    This paper introduces and tests a conjoint choice experiment approach to modeling urban tourists' choice of activity packages. The joint logit model is introduced as a tool to model choices between combinations of activities and an experimental design approach is proposed that includes attributes

  3. On the choice of minimization parameters using 4 momentum conservation law for particle momenta improvement

    International Nuclear Information System (INIS)

    Anykeyev, V.B.; Zhigunov, V.P.; Spiridonov, A.A.

    1981-01-01

    Special choice of parameters for minimization is offered in the problem of improving estimates for particle momenta in the vertex of the event with the use of 4-momentum conservation law. This choice permits to use any unconditional minimization method instead of that of Lagrange multipliers. The above method is used when analysing the data on the K - +p→n + anti k 0 +π 0 reaction [ru

  4. The choice of a biological model in assessing internal dose equivalent

    International Nuclear Information System (INIS)

    Parodo, A.; Erre, N.

    1977-01-01

    Many are the biological models related to kinetic behavior of radioactive materials within the organism, or in an organ. This is true particularly for the metabolic kinetics of bone-seekers radionuclides described differently by various authors: as a consequence, different forms of the retention function have been used in calculating internal dose equivalent. In our opinion, the retention functions expressed as linear combinations of exponential terms with negative exponents are preferable. In fact, they can be obtained by coherent compartmental analysis and allow a mathematical formalism fairly well definite and easily adaptable to computers. Moreover, it is possible to make use of graphs and monograms already published. The role of the biological model in internal dosimetry, referred to the reliability of the quantitative informations on the kinetic behavior of the radionuclides in the organism and, therefrom, to the accuracy of the doses calculated, is discussed. By comparing the results obtained with different biological models, one finds that the choice of a model is less important than the choice of the value of the appropriate parameters

  5. INFLUENCE OF ROLLING STOCK VIBROACOUSTICAL PARAMETERS ON THE CHOICE OF RATIONAL VALUES OF LOCOMOTIVE RUNNING GEAR

    Directory of Open Access Journals (Sweden)

    Yu. V. Zelenko

    2016-06-01

    Full Text Available Purpose.The success of the traffic on the railways of Ukraine depends on the number and the operational fleet of electric locomotives. Today, the locomotive depot exploit physically and morally outdated locomotives that have low reliability. Modernization of electric locomotives is not economically justified. The aim of this study is to improve the safety of the traction rolling stock by the frequency analysis of dynamical systems, which allows conducting the calculation of the natural (of resonant frequencies of the design and related forms of vibrations.Methodology.The study was conducted by methods of analytical mechanics and mathematical modeling of operating loads of freight locomotive when driving at different speeds on the straight and curved track sections. The theoretical value of the work is the technique of choice of constructive schemes and rational parameters of perspective electric locomotive taking into account the electric inertia ratios and stiffness coefficients of Lagrange second-order equations.Findings. The problems of theoretical research and the development of a mathematical model of the spatial electric vibrations are solved. The theoretical studies of the effect of inertia ratios and stiffness coefficients on the dynamic values and the parameter values of electric locomotive undercarriages are presented.Originality.The set of developed regulations and obtained results is a practical solution to selecting rational parameters of bogies of the freight mainline locomotive for railways of Ukraine. A concept of choice of constructive scheme and rational parameters of perspective locomotive is formulated. It is developed the method of calculation of spatial electric locomotive oscillations to determine its dynamic performance. The software complex for processing the data of experimental studies of dynamic parameters of electric locomotive and comparing the results of the theoretical calculations with the data of full

  6. A constrained multinomial Probit route choice model in the metro network: Formulation, estimation and application

    Science.gov (United States)

    Zhang, Yongsheng; Wei, Heng; Zheng, Kangning

    2017-01-01

    Considering that metro network expansion brings us with more alternative routes, it is attractive to integrate the impacts of routes set and the interdependency among alternative routes on route choice probability into route choice modeling. Therefore, the formulation, estimation and application of a constrained multinomial probit (CMNP) route choice model in the metro network are carried out in this paper. The utility function is formulated as three components: the compensatory component is a function of influencing factors; the non-compensatory component measures the impacts of routes set on utility; following a multivariate normal distribution, the covariance of error component is structured into three parts, representing the correlation among routes, the transfer variance of route, and the unobserved variance respectively. Considering multidimensional integrals of the multivariate normal probability density function, the CMNP model is rewritten as Hierarchical Bayes formula and M-H sampling algorithm based Monte Carlo Markov Chain approach is constructed to estimate all parameters. Based on Guangzhou Metro data, reliable estimation results are gained. Furthermore, the proposed CMNP model also shows a good forecasting performance for the route choice probabilities calculation and a good application performance for transfer flow volume prediction. PMID:28591188

  7. Electrostatic influence in a wire chamber. Choice of geometric parameters of a chamber

    International Nuclear Information System (INIS)

    Comparat, V.; Ovazza, D.

    1979-01-01

    The MWPC electrostatic properties are studied: a positive ponctual charge is put near an anode wire and induced charges on all electrodes of MWPC and their variations with the position of the positive charge are determined. So the best choice for geometrical parameters of a PWPC is given [fr

  8. Human X-chromosome inactivation pattern distributions fit a model of genetically influenced choice better than models of completely random choice

    Science.gov (United States)

    Renault, Nisa K E; Pritchett, Sonja M; Howell, Robin E; Greer, Wenda L; Sapienza, Carmen; Ørstavik, Karen Helene; Hamilton, David C

    2013-01-01

    In eutherian mammals, one X-chromosome in every XX somatic cell is transcriptionally silenced through the process of X-chromosome inactivation (XCI). Females are thus functional mosaics, where some cells express genes from the paternal X, and the others from the maternal X. The relative abundance of the two cell populations (X-inactivation pattern, XIP) can have significant medical implications for some females. In mice, the ‘choice' of which X to inactivate, maternal or paternal, in each cell of the early embryo is genetically influenced. In humans, the timing of XCI choice and whether choice occurs completely randomly or under a genetic influence is debated. Here, we explore these questions by analysing the distribution of XIPs in large populations of normal females. Models were generated to predict XIP distributions resulting from completely random or genetically influenced choice. Each model describes the discrete primary distribution at the onset of XCI, and the continuous secondary distribution accounting for changes to the XIP as a result of development and ageing. Statistical methods are used to compare models with empirical data from Danish and Utah populations. A rigorous data treatment strategy maximises information content and allows for unbiased use of unphased XIP data. The Anderson–Darling goodness-of-fit statistics and likelihood ratio tests indicate that a model of genetically influenced XCI choice better fits the empirical data than models of completely random choice. PMID:23652377

  9. Comparison of Vehicle Choice Models

    Energy Technology Data Exchange (ETDEWEB)

    Stephens, Thomas S. [Argonne National Lab. (ANL), Argonne, IL (United States); Levinson, Rebecca S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brooker, Aaron [National Renewable Energy Lab. (NREL), Golden, CO (United States); Liu, Changzheng [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lin, Zhenhong [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Birky, Alicia [Energetics Incorporated, Columbia, MD (United States); Kontou, Eleftheria [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2017-10-01

    Five consumer vehicle choice models that give projections of future sales shares of light-duty vehicles were compared by running each model using the same inputs, where possible, for two scenarios. The five models compared — LVCFlex, MA3T, LAVE-Trans, ParaChoice, and ADOPT — have been used in support of the Energy Efficiency and Renewable Energy (EERE) Vehicle Technologies Office in analyses of future light-duty vehicle markets under different assumptions about future vehicle technologies and market conditions. The models give projections of sales shares by powertrain technology. Projections made using common, but not identical, inputs showed qualitative agreement, with the exception of ADOPT. ADOPT estimated somewhat lower advanced vehicle shares, mostly composed of hybrid electric vehicles. Other models projected large shares of multiple advanced vehicle powertrains. Projections of models differed in significant ways, including how different technologies penetrated cars and light trucks. Since the models are constructed differently and take different inputs, not all inputs were identical, but were the same or very similar where possible.

  10. Modelling Choice of Information Sources

    Directory of Open Access Journals (Sweden)

    Agha Faisal Habib Pathan

    2013-04-01

    Full Text Available This paper addresses the significance of traveller information sources including mono-modal and multimodal websites for travel decisions. The research follows a decision paradigm developed earlier, involving an information acquisition process for travel choices, and identifies the abstract characteristics of new information sources that deserve further investigation (e.g. by incorporating these in models and studying their significance in model estimation. A Stated Preference experiment is developed and the utility functions are formulated by expanding the travellers' choice set to include different combinations of sources of information. In order to study the underlying choice mechanisms, the resulting variables are examined in models based on different behavioural strategies, including utility maximisation and minimising the regret associated with the foregone alternatives. This research confirmed that RRM (Random Regret Minimisation Theory can fruitfully be used and can provide important insights for behavioural studies. The study also analyses the properties of travel planning websites and establishes a link between travel choices and the content, provenance, design, presence of advertisements, and presentation of information. The results indicate that travellers give particular credence to governmentowned sources and put more importance on their own previous experiences than on any other single source of information. Information from multimodal websites is more influential than that on train-only websites. This in turn is more influential than information from friends, while information from coachonly websites is the least influential. A website with less search time, specific information on users' own criteria, and real time information is regarded as most attractive

  11. Application of an Evolutionary Algorithm for Parameter Optimization in a Gully Erosion Model

    Energy Technology Data Exchange (ETDEWEB)

    Rengers, Francis; Lunacek, Monte; Tucker, Gregory

    2016-06-01

    Herein we demonstrate how to use model optimization to determine a set of best-fit parameters for a landform model simulating gully incision and headcut retreat. To achieve this result we employed the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), an iterative process in which samples are created based on a distribution of parameter values that evolve over time to better fit an objective function. CMA-ES efficiently finds optimal parameters, even with high-dimensional objective functions that are non-convex, multimodal, and non-separable. We ran model instances in parallel on a high-performance cluster, and from hundreds of model runs we obtained the best parameter choices. This method is far superior to brute-force search algorithms, and has great potential for many applications in earth science modeling. We found that parameters representing boundary conditions tended to converge toward an optimal single value, whereas parameters controlling geomorphic processes are defined by a range of optimal values.

  12. An Improved Cognitive Model of the Iowa and Soochow Gambling Tasks With Regard to Model Fitting Performance and Tests of Parameter Consistency

    Directory of Open Access Journals (Sweden)

    Junyi eDai

    2015-03-01

    Full Text Available The Iowa Gambling Task (IGT and the Soochow Gambling Task (SGT are two experience-based risky decision-making tasks for examining decision-making deficits in clinical populations. Several cognitive models, including the expectancy-valence learning model (EVL and the prospect valence learning model (PVL, have been developed to disentangle the motivational, cognitive, and response processes underlying the explicit choices in these tasks. The purpose of the current study was to develop an improved model that can fit empirical data better than the EVL and PVL models and, in addition, produce more consistent parameter estimates across the IGT and SGT. Twenty-six opiate users (mean age 34.23; SD 8.79 and 27 control participants (mean age 35; SD 10.44 completed both tasks. Eighteen cognitive models varying in evaluation, updating, and choice rules were fit to individual data and their performances were compared to that of a statistical baseline model to find a best fitting model. The results showed that the model combining the prospect utility function treating gains and losses separately, the decay-reinforcement updating rule, and the trial-independent choice rule performed the best in both tasks. Furthermore, the winning model produced more consistent individual parameter estimates across the two tasks than any of the other models.

  13. A choice of the parameters of NPP steam generators on the basis of vector optimization

    International Nuclear Information System (INIS)

    Lemeshev, V.U.; Metreveli, D.G.

    1981-01-01

    The optimization problem of the parameters of the designed systems is considered as the problem of multicriterion optimization. It is proposed to choose non-dominant, optimal according to Pareto, parameters. An algorithm is built on the basis of the required and sufficient non-dominant conditions to find non-dominant solutions. This algorithm has been employed to solve the problem on a choice of optimal parameters for the counterflow shell-tube steam generator of NPP of BRGD type [ru

  14. Complexity, parameter sensitivity and parameter transferability in the modelling of floodplain inundation

    Science.gov (United States)

    Bates, P. D.; Neal, J. C.; Fewtrell, T. J.

    2012-12-01

    In this we paper we consider two related questions. First, we address the issue of how much physical complexity is necessary in a model in order to simulate floodplain inundation to within validation data error. This is achieved through development of a single code/multiple physics hydraulic model (LISFLOOD-FP) where different degrees of complexity can be switched on or off. Different configurations of this code are applied to four benchmark test cases, and compared to the results of a number of industry standard models. Second we address the issue of how parameter sensitivity and transferability change with increasing complexity using numerical experiments with models of different physical and geometric intricacy. Hydraulic models are a good example system with which to address such generic modelling questions as: (1) they have a strong physical basis; (2) there is only one set of equations to solve; (3) they require only topography and boundary conditions as input data; and (4) they typically require only a single free parameter, namely boundary friction. In terms of complexity required we show that for the problem of sub-critical floodplain inundation a number of codes of different dimensionality and resolution can be found to fit uncertain model validation data equally well, and that in this situation Occam's razor emerges as a useful logic to guide model selection. We find also find that model skill usually improves more rapidly with increases in model spatial resolution than increases in physical complexity, and that standard approaches to testing hydraulic models against laboratory data or analytical solutions may fail to identify this important fact. Lastly, we find that in benchmark testing studies significant differences can exist between codes with identical numerical solution techniques as a result of auxiliary choices regarding the specifics of model implementation that are frequently unreported by code developers. As a consequence, making sound

  15. A random regret minimization model of travel choice

    NARCIS (Netherlands)

    Chorus, C.G.; Arentze, T.A.; Timmermans, H.J.P.

    2008-01-01

    Abstract This paper presents an alternative to Random Utility-Maximization models of travel choice. Our Random Regret-Minimization model is rooted in Regret Theory and provides several useful features for travel demand analysis. Firstly, it allows for the possibility that choices between travel

  16. Comparison of Vehicle Choice Models

    Energy Technology Data Exchange (ETDEWEB)

    Stephens, Thomas S. [Argonne National Lab. (ANL), Argonne, IL (United States); Levinson, Rebecca S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brooker, Aaron [National Renewable Energy Lab. (NREL), Golden, CO (United States); Liu, Changzheng [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lin, Zhenhong [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Birky, Alicia [Energetics Incorporated, Columbia, MD (United States); Kontou, Eleftheria [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2017-10-31

    Five consumer vehicle choice models that give projections of future sales shares of light-duty vehicles were compared by running each model using the same inputs, where possible, for two scenarios. The five models compared — LVCFlex, MA3T, LAVE-Trans, ParaChoice, and ADOPT — have been used in support of the Energy Efficiency and Renewable Energy (EERE) Vehicle Technologies Office in analyses of future light-duty vehicle markets under different assumptions about future vehicle technologies and market conditions. The models give projections of sales shares by powertrain technology. Projections made using common, but not identical, inputs showed qualitative agreement, with the exception of ADOPT. ADOPT estimated somewhat lower advanced vehicle shares, mostly composed of hybrid electric vehicles. Other models projected large shares of multiple advanced vehicle powertrains. Projections of models differed in significant ways, including how different technologies penetrated cars and light trucks. Since the models are constructed differently and take different inputs, not all inputs were identical, but were the same or very similar where possible. Projections by all models were in close agreement only in the first few years. Although the projections from LVCFlex, MA3T, LAVE-Trans, and ParaChoice were in qualitative agreement, there were significant differences in sales shares given by the different models for individual powertrain types, particularly in later years (2030 and later). For example, projected sales shares of conventional spark-ignition vehicles in 2030 for a given scenario ranged from 35% to 74%. Reasons for such differences are discussed, recognizing that these models were not developed to give quantitatively accurate predictions of future sales shares, but to represent vehicles markets realistically and capture the connections between sales and important influences. Model features were also compared at a high level, and suggestions for further comparison

  17. ParaChoice Model.

    Energy Technology Data Exchange (ETDEWEB)

    Heimer, Brandon Walter [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Levinson, Rebecca Sobel [Sandia National Lab. (SNL-CA), Livermore, CA (United States); West, Todd H. [Sandia National Lab. (SNL-CA), Livermore, CA (United States)

    2017-12-01

    Analysis with the ParaChoice model addresses three barriers from the VTO Multi-Year Program Plan: availability of alternative fuels and electric charging station infrastructure, availability of AFVs and electric drive vehicles, and consumer reluctance to purchase new technologies. In this fiscal year, we first examined the relationship between the availability of alternative fuels and station infrastructure. Specifically, we studied how electric vehicle charging infrastructure affects the ability of EVs to compete with vehicles that rely on mature, conventional petroleum-based fuels. Second, we studied how the availability of less costly AFVs promotes their representation in the LDV fleet. Third, we used ParaChoice trade space analyses to help inform which consumers are reluctant to purchase new technologies. Last, we began analysis of impacts of alternative energy technologies on Class 8 trucks to isolate those that may most efficaciously advance HDV efficiency and petroleum use reduction goals.

  18. Predictors of science, technology, engineering, and mathematics choice options: A meta-analytic path analysis of the social-cognitive choice model by gender and race/ethnicity.

    Science.gov (United States)

    Lent, Robert W; Sheu, Hung-Bin; Miller, Matthew J; Cusick, Megan E; Penn, Lee T; Truong, Nancy N

    2018-01-01

    We tested the interest and choice portion of social-cognitive career theory (SCCT; Lent, Brown, & Hackett, 1994) in the context of science, technology, engineering, and mathematics (STEM) domains. Data from 143 studies (including 196 independent samples) conducted over a 30-year period (1983 through 2013) were subjected to meta-analytic path analyses. The interest/choice model was found to fit the data well over all samples as well as within samples composed primarily of women and men and racial/ethnic minority and majority persons. The model also accounted for large portions of the variance in interests and choice goals within each path analysis. Despite the general predictive utility of SCCT across gender and racial/ethnic groups, we did find that several parameter estimates differed by group. We present both the group similarities and differences and consider their implications for future research, intervention, and theory refinement. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  19. Complexity effects in choice experiments-based models

    NARCIS (Netherlands)

    Dellaert, B.G.C.; Donkers, B.; van Soest, A.H.O.

    2012-01-01

    Many firms rely on choice experiment–based models to evaluate future marketing actions under various market conditions. This research investigates choice complexity (i.e., number of alternatives, number of attributes, and utility similarity between the most attractive alternatives) and individual

  20. Route Choice Model Based on Game Theory for Commuters

    Directory of Open Access Journals (Sweden)

    Licai Yang

    2016-06-01

    Full Text Available The traffic behaviours of commuters may cause traffic congestion during peak hours. Advanced Traffic Information System can provide dynamic information to travellers. Due to the lack of timeliness and comprehensiveness, the provided information cannot satisfy the travellers’ needs. Since the assumptions of traditional route choice model based on Expected Utility Theory conflict with the actual situation, a route choice model based on Game Theory is proposed to provide reliable route choice to commuters in actual situation in this paper. The proposed model treats the alternative routes as game players and utilizes the precision of predicted information and familiarity of traffic condition to build a game. The optimal route can be generated considering Nash Equilibrium by solving the route choice game. Simulations and experimental analysis show that the proposed model can describe the commuters’ routine route choice decisionexactly and the provided route is reliable.

  1. A Bayesian Network Model on the Public Bicycle Choice Behavior of Residents: A Case Study of Xi’an

    Directory of Open Access Journals (Sweden)

    Qiuping Wang

    2017-01-01

    Full Text Available In order to study the main factors affecting the behaviors that city residents make regarding public bicycle choice and to further study the public bicycle user’s personal characteristics and travel characteristics, a travel mode choice model based on a Bayesian network was established. Taking residents of Xi’an as the research object, a K2 algorithm combined with mutual information and expert knowledge was proposed for Bayesian network structure learning. The Bayesian estimation method was used to estimate the parameters of the network, and a Bayesian network model was established to reflect the interactions among the public bicycle choice behaviors along with other major factors. The K-fold cross-validation method was used to validate the model performance, and the hit rate of each travel mode was more than 80%, indicating the precision of the proposed model. Experimental results also present the higher classification accuracy of the proposed model. Therefore, it may be concluded that the resident travel mode choice may be accurately predicted according to the Bayesian network model proposed in our study. Additionally, this model may be employed to analyze and discuss changes in the resident public bicycle choice and to note that they may possibly be influenced by different travelers’ characteristics and trip characteristics.

  2. Global parameter estimation for thermodynamic models of transcriptional regulation.

    Science.gov (United States)

    Suleimenov, Yerzhan; Ay, Ahmet; Samee, Md Abul Hassan; Dresch, Jacqueline M; Sinha, Saurabh; Arnosti, David N

    2013-07-15

    Deciphering the mechanisms involved in gene regulation holds the key to understanding the control of central biological processes, including human disease, population variation, and the evolution of morphological innovations. New experimental techniques including whole genome sequencing and transcriptome analysis have enabled comprehensive modeling approaches to study gene regulation. In many cases, it is useful to be able to assign biological significance to the inferred model parameters, but such interpretation should take into account features that affect these parameters, including model construction and sensitivity, the type of fitness calculation, and the effectiveness of parameter estimation. This last point is often neglected, as estimation methods are often selected for historical reasons or for computational ease. Here, we compare the performance of two parameter estimation techniques broadly representative of local and global approaches, namely, a quasi-Newton/Nelder-Mead simplex (QN/NMS) method and a covariance matrix adaptation-evolutionary strategy (CMA-ES) method. The estimation methods were applied to a set of thermodynamic models of gene transcription applied to regulatory elements active in the Drosophila embryo. Measuring overall fit, the global CMA-ES method performed significantly better than the local QN/NMS method on high quality data sets, but this difference was negligible on lower quality data sets with increased noise or on data sets simplified by stringent thresholding. Our results suggest that the choice of parameter estimation technique for evaluation of gene expression models depends both on quality of data, the nature of the models [again, remains to be established] and the aims of the modeling effort. Copyright © 2013 Elsevier Inc. All rights reserved.

  3. Joint Residence-Workplace Location Choice Model Based on Household Decision Behavior

    Directory of Open Access Journals (Sweden)

    Pengpeng Jiao

    2015-01-01

    Full Text Available Residence location and workplace are the two most important urban land-use types, and there exist strong interdependences between them. Existing researches often assume that one choice dimension is correlated to the other. Using the mixed logit framework, three groups of choice models are developed to illustrate such choice dependencies. First, for all households, this paper presents a basic methodology of the residence location and workplace choice without decision sequence based on the assumption that the two choice behaviors are independent of each other. Second, the paper clusters all households into two groups, choosing residence or workplace first, and formulates the residence location and workplace choice models under the constraint of decision sequence. Third, this paper combines the residence location and workplace together as the choice alternative and puts forward the joint choice model. A questionnaire survey is implemented in Beijing city to collect the data of 1994 households. Estimation results indicate that the joint choice model fits the data significantly better, and the elasticity effects analyses show that the joint choice model reflects the influences of relevant factors to the choice probability well and leads to the job-housing balance.

  4. Consumer choice of theme parks : a conjoint choice model of seasonality effects and variety seeking behavior

    NARCIS (Netherlands)

    Kemperman, A.D.A.M.; Borgers, A.W.J.; Oppewal, H.; Timmermans, H.J.P.

    2000-01-01

    Most existing mathematical models of tourist choice behavior assume that individuals' preferences for choice alternatives remain invariant over time. Although the assumption of invariant preference functions may be reasonable in some choice contexts, this study examines the hypothesis that

  5. Impact of power plant reliability on the choice of operating parameter values

    International Nuclear Information System (INIS)

    Kramer, R.A.

    1985-01-01

    In this thesis, the basic structure for the development of a methodology to evaluate the effect of operating parameters on plant availability and generating system economic dispatch optimization is described. Plant availability is determined by a fault free model. In this model historic, time dependent, component induced forced outage data is utilized as the basis for the calculation of projected plant forced outage rates. The influence of a particular fuel-cycle length at a specific generating station on the operational planning of a multi unit generating system is considered. The basis of the dispatch of units in this analysis is optimal economic operation, i.e., the minimization of the cost of reliability supplying electricity to the system's customers. As a result of the utilization of this technique, a simplified example that considers the choice between a 12- and 18-month fuel cycle length is evaluated in terms of its impact on plant availability, fuel cycle economics and overall optimal generating system economic dispatch. The reliability portion of this methodology is applied to a simplified representation of the recirculation system of a pressurized water reactor nuclear power plant to illustrate the analytic techniques

  6. Lumped-parameter models

    Energy Technology Data Exchange (ETDEWEB)

    Ibsen, Lars Bo; Liingaard, M.

    2006-12-15

    A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. In this technical report the steps of establishing a lumped-parameter model are presented. Following sections are included in this report: Static and dynamic formulation, Simple lumped-parameter models and Advanced lumped-parameter models. (au)

  7. Modelling life trajectories and mode choice using Bayesian belief networks

    NARCIS (Netherlands)

    Verhoeven, M.

    2010-01-01

    Traditionally, transport mode choice was primarily examined as a stand alone problem. Given a purpose and destination, the choice of transport mode was modelled as a function of the various attributes of the transport mode alternatives. Later, transport mode choice decisions were modelled as part of

  8. Exploring the Influence of Attitudes to Walking and Cycling on Commute Mode Choice Using a Hybrid Choice Model

    Directory of Open Access Journals (Sweden)

    Chuan Ding

    2017-01-01

    Full Text Available Transport-related problems, such as automobile dependence, traffic congestion, and greenhouse emissions, lead to a great burden on the environment. In developing countries like China, in order to improve the air quality, promoting sustainable travel modes to reduce the automobile usage is gradually recognized as an emerging national concern. Though there are many studies related to the physically active modes (e.g., walking and cycling, the research on the influence of attitudes to active modes on travel behavior is limited, especially in China. To fill up this gap, this paper focuses on examining the impact of attitudes to walking and cycling on commute mode choice. Using the survey data collected in China cities, an integrated discrete choice model and the structural equation model are proposed. By applying the hybrid choice model, not only the role of the latent attitude played in travel mode choice, but also the indirect effects of social factors on travel mode choice are obtained. The comparison indicates that the hybrid choice model outperforms the traditional model. This study is expected to provide a better understanding for urban planners on the influential factors of green travel modes.

  9. Generalized outcome-based strategy classification: comparing deterministic and probabilistic choice models.

    Science.gov (United States)

    Hilbig, Benjamin E; Moshagen, Morten

    2014-12-01

    Model comparisons are a vital tool for disentangling which of several strategies a decision maker may have used--that is, which cognitive processes may have governed observable choice behavior. However, previous methodological approaches have been limited to models (i.e., decision strategies) with deterministic choice rules. As such, psychologically plausible choice models--such as evidence-accumulation and connectionist models--that entail probabilistic choice predictions could not be considered appropriately. To overcome this limitation, we propose a generalization of Bröder and Schiffer's (Journal of Behavioral Decision Making, 19, 361-380, 2003) choice-based classification method, relying on (1) parametric order constraints in the multinomial processing tree framework to implement probabilistic models and (2) minimum description length for model comparison. The advantages of the generalized approach are demonstrated through recovery simulations and an experiment. In explaining previous methods and our generalization, we maintain a nontechnical focus--so as to provide a practical guide for comparing both deterministic and probabilistic choice models.

  10. Think twice before you book? Modelling the choice of public vs private dentist in a choice experiment.

    Science.gov (United States)

    Kiiskinen, Urpo; Suominen-Taipale, Anna Liisa; Cairns, John

    2010-06-01

    This study concerns the choice of primary dental service provider by consumers. If the health service delivery system allows individuals to choose between public-care providers or if complementary private services are available, it is typically assumed that utilisation is a three-stage decision process. The patient first makes a decision to seek care, and then chooses the service provider. The final stage, involving decisions over the amount and form of treatment, is not considered here. The paper reports a discrete choice experiment (DCE) designed to evaluate attributes affecting individuals' choice of dental-care provider. The feasibility of the DCE approach in modelling consumers' choice in the context of non-acute need for dental care is assessed. The aim is to test whether a separate two-stage logit, a multinomial logit, or a nested logit best fits the choice process of consumers. A nested logit model of indirect utility functions is estimated and inclusive value (IV) constraints are tested for modelling implications. The results show that non-trading behaviour has an impact on the choice of appropriate modelling technique, but is to some extent dependent on the choice of scenarios offered. It is concluded that for traders multinomial logit is appropriate, whereas for non-traders and on average the nested logit is the method supported by the analyses. The consistent finding in all subgroup analyses is that the traditional two-stage decision process is found to be implausible in the context of consumer's choice of dental-care provider.

  11. Misclassification in binary choice models

    Czech Academy of Sciences Publication Activity Database

    Meyer, B. D.; Mittag, Nikolas

    2017-01-01

    Roč. 200, č. 2 (2017), s. 295-311 ISSN 0304-4076 Institutional support: RVO:67985998 Keywords : measurement error * binary choice models * program take-up Subject RIV: AH - Economics OBOR OECD: Economic Theory Impact factor: 1.633, year: 2016

  12. Assessing the relative importance of parameter and forcing uncertainty and their interactions in conceptual hydrological model simulations

    Science.gov (United States)

    Mockler, E. M.; Chun, K. P.; Sapriza-Azuri, G.; Bruen, M.; Wheater, H. S.

    2016-11-01

    Predictions of river flow dynamics provide vital information for many aspects of water management including water resource planning, climate adaptation, and flood and drought assessments. Many of the subjective choices that modellers make including model and criteria selection can have a significant impact on the magnitude and distribution of the output uncertainty. Hydrological modellers are tasked with understanding and minimising the uncertainty surrounding streamflow predictions before communicating the overall uncertainty to decision makers. Parameter uncertainty in conceptual rainfall-runoff models has been widely investigated, and model structural uncertainty and forcing data have been receiving increasing attention. This study aimed to assess uncertainties in streamflow predictions due to forcing data and the identification of behavioural parameter sets in 31 Irish catchments. By combining stochastic rainfall ensembles and multiple parameter sets for three conceptual rainfall-runoff models, an analysis of variance model was used to decompose the total uncertainty in streamflow simulations into contributions from (i) forcing data, (ii) identification of model parameters and (iii) interactions between the two. The analysis illustrates that, for our subjective choices, hydrological model selection had a greater contribution to overall uncertainty, while performance criteria selection influenced the relative intra-annual uncertainties in streamflow predictions. Uncertainties in streamflow predictions due to the method of determining parameters were relatively lower for wetter catchments, and more evenly distributed throughout the year when the Nash-Sutcliffe Efficiency of logarithmic values of flow (lnNSE) was the evaluation criterion.

  13. Modeling of Parameters of Subcritical Assembly SAD

    CERN Document Server

    Petrochenkov, S; Puzynin, I

    2005-01-01

    The accepted conceptual design of the experimental Subcritical Assembly in Dubna (SAD) is based on the MOX core with a nominal unit capacity of 25 kW (thermal). This corresponds to the multiplication coefficient $k_{\\rm eff} =0.95$ and accelerator beam power 1 kW. A subcritical assembly driven with the existing 660 MeV proton accelerator at the Joint Institute for Nuclear Research has been modelled in order to make choice of the optimal parameters for the future experiments. The Monte Carlo method was used to simulate neutron spectra, energy deposition and doses calculations. Some of the calculation results are presented in the paper.

  14. Impact of implementation choices on quantitative predictions of cell-based computational models

    Science.gov (United States)

    Kursawe, Jochen; Baker, Ruth E.; Fletcher, Alexander G.

    2017-09-01

    'Cell-based' models provide a powerful computational tool for studying the mechanisms underlying the growth and dynamics of biological tissues in health and disease. An increasing amount of quantitative data with cellular resolution has paved the way for the quantitative parameterisation and validation of such models. However, the numerical implementation of cell-based models remains challenging, and little work has been done to understand to what extent implementation choices may influence model predictions. Here, we consider the numerical implementation of a popular class of cell-based models called vertex models, which are often used to study epithelial tissues. In two-dimensional vertex models, a tissue is approximated as a tessellation of polygons and the vertices of these polygons move due to mechanical forces originating from the cells. Such models have been used extensively to study the mechanical regulation of tissue topology in the literature. Here, we analyse how the model predictions may be affected by numerical parameters, such as the size of the time step, and non-physical model parameters, such as length thresholds for cell rearrangement. We find that vertex positions and summary statistics are sensitive to several of these implementation parameters. For example, the predicted tissue size decreases with decreasing cell cycle durations, and cell rearrangement may be suppressed by large time steps. These findings are counter-intuitive and illustrate that model predictions need to be thoroughly analysed and implementation details carefully considered when applying cell-based computational models in a quantitative setting.

  15. The Drift Diffusion Model can account for the accuracy and reaction time of value-based choices under high and low time pressure

    Directory of Open Access Journals (Sweden)

    Milica Milosavljevic

    2010-10-01

    Full Text Available An important open problem is how values are compared to make simple choices. A natural hypothesis is that the brain carries out the computations associated with the value comparisons in a manner consistent with the Drift Diffusion Model (DDM, since this model has been able to account for a large amount of data in other domains. We investigated the ability of four different versions of the DDM to explain the data in a real binary food choice task under conditions of high and low time pressure. We found that a seven-parameter version of the DDM can account for the choice and reaction time data with high-accuracy, in both the high and low time pressure conditions. The changes associated with the introduction of time pressure could be traced to changes in two key model parameters: the barrier height and the noise in the slope of the drift process.

  16. Harvest choice and timber supply models for forest forecasting

    Science.gov (United States)

    Maksym Polyakov; David N Wear

    2010-01-01

    Timber supply has traditionally been modeled using aggregate data, whereas individual harvest choices have been shown to be sensitive to the vintage and condition of forest capital stocks. In this article, we build aggregate supply models for four roundwood products in a seven-state region of the US South directly from stand-level harvest choice models applied to...

  17. Uncertainty in dual permeability model parameters for structured soils

    Science.gov (United States)

    Arora, B.; Mohanty, B. P.; McGuire, J. T.

    2012-01-01

    Successful application of dual permeability models (DPM) to predict contaminant transport is contingent upon measured or inversely estimated soil hydraulic and solute transport parameters. The difficulty in unique identification of parameters for the additional macropore- and matrix-macropore interface regions, and knowledge about requisite experimental data for DPM has not been resolved to date. Therefore, this study quantifies uncertainty in dual permeability model parameters of experimental soil columns with different macropore distributions (single macropore, and low- and high-density multiple macropores). Uncertainty evaluation is conducted using adaptive Markov chain Monte Carlo (AMCMC) and conventional Metropolis-Hastings (MH) algorithms while assuming 10 out of 17 parameters to be uncertain or random. Results indicate that AMCMC resolves parameter correlations and exhibits fast convergence for all DPM parameters while MH displays large posterior correlations for various parameters. This study demonstrates that the choice of parameter sampling algorithms is paramount in obtaining unique DPM parameters when information on covariance structure is lacking, or else additional information on parameter correlations must be supplied to resolve the problem of equifinality of DPM parameters. This study also highlights the placement and significance of matrix-macropore interface in flow experiments of soil columns with different macropore densities. Histograms for certain soil hydraulic parameters display tri-modal characteristics implying that macropores are drained first followed by the interface region and then by pores of the matrix domain in drainage experiments. Results indicate that hydraulic properties and behavior of the matrix-macropore interface is not only a function of saturated hydraulic conductivity of the macroporematrix interface (Ksa) and macropore tortuosity (lf) but also of other parameters of the matrix and macropore domains.

  18. Risk Route Choice Analysis and the Equilibrium Model under Anticipated Regret Theory

    Directory of Open Access Journals (Sweden)

    pengcheng yuan

    2014-02-01

    Full Text Available The assumption about travellers’ route choice behaviour has major influence on the traffic flow equilibrium analysis. Previous studies about the travellers’ route choice were mainly based on the expected utility maximization theory. However, with the gradually increasing knowledge about the uncertainty of the transportation system, the researchers have realized that there is much constraint in expected util­ity maximization theory, because expected utility maximiza­tion requires travellers to be ‘absolutely rational’; but in fact, travellers are not truly ‘absolutely rational’. The anticipated regret theory proposes an alternative framework to the tra­ditional risk-taking in route choice behaviour which might be more scientific and reasonable. We have applied the antici­pated regret theory to the analysis of the risk route choosing process, and constructed an anticipated regret utility func­tion. By a simple case which includes two parallel routes, the route choosing results influenced by the risk aversion degree, regret degree and the environment risk degree have been analyzed. Moreover, the user equilibrium model based on the anticipated regret theory has been established. The equivalence and the uniqueness of the model are proved; an efficacious algorithm is also proposed to solve the model. Both the model and the algorithm are demonstrated in a real network. By an experiment, the model results and the real data have been compared. It was found that the model re­sults can be similar to the real data if a proper regret degree parameter is selected. This illustrates that the model can better explain the risk route choosing behaviour. Moreover, it was also found that the traveller’ regret degree increases when the environment becomes more and more risky.

  19. Inter-temporal variation in the travel time and travel cost parameters of transport models

    OpenAIRE

    Börjesson, Maria

    2012-01-01

    The parameters for travel time and travel cost are central in travel demand forecasting models. Since valuation of infrastructure investments requires prediction of travel demand for future evaluation years, inter-temporal variation of the travel time and travel cost parameters is a key issue in forecasting. Using two identical stated choice experiments conducted among Swedish drivers with an interval of 13 years, 1994 and 2007, this paper estimates the inter-temporal variation in travel time...

  20. Discrete choice modeling of season choice for Minnesota turkey hunters

    Science.gov (United States)

    Schroeder, Susan A.; Fulton, David C.; Cornicelli, Louis; Merchant, Steven S.

    2018-01-01

    Recreational turkey hunting exemplifies the interdisciplinary nature of modern wildlife management. Turkey populations in Minnesota have reached social or biological carrying capacities in many areas, and changes to turkey hunting regulations have been proposed by stakeholders and wildlife managers. This study employed discrete stated choice modeling to enhance understanding of turkey hunter preferences about regulatory alternatives. We distributed mail surveys to 2,500 resident turkey hunters. Results suggest that, compared to season structure and lotteries, additional permits and level of potential interference from other hunters most influenced hunter preferences for regulatory alternatives. Low hunter interference was preferred to moderate or high interference. A second permit issued only to unsuccessful hunters was preferred to no second permit or permits for all hunters. Results suggest that utility is not strictly defined by harvest or an individual's material gain but can involve preference for other outcomes that on the surface do not materially benefit an individual. Discrete stated choice modeling offers wildlife managers an effective way to assess constituent preferences related to new regulations before implementing them. 

  1. Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software.

    Science.gov (United States)

    Lancsar, Emily; Fiebig, Denzil G; Hole, Arne Risa

    2017-07-01

    We provide a user guide on the analysis of data (including best-worst and best-best data) generated from discrete-choice experiments (DCEs), comprising a theoretical review of the main choice models followed by practical advice on estimation and post-estimation. We also provide a review of standard software. In providing this guide, we endeavour to not only provide guidance on choice modelling but to do so in a way that provides a 'way in' for researchers to the practicalities of data analysis. We argue that choice of modelling approach depends on the research questions, study design and constraints in terms of quality/quantity of data and that decisions made in relation to analysis of choice data are often interdependent rather than sequential. Given the core theory and estimation of choice models is common across settings, we expect the theoretical and practical content of this paper to be useful to researchers not only within but also beyond health economics.

  2. Closing the gap between behavior and models in route choice: The role of spatiotemporal constraints and latent traits in choice set formation

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    2012-01-01

    not account for individual-related spatiotemporal constraints. This paper reduces the gap by proposing a route choice model incorporating spatiotemporal constraints and latent traits. The proposed approach combines stochastic route generation with a latent variable semi-compensatory model representing......A considerable gap exists between the behavioral paradigm of choice set formation in route choice and its representation in route choice modeling. While travelers form their viable choice set by retaining routes that satisfy spatiotemporal constraints, existing route generation techniques do...

  3. Misclassification in binary choice models

    Czech Academy of Sciences Publication Activity Database

    Meyer, B. D.; Mittag, Nikolas

    2017-01-01

    Roč. 200, č. 2 (2017), s. 295-311 ISSN 0304-4076 R&D Projects: GA ČR(CZ) GJ16-07603Y Institutional support: Progres-Q24 Keywords : measurement error * binary choice models * program take-up Subject RIV: AH - Economics OBOR OECD: Economic Theory Impact factor: 1.633, year: 2016

  4. Modeling Dynamic Food Choice Processes to Understand Dietary Intervention Effects.

    Science.gov (United States)

    Marcum, Christopher Steven; Goldring, Megan R; McBride, Colleen M; Persky, Susan

    2018-02-17

    Meal construction is largely governed by nonconscious and habit-based processes that can be represented as a collection of in dividual, micro-level food choices that eventually give rise to a final plate. Despite this, dietary behavior intervention research rarely captures these micro-level food choice processes, instead measuring outcomes at aggregated levels. This is due in part to a dearth of analytic techniques to model these dynamic time-series events. The current article addresses this limitation by applying a generalization of the relational event framework to model micro-level food choice behavior following an educational intervention. Relational event modeling was used to model the food choices that 221 mothers made for their child following receipt of an information-based intervention. Participants were randomized to receive either (a) control information; (b) childhood obesity risk information; (c) childhood obesity risk information plus a personalized family history-based risk estimate for their child. Participants then made food choices for their child in a virtual reality-based food buffet simulation. Micro-level aspects of the built environment, such as the ordering of each food in the buffet, were influential. Other dynamic processes such as choice inertia also influenced food selection. Among participants receiving the strongest intervention condition, choice inertia decreased and the overall rate of food selection increased. Modeling food selection processes can elucidate the points at which interventions exert their influence. Researchers can leverage these findings to gain insight into nonconscious and uncontrollable aspects of food selection that influence dietary outcomes, which can ultimately improve the design of dietary interventions.

  5. Estimating Parameters in Physical Models through Bayesian Inversion: A Complete Example

    KAUST Repository

    Allmaras, Moritz

    2013-02-07

    All mathematical models of real-world phenomena contain parameters that need to be estimated from measurements, either for realistic predictions or simply to understand the characteristics of the model. Bayesian statistics provides a framework for parameter estimation in which uncertainties about models and measurements are translated into uncertainties in estimates of parameters. This paper provides a simple, step-by-step example-starting from a physical experiment and going through all of the mathematics-to explain the use of Bayesian techniques for estimating the coefficients of gravity and air friction in the equations describing a falling body. In the experiment we dropped an object from a known height and recorded the free fall using a video camera. The video recording was analyzed frame by frame to obtain the distance the body had fallen as a function of time, including measures of uncertainty in our data that we describe as probability densities. We explain the decisions behind the various choices of probability distributions and relate them to observed phenomena. Our measured data are then combined with a mathematical model of a falling body to obtain probability densities on the space of parameters we seek to estimate. We interpret these results and discuss sources of errors in our estimation procedure. © 2013 Society for Industrial and Applied Mathematics.

  6. An aggregate method to calibrate the reference point of cumulative prospect theory-based route choice model for urban transit network

    Science.gov (United States)

    Zhang, Yufeng; Long, Man; Luo, Sida; Bao, Yu; Shen, Hanxia

    2015-12-01

    Transit route choice model is the key technology of public transit systems planning and management. Traditional route choice models are mostly based on expected utility theory which has an evident shortcoming that it cannot accurately portray travelers' subjective route choice behavior for their risk preferences are not taken into consideration. Cumulative prospect theory (CPT), a brand new theory, can be used to describe travelers' decision-making process under the condition of uncertainty of transit supply and risk preferences of multi-type travelers. The method to calibrate the reference point, a key parameter to CPT-based transit route choice model, determines the precision of the model to a great extent. In this paper, a new method is put forward to obtain the value of reference point which combines theoretical calculation and field investigation results. Comparing the proposed method with traditional method, it shows that the new method can promote the quality of CPT-based model by improving the accuracy in simulating travelers' route choice behaviors based on transit trip investigation from Nanjing City, China. The proposed method is of great significance to logical transit planning and management, and to some extent makes up the defect that obtaining the reference point is solely based on qualitative analysis.

  7. Essays on portfolio choice with Bayesian methods

    OpenAIRE

    Kebabci, Deniz

    2007-01-01

    How investors should allocate assets to their portfolios in the presence of predictable components in asset returns is a question of great importance in finance. While early studies took the return generating process as given, recent studies have addressed issues such as parameter estimation and model uncertainty. My dissertation develops Bayesian methods for portfolio choice - and industry allocation in particular - under parameter and model uncertainty. The first chapter of my dissertation,...

  8. Choices and changes: Eccles' Expectancy-Value model and upper-secondary school students' longitudinal reflections about their choice of a STEM education

    Science.gov (United States)

    Lykkegaard, Eva; Ulriksen, Lars

    2016-03-01

    During the past 30 years, Eccles' comprehensive social-psychological Expectancy-Value Model of Motivated Behavioural Choices (EV-MBC model) has been proven suitable for studying educational choices related to Science, Technology, Engineering and/or Mathematics (STEM). The reflections of 15 students in their last year in upper-secondary school concerning their choice of tertiary education were examined using quantitative EV-MBC surveys and repeated qualitative interviews. This article presents the analyses of three cases in detail. The analytical focus was whether the factors indicated in the EV-MBC model could be used to detect significant changes in the students' educational choice processes. An important finding was that the quantitative EV-MBC surveys and the qualitative interviews gave quite different results concerning the students' considerations about the choice of tertiary education, and that significant changes in the students' reflections were not captured by the factors of the EV-MBC model. This questions the validity of the EV-MBC surveys. Moreover, the quantitative factors from the EV-MBC model did not sufficiently explain students' dynamical educational choice processes where students in parallel considered several different potential educational trajectories. We therefore call for further studies of the EV-MBC model's use in describing longitudinal choice processes and especially in investigating significant changes.

  9. Nonlinear adaptive synchronization rule for identification of a large amount of parameters in dynamical models

    International Nuclear Information System (INIS)

    Ma Huanfei; Lin Wei

    2009-01-01

    The existing adaptive synchronization technique based on the stability theory and invariance principle of dynamical systems, though theoretically proved to be valid for parameters identification in specific models, is always showing slow convergence rate and even failed in practice when the number of parameters becomes large. Here, for parameters update, a novel nonlinear adaptive rule is proposed to accelerate the rate. Its feasibility is validated by analytical arguments as well as by specific parameters identification in the Lotka-Volterra model with multiple species. Two adjustable factors in this rule influence the identification accuracy, which means that a proper choice of these factors leads to an optimal performance of this rule. In addition, a feasible method for avoiding the occurrence of the approximate linear dependence among terms with parameters on the synchronized manifold is also proposed.

  10. Improving navigability on the Kromme River Estuary: A choice ...

    African Journals Online (AJOL)

    2013-03-14

    Mar 14, 2013 ... logit model, random parameters logit model. INTRODUCTION .... tives, is treated by the RUM as a stochastic, utility-maximising choice (Louviere et ..... comparable to the one estimated for a linear regression model. (the ones ...

  11. An economic model of amniocentesis choice.

    Science.gov (United States)

    Fajnzylber, Eduardo; Hotz, V Joseph; Sanders, Seth G

    2010-03-01

    Medical practitioners typically utilize the following protocol when advising pregnant women about testing for the possibility of genetic disorders with their fetus: Pregnant women over the age of 35 should be tested for Down syndrome and other genetic disorders, while for younger women, such tests are discouraged (or not discussed) as the test can cause a pregnancy to miscarry. The logic appears compelling. The rate at which amniocentesis causes a pregnancy to miscarry is constant while the rate of genetic disorder rises substantially over a woman's reproductive years. Hence the potential benefit from testing - being able to terminate a fetus that is known to have a genetic disorder - rises with maternal age. This article argues that this logic is incomplete. While the benefits to testing do rise with age, the costs rise as well. Undergoing an amniocentesis always entails the risk of inducing a miscarriage of a healthy fetus. However, these costs are lower at early ages, because there is a higher probability of being able to replace a miscarried fetus with a healthy birth at a later age. We develop and calibrate a dynamic model of amniocentesis choice to explore this tradeoff. For parameters that characterize realistic age patterns of chromosomal abnormalities, fertility rates and miscarriages following amniocentesis, our model implies a falling, rather than rising, rate of amniocentesis as women approach menopause.

  12. Development of discrete choice model considering internal reference points and their effects in travel mode choice context

    Science.gov (United States)

    Sarif; Kurauchi, Shinya; Yoshii, Toshio

    2017-06-01

    In the conventional travel behavior models such as logit and probit, decision makers are assumed to conduct the absolute evaluations on the attributes of the choice alternatives. On the other hand, many researchers in cognitive psychology and marketing science have been suggesting that the perceptions of attributes are characterized by the benchmark called “reference points” and the relative evaluations based on them are often employed in various choice situations. Therefore, this study developed a travel behavior model based on the mental accounting theory in which the internal reference points are explicitly considered. A questionnaire survey about the shopping trip to the CBD in Matsuyama city was conducted, and then the roles of reference points in travel mode choice contexts were investigated. The result showed that the goodness-of-fit of the developed model was higher than that of the conventional model, indicating that the internal reference points might play the major roles in the choice of travel mode. Also shown was that the respondents seem to utilize various reference points: some tend to adopt the lowest fuel price they have experienced, others employ fare price they feel in perceptions of the travel cost.

  13. A Simulation-Based Dynamic Stochastic Route Choice Model for Evacuation

    Directory of Open Access Journals (Sweden)

    Xing Zhao

    2012-01-01

    Full Text Available This paper establishes a dynamic stochastic route choice model for evacuation to simulate the propagation process of traffic flow and estimate the stochastic route choice under evacuation situations. The model contains a lane-group-based cell transmission model (CTM which sets different traffic capacities for links with different turning movements to flow out in an evacuation situation, an actual impedance model which is to obtain the impedance of each route in time units at each time interval and a stochastic route choice model according to the probit-based stochastic user equilibrium. In this model, vehicles loading at each origin at each time interval are assumed to choose an evacuation route under determinate road network, signal design, and OD demand. As a case study, the proposed model is validated on the network nearby Nanjing Olympic Center after the opening ceremony of the 10th National Games of the People's Republic of China. The traffic volumes and clearing time at five exit points of the evacuation zone are calculated by the model to compare with survey data. The results show that this model can appropriately simulate the dynamic route choice and evolution process of the traffic flow on the network in an evacuation situation.

  14. Airport choice model in multiple airport regions

    Directory of Open Access Journals (Sweden)

    Claudia Muñoz

    2017-02-01

    Full Text Available Purpose: This study aims to analyze travel choices made by air transportation users in multi airport regions because it is a crucial component when planning passenger redistribution policies. The purpose of this study is to find a utility function which makes it possible to know the variables that influence users’ choice of the airports on routes to the main cities in the Colombian territory. Design/methodology/approach: This research generates a Multinomial Logit Model (MNL, which is based on the theory of maximizing utility, and it is based on the data obtained on revealed and stated preference surveys applied to users who reside in the metropolitan area of Aburrá Valley (Colombia. This zone is the only one in the Colombian territory which has two neighboring airports for domestic flights. The airports included in the modeling process were Enrique Olaya Herrera (EOH Airport and José María Córdova (JMC Airport. Several structure models were tested, and the MNL proved to be the most significant revealing the common variables that affect passenger airport choice include the airfare, the price to travel the airport, and the time to get to the airport. Findings and Originality/value: The airport choice model which was calibrated corresponds to a valid powerful tool used to calculate the probability of each analyzed airport of being chosen for domestic flights in the Colombian territory. This is done bearing in mind specific characteristic of each of the attributes contained in the utility function. In addition, these probabilities will be used to calculate future market shares of the two airports considered in this study, and this will be done generating a support tool for airport and airline marketing policies.

  15. Multinational consistency of a discrete choice model in quantifying health states for the extended 5-level EQ-5D

    NARCIS (Netherlands)

    Krabbe, P.F.M.; Devlin, N.J.; Stolk, E.A.; Shah, K.K.; Oppe, M.; Van Hout, B.; Quik, E.H.; Pickard, A.S.; Xie, F.

    2013-01-01

    Objectives: To investigate the feasibility of choice experiments for EQ-5D-5L states using computer-based data collection, and to examine the consistency of the estimated parameters values derived after modeling the stated preference data across countries in a multinational study. Methods: Similar

  16. Maximum profile likelihood estimation of differential equation parameters through model based smoothing state estimates.

    Science.gov (United States)

    Campbell, D A; Chkrebtii, O

    2013-12-01

    Statistical inference for biochemical models often faces a variety of characteristic challenges. In this paper we examine state and parameter estimation for the JAK-STAT intracellular signalling mechanism, which exemplifies the implementation intricacies common in many biochemical inference problems. We introduce an extension to the Generalized Smoothing approach for estimating delay differential equation models, addressing selection of complexity parameters, choice of the basis system, and appropriate optimization strategies. Motivated by the JAK-STAT system, we further extend the generalized smoothing approach to consider a nonlinear observation process with additional unknown parameters, and highlight how the approach handles unobserved states and unevenly spaced observations. The methodology developed is generally applicable to problems of estimation for differential equation models with delays, unobserved states, nonlinear observation processes, and partially observed histories. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

  17. Value-based choice: An integrative, neuroscience-informed model of health goals.

    Science.gov (United States)

    Berkman, Elliot T

    2018-01-01

    Traditional models of health behaviour focus on the roles of cognitive, personality and social-cognitive constructs (e.g. executive function, grit, self-efficacy), and give less attention to the process by which these constructs interact in the moment that a health-relevant choice is made. Health psychology needs a process-focused account of how various factors are integrated to produce the decisions that determine health behaviour. I present an integrative value-based choice model of health behaviour, which characterises the mechanism by which a variety of factors come together to determine behaviour. This model imports knowledge from research on behavioural economics and neuroscience about how choices are made to the study of health behaviour, and uses that knowledge to generate novel predictions about how to change health behaviour. I describe anomalies in value-based choice that can be exploited for health promotion, and review neuroimaging evidence about the involvement of midline dopamine structures in tracking and integrating value-related information during choice. I highlight how this knowledge can bring insights to health psychology using illustrative case of healthy eating. Value-based choice is a viable model for health behaviour and opens new avenues for mechanism-focused intervention.

  18. Behavioural Models for Route Choice of Passengers in Multimodal Public Transport Networks

    DEFF Research Database (Denmark)

    Anderson, Marie Karen

    in the estimation of route choice models of public transport users based upon observed choices. Public transport route choice models have not benefitted from the same technological enhancements as car models because of the necessity (i) to collect additional information concerning lines and transfers, and (ii...... modes, public transport modes, lines, transfers, egress modes) is large. This thesis proposes a doubly stochastic approach for generating alternative routes that are relevant to travellers, since the method allows accounting for both perceived costs of the network elements and heterogeneity......The subject of this thesis is behavioural models for route choice of passengers in multimodal public transport networks. While research in sustainable transport has dedicated much attention toward the determinants of choice between car and sustainable travel options, it has devoted less attention...

  19. Analysis Test of Understanding of Vectors with the Three-Parameter Logistic Model of Item Response Theory and Item Response Curves Technique

    Science.gov (United States)

    Rakkapao, Suttida; Prasitpong, Singha; Arayathanitkul, Kwan

    2016-01-01

    This study investigated the multiple-choice test of understanding of vectors (TUV), by applying item response theory (IRT). The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming…

  20. Discrete choice models with multiplicative error terms

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; Bierlaire, Michel

    2009-01-01

    The conditional indirect utility of many random utility maximization (RUM) discrete choice models is specified as a sum of an index V depending on observables and an independent random term ε. In general, the universe of RUM consistent models is much larger, even fixing some specification of V due...

  1. Nonparametric Identification and Estimation of Finite Mixture Models of Dynamic Discrete Choices

    OpenAIRE

    Hiroyuki Kasahara; Katsumi Shimotsu

    2006-01-01

    In dynamic discrete choice analysis, controlling for unobserved heterogeneity is an important issue, and finite mixture models provide flexible ways to account for unobserved heterogeneity. This paper studies nonparametric identifiability of type probabilities and type-specific component distributions in finite mixture models of dynamic discrete choices. We derive sufficient conditions for nonparametric identification for various finite mixture models of dynamic discrete choices used in appli...

  2. Utility-free heuristic models of two-option choice can mimic predictions of utility-stage models under many conditions

    Directory of Open Access Journals (Sweden)

    Steven T Piantadosi

    2015-04-01

    Full Text Available Economists often model choices as if decision-makers assign each option a scalar value variable, known as utility, and then select the option with the highest utility. It remains unclear whether as-if utility models describe real mental and neural steps in choice. Although choices alone cannot prove the existence of a utility stage in choice, utility transformations are often taken to provide the most parsimonious or psychologically plausible explanation for choice data. Here, we show that it is possible to mathematically transform a large set of common utility-stage two-option choice models (specifically ones in which dimensions are linearly separable into a psychologically plausible heuristic model (specifically, a dimensional prioritization heuristic that has no utility computation stage. We then show that under a range of plausible assumptions, both classes of model predict similar neural responses. These results highlight the difficulties in using neuroeconomic data to infer the existence of a value stage in choice.

  3. A comparison of methods for representing random taste heterogeneity in discrete choice models

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; Hess, Stephane

    2009-01-01

    This paper reports the findings of a systematic study using Monte Carlo experiments and a real dataset aimed at comparing the performance of various ways of specifying random taste heterogeneity in a discrete choice model. Specifically, the analysis compares the performance of two recent advanced...... distributions. Both approaches allow the researcher to increase the number of parameters as desired. The paper provides a range of evidence on the ability of the various approaches to recover various distributions from data. The two advanced approaches are comparable in terms of the likelihoods achieved...

  4. Models of Affective Decision Making: How Do Feelings Predict Choice?

    Science.gov (United States)

    Charpentier, Caroline J; De Neve, Jan-Emmanuel; Li, Xinyi; Roiser, Jonathan P; Sharot, Tali

    2016-06-01

    Intuitively, how you feel about potential outcomes will determine your decisions. Indeed, an implicit assumption in one of the most influential theories in psychology, prospect theory, is that feelings govern choice. Surprisingly, however, very little is known about the rules by which feelings are transformed into decisions. Here, we specified a computational model that used feelings to predict choices. We found that this model predicted choice better than existing value-based models, showing a unique contribution of feelings to decisions, over and above value. Similar to the value function in prospect theory, our feeling function showed diminished sensitivity to outcomes as value increased. However, loss aversion in choice was explained by an asymmetry in how feelings about losses and gains were weighted when making a decision, not by an asymmetry in the feelings themselves. The results provide new insights into how feelings are utilized to reach a decision. © The Author(s) 2016.

  5. Choices and Changes: Eccles’ Expectancy-Value Model and Upper-Secondary School Students’ Longitudinal Reflections about their Choice of a STEM Education

    DEFF Research Database (Denmark)

    Lykkegaard, Eva; Ulriksen, Lars

    2016-01-01

    During the past 30 years, Eccles’ comprehensive social-psychological Expectancy-Value Model of Motivated Behavioural Choices (EV-MBC model) has been proven suitable for studying educational choices related to Science, Technology, Engineering and/or Mathematics (STEM). The reflections of 15 students...... in their last year in upper-secondary school concerning their choice of tertiary education were examined using quantitative EV-MBC surveys and repeated qualitative interviews. This article presents the analyses of three cases in detail. The analytical focus was whether the factors indicated in the EV-MBC model......, and that significant changes in the students’ reflections were not captured by the factors of the EV-MBC model. This questions the validity of the EVMBC surveys. Moreover, the quantitative factors from the EV-MBC model did not sufficiently explain students’ dynamical educational choice processes where students...

  6. SPOTting model parameters using a ready-made Python package

    Science.gov (United States)

    Houska, Tobias; Kraft, Philipp; Breuer, Lutz

    2015-04-01

    The selection and parameterization of reliable process descriptions in ecological modelling is driven by several uncertainties. The procedure is highly dependent on various criteria, like the used algorithm, the likelihood function selected and the definition of the prior parameter distributions. A wide variety of tools have been developed in the past decades to optimize parameters. Some of the tools are closed source. Due to this, the choice for a specific parameter estimation method is sometimes more dependent on its availability than the performance. A toolbox with a large set of methods can support users in deciding about the most suitable method. Further, it enables to test and compare different methods. We developed the SPOT (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of modules, to analyze and optimize parameters of (environmental) models. SPOT comes along with a selected set of algorithms for parameter optimization and uncertainty analyses (Monte Carlo, MC; Latin Hypercube Sampling, LHS; Maximum Likelihood, MLE; Markov Chain Monte Carlo, MCMC; Scuffled Complex Evolution, SCE-UA; Differential Evolution Markov Chain, DE-MCZ), together with several likelihood functions (Bias, (log-) Nash-Sutcliff model efficiency, Correlation Coefficient, Coefficient of Determination, Covariance, (Decomposed-, Relative-, Root-) Mean Squared Error, Mean Absolute Error, Agreement Index) and prior distributions (Binomial, Chi-Square, Dirichlet, Exponential, Laplace, (log-, multivariate-) Normal, Pareto, Poisson, Cauchy, Uniform, Weibull) to sample from. The model-independent structure makes it suitable to analyze a wide range of applications. We apply all algorithms of the SPOT package in three different case studies. Firstly, we investigate the response of the Rosenbrock function, where the MLE algorithm shows its strengths. Secondly, we study the Griewank function, which has a challenging response surface for

  7. Rational Choice of the Investment Project Using Interval Estimates of the Initial Parameters

    Directory of Open Access Journals (Sweden)

    Kotsyuba Oleksiy S.

    2016-11-01

    Full Text Available The article is dedicated to the development of instruments to support decision-making on the problem of choosing the best investment project in a situation when initial quantitative parameters of the considered investment alternatives are described by interval estimates. In terms of managing the risk caused by interval uncertainty of the initial data, the study is limited to the component (aspect of risk measure as a degree of possibility of discrepancy between the resulting economic indicator (criterion and its normative level (the norm. An important hypothesis used as a basis for the proposed in the work formalization of the problem under consideration is the presence – for some or all of the projects from which the choice is made – of risk of poor rate of return in terms of net present (current value. Based upon relevant developments within the framework of the fuzzy-set methodology and interval analysis, there formulated a model for choosing an optimal investment project from the set of alternative options for the interval formulation of the problem. In this case it is assumed that indicators of economic attractiveness (performance of the compared directions of real investment are described either by interval estimates or possibility distribution functions. With the help of the estimated conditional example there implemented an approbation of the proposed model, which demonstrated its practical viability.

  8. Empirical analyses of a choice model that captures ordering among attribute values

    DEFF Research Database (Denmark)

    Mabit, Stefan Lindhard

    2017-01-01

    an alternative additionally because it has the highest price. In this paper, we specify a discrete choice model that takes into account the ordering of attribute values across alternatives. This model is used to investigate the effect of attribute value ordering in three case studies related to alternative-fuel...... vehicles, mode choice, and route choice. In our application to choices among alternative-fuel vehicles, we see that especially the price coefficient is sensitive to changes in ordering. The ordering effect is also found in the applications to mode and route choice data where both travel time and cost...

  9. On the role of modeling parameters in IMRT plan optimization

    International Nuclear Information System (INIS)

    Krause, Michael; Scherrer, Alexander; Thieke, Christian

    2008-01-01

    The formulation of optimization problems in intensity-modulated radiotherapy (IMRT) planning comprises the choice of various values such as function-specific parameters or constraint bounds. In current inverse planning programs that yield a single treatment plan for each optimization, it is often unclear how strongly these modeling parameters affect the resulting plan. This work investigates the mathematical concepts of elasticity and sensitivity to deal with this problem. An artificial planning case with a horse-shoe formed target with different opening angles surrounding a circular risk structure is studied. As evaluation functions the generalized equivalent uniform dose (EUD) and the average underdosage below and average overdosage beyond certain dose thresholds are used. A single IMRT plan is calculated for an exemplary parameter configuration. The elasticity and sensitivity of each parameter are then calculated without re-optimization, and the results are numerically verified. The results show the following. (1) elasticity can quantify the influence of a modeling parameter on the optimization result in terms of how strongly the objective function value varies under modifications of the parameter value. It also can describe how strongly the geometry of the involved planning structures affects the optimization result. (2) Based on the current parameter settings and corresponding treatment plan, sensitivity analysis can predict the optimization result for modified parameter values without re-optimization, and it can estimate the value intervals in which such predictions are valid. In conclusion, elasticity and sensitivity can provide helpful tools in inverse IMRT planning to identify the most critical parameters of an individual planning problem and to modify their values in an appropriate way

  10. Recent evolution of italian households’ equity portfolio choices: an empirical investigation

    Directory of Open Access Journals (Sweden)

    Attilio Gardini

    2013-05-01

    Full Text Available We study Italian households’ portfolio choices, with a special focus on equity investments, by analysing jointly time series and cross-sectional portfolio data. We investigate the temporal evolution of the actual composition of Italian households’ investments in order to explain their portfolio choices and to detect possible determinants of the observed disequilibria phenomena. Moreover, we model the stock market participation choice by using probit regression techniques and we test for parameter stability over time. Instability of participation parameters and a peculiar evolution of Italian households’ portfolios pointed out by our concurrent analysis of cross-sectional and time series data seem to confirm the distance of Italian households’ financial decisions from the rational choice predicted by the Markowitz model. In particular, we find that the housing market bubbles interact strongly with the stock market and financial institutions seem to be unable to advise investors suggesting optimal portfolio choices. The deep reason behind these facts may be the bounded education of investors, in particular the low financial literacy of Italian households.

  11. Patient choice modelling: how do patients choose their hospitals?

    Science.gov (United States)

    Smith, Honora; Currie, Christine; Chaiwuttisak, Pornpimol; Kyprianou, Andreas

    2018-06-01

    As an aid to predicting future hospital admissions, we compare use of the Multinomial Logit and the Utility Maximising Nested Logit models to describe how patients choose their hospitals. The models are fitted to real data from Derbyshire, United Kingdom, which lists the postcodes of more than 200,000 admissions to six different local hospitals. Both elective and emergency admissions are analysed for this mixed urban/rural area. For characteristics that may affect a patient's choice of hospital, we consider the distance of the patient from the hospital, the number of beds at the hospital and the number of car parking spaces available at the hospital, as well as several statistics publicly available on National Health Service (NHS) websites: an average waiting time, the patient survey score for ward cleanliness, the patient safety score and the inpatient survey score for overall care. The Multinomial Logit model is successfully fitted to the data. Results obtained with the Utility Maximising Nested Logit model show that nesting according to city or town may be invalid for these data; in other words, the choice of hospital does not appear to be preceded by choice of city. In all of the analysis carried out, distance appears to be one of the main influences on a patient's choice of hospital rather than statistics available on the Internet.

  12. Incorporating Latent Variables into Discrete Choice Models - A Simultaneous Estimation Approach Using SEM Software

    Directory of Open Access Journals (Sweden)

    Dirk Temme

    2008-12-01

    Full Text Available Integrated choice and latent variable (ICLV models represent a promising new class of models which merge classic choice models with the structural equation approach (SEM for latent variables. Despite their conceptual appeal, applications of ICLV models in marketing remain rare. We extend previous ICLV applications by first estimating a multinomial choice model and, second, by estimating hierarchical relations between latent variables. An empirical study on travel mode choice clearly demonstrates the value of ICLV models to enhance the understanding of choice processes. In addition to the usually studied directly observable variables such as travel time, we show how abstract motivations such as power and hedonism as well as attitudes such as a desire for flexibility impact on travel mode choice. Furthermore, we show that it is possible to estimate such a complex ICLV model with the widely available structural equation modeling package Mplus. This finding is likely to encourage more widespread application of this appealing model class in the marketing field.

  13. Modeling route choice criteria from home to major streets: A discrete choice approach

    Directory of Open Access Journals (Sweden)

    Jose Osiris Vidana-Bencomo

    2018-03-01

    Full Text Available A discrete choice model that consists of three sub-models was developed to investigates the route choice criteria of drivers who travel from their homes in the morning to the access point along the major streets that bound the Traffic Analysis Zones (TAZs. The first sub-model is a Nested Logit Model (NLM that estimates the probability of a driver has or has no multiple routes, and if the driver has multiple routes, the route selection criteria are based on the access point’s intersection control type or other factors. The second sub-model is a Mixed Logit (MXL model. It estimates the probabilities of the type of intersection control preferred by a driver. The third sub-model is a NLM that estimates the probabilities of a driver selecting his/her route for its shortest travel time or to avoid pedestrian, and if the aim is to take the fastest route, the decision criteria is based on the shortest distance or minimum stops and turns. Data gathered in a questionnaire survey were used to estimate the sub-models. The attributes of the utility functions of the sub-models are the driver’s demographic and trip characteristics. The model provides a means for transportation planners to distribute the total number of home-based trips generated within a TAZ to the access points along the major streets that bound the TAZ.

  14. Understanding Predisposition in College Choice: Toward an Integrated Model of College Choice and Theory of Reasoned Action

    Science.gov (United States)

    Pitre, Paul E.; Johnson, Todd E.; Pitre, Charisse Cowan

    2006-01-01

    This article seeks to improve traditional models of college choice that draw from recruitment and enrollment management paradigms. In adopting a consumer approach to college choice, this article seeks to build upon consumer-related research, which centers on behavior and reasoning. More specifically, this article seeks to move inquiry beyond the…

  15. Assessing the accuracy of subject-specific, muscle-model parameters determined by optimizing to match isometric strength.

    Science.gov (United States)

    DeSmitt, Holly J; Domire, Zachary J

    2016-12-01

    Biomechanical models are sensitive to the choice of model parameters. Therefore, determination of accurate subject specific model parameters is important. One approach to generate these parameters is to optimize the values such that the model output will match experimentally measured strength curves. This approach is attractive as it is inexpensive and should provide an excellent match to experimentally measured strength. However, given the problem of muscle redundancy, it is not clear that this approach generates accurate individual muscle forces. The purpose of this investigation is to evaluate this approach using simulated data to enable a direct comparison. It is hypothesized that the optimization approach will be able to recreate accurate muscle model parameters when information from measurable parameters is given. A model of isometric knee extension was developed to simulate a strength curve across a range of knee angles. In order to realistically recreate experimentally measured strength, random noise was added to the modeled strength. Parameters were solved for using a genetic search algorithm. When noise was added to the measurements the strength curve was reasonably recreated. However, the individual muscle model parameters and force curves were far less accurate. Based upon this examination, it is clear that very different sets of model parameters can recreate similar strength curves. Therefore, experimental variation in strength measurements has a significant influence on the results. Given the difficulty in accurately recreating individual muscle parameters, it may be more appropriate to perform simulations with lumped actuators representing similar muscles.

  16. Utility-free heuristic models of two-option choice can mimic predictions of utility-stage models under many conditions

    Science.gov (United States)

    Piantadosi, Steven T.; Hayden, Benjamin Y.

    2015-01-01

    Economists often model choices as if decision-makers assign each option a scalar value variable, known as utility, and then select the option with the highest utility. It remains unclear whether as-if utility models describe real mental and neural steps in choice. Although choices alone cannot prove the existence of a utility stage, utility transformations are often taken to provide the most parsimonious or psychologically plausible explanation for choice data. Here, we show that it is possible to mathematically transform a large set of common utility-stage two-option choice models (specifically ones in which dimensions are can be decomposed into additive functions) into a heuristic model (specifically, a dimensional prioritization heuristic) that has no utility computation stage. We then show that under a range of plausible assumptions, both classes of model predict similar neural responses. These results highlight the difficulties in using neuroeconomic data to infer the existence of a value stage in choice. PMID:25914613

  17. Impact of modeling Choices on Inventory and In-Cask Criticality Calculations for Forsmark 3 BWR Spent Fuel

    International Nuclear Information System (INIS)

    Martinez-Gonzalez, Jesus S.; Ade, Brian J.; Bowman, Stephen M.; Gauld, Ian C.; Ilas, Germina; Marshall, William BJ J.

    2015-01-01

    Simulation of boiling water reactor (BWR) fuel depletion poses a challenge for nuclide inventory validation and nuclear criticality safety analyses. This challenge is due to the complex operating conditions and assembly design heterogeneities that characterize these nuclear systems. Fuel depletion simulations and in-cask criticality calculations are affected by (1) completeness of design information, (2) variability of operating conditions needed for modeling purposes, and (3) possible modeling choices. These effects must be identified, quantified, and ranked according to their significance. This paper presents an investigation of BWR fuel depletion using a complete set of actual design specifications and detailed operational data available for five operating cycles of the Swedish BWR Forsmark 3 reactor. The data includes detailed axial profiles of power, burnup, and void fraction in a very fine temporal mesh for a GE14 (10x10) fuel assembly. The specifications of this case can be used to assess the impacts of different modeling choices on inventory prediction and in-cask criticality, specifically regarding the key parameters that drive inventory and reactivity throughout fuel burnup. This study focused on the effects of the fidelity with which power history and void fraction distributions are modeled. The corresponding sensitivity of the reactivity in storage configurations is assessed, and the impacts of modeling choices on decay heat and inventory are addressed.

  18. Study on Identification of Material Model Parameters from Compact Tension Test on Concrete Specimens

    Science.gov (United States)

    Hokes, Filip; Kral, Petr; Husek, Martin; Kala, Jiri

    2017-10-01

    Identification of a concrete material model parameters using optimization is based on a calculation of a difference between experimentally measured and numerically obtained data. Measure of the difference can be formulated via root mean squared error that is often used for determination of accuracy of a mathematical model in the field of meteorology or demography. The quality of the identified parameters is, however, determined not only by right choice of an objective function but also by the source experimental data. One of the possible way is to use load-displacement curves from three-point bending tests that were performed on concrete specimens. This option shows the significance of modulus of elasticity, tensile strength and specific fracture energy. Another possible option is to use experimental data from compact tension test. It is clear that the response in the second type of test is also dependent on the above mentioned material parameters. The question is whether the parameters identified within three-point bending test and within compact tension test will reach the same values. The presented article brings the numerical study of inverse identification of material model parameters from experimental data measured during compact tension tests. The article also presents utilization of the modified sensitivity analysis that calculates the sensitivity of the material model parameters for different parts of loading curve. The main goal of the article is to describe the process of inverse identification of parameters for plasticity-based material model of concrete and prepare data for future comparison with identified values of the material model parameters from different type of fracture tests.

  19. Testing process predictions of models of risky choice: a quantitative model comparison approach

    Science.gov (United States)

    Pachur, Thorsten; Hertwig, Ralph; Gigerenzer, Gerd; Brandstätter, Eduard

    2013-01-01

    This article presents a quantitative model comparison contrasting the process predictions of two prominent views on risky choice. One view assumes a trade-off between probabilities and outcomes (or non-linear functions thereof) and the separate evaluation of risky options (expectation models). Another view assumes that risky choice is based on comparative evaluation, limited search, aspiration levels, and the forgoing of trade-offs (heuristic models). We derived quantitative process predictions for a generic expectation model and for a specific heuristic model, namely the priority heuristic (Brandstätter et al., 2006), and tested them in two experiments. The focus was on two key features of the cognitive process: acquisition frequencies (i.e., how frequently individual reasons are looked up) and direction of search (i.e., gamble-wise vs. reason-wise). In Experiment 1, the priority heuristic predicted direction of search better than the expectation model (although neither model predicted the acquisition process perfectly); acquisition frequencies, however, were inconsistent with both models. Additional analyses revealed that these frequencies were primarily a function of what Rubinstein (1988) called “similarity.” In Experiment 2, the quantitative model comparison approach showed that people seemed to rely more on the priority heuristic in difficult problems, but to make more trade-offs in easy problems. This finding suggests that risky choice may be based on a mental toolbox of strategies. PMID:24151472

  20. Testing Process Predictions of Models of Risky Choice: A Quantitative Model Comparison Approach

    Directory of Open Access Journals (Sweden)

    Thorsten ePachur

    2013-09-01

    Full Text Available This article presents a quantitative model comparison contrasting the process predictions of two prominent views on risky choice. One view assumes a trade-off between probabilities and outcomes (or nonlinear functions thereof and the separate evaluation of risky options (expectation models. Another view assumes that risky choice is based on comparative evaluation, limited search, aspiration levels, and the forgoing of trade-offs (heuristic models. We derived quantitative process predictions for a generic expectation model and for a specific heuristic model, namely the priority heuristic (Brandstätter, Gigerenzer, & Hertwig, 2006, and tested them in two experiments. The focus was on two key features of the cognitive process: acquisition frequencies (i.e., how frequently individual reasons are looked up and direction of search (i.e., gamble-wise vs. reason-wise. In Experiment 1, the priority heuristic predicted direction of search better than the expectation model (although neither model predicted the acquisition process perfectly; acquisition frequencies, however, were inconsistent with both models. Additional analyses revealed that these frequencies were primarily a function of what Rubinstein (1988 called similarity. In Experiment 2, the quantitative model comparison approach showed that people seemed to rely more on the priority heuristic in difficult problems, but to make more trade-offs in easy problems. This finding suggests that risky choice may be based on a mental toolbox of strategies.

  1. A Conditional Curie-Weiss Model for Stylized Multi-group Binary Choice with Social Interaction

    Science.gov (United States)

    Opoku, Alex Akwasi; Edusei, Kwame Owusu; Ansah, Richard Kwame

    2018-04-01

    This paper proposes a conditional Curie-Weiss model as a model for decision making in a stylized society made up of binary decision makers that face a particular dichotomous choice between two options. Following Brock and Durlauf (Discrete choice with social interaction I: theory, 1955), we set-up both socio-economic and statistical mechanical models for the choice problem. We point out when both the socio-economic and statistical mechanical models give rise to the same self-consistent equilibrium mean choice level(s). Phase diagram of the associated statistical mechanical model and its socio-economic implications are discussed.

  2. Choices and Changes: Eccles' Expectancy-Value Model and Upper-Secondary School Students' Longitudinal Reflections about Their Choice of a STEM Education

    Science.gov (United States)

    Lykkegaard, Eva; Ulriksen, Lars

    2016-01-01

    During the past 30 years, Eccles' comprehensive social-psychological Expectancy-Value Model of Motivated Behavioural Choices (EV-MBC model) has been proven suitable for studying educational choices related to Science, Technology, Engineering and/or Mathematics (STEM). The reflections of 15 students in their last year in upper-secondary school…

  3. Decisions with Endogenous Preference Parameters (Replaced by CentER DP 2010-142)

    NARCIS (Netherlands)

    Dalton, P.S.; Ghosal, S.

    2010-01-01

    We relate the normative implications of a model of decision-making with endogenous preference parameters to choice theoretic models (Bernheim and Rangel 2007, 2009; Rubinstein and Salant, 2008) in which observed choices are determined by frames or ancillary conditions.

  4. MODELLING CONSUMER CHOICE IN THE MARKET SWITCHBOARD EQUIPMENT USING IBM SPSS STATISTICS

    Directory of Open Access Journals (Sweden)

    Sergey V. Mkhitaryan

    2014-01-01

    Full Text Available Modelling consumer choice in the marketswitch equipment will allow manufacturing enterprises to improve the efficiencyof design and marketing activities byreducing the financial and human losses associated with pre-treatment orders. Todevelop a model of consumer choice canbe used logistic regression.

  5. Calibration of sea ice dynamic parameters in an ocean-sea ice model using an ensemble Kalman filter

    Science.gov (United States)

    Massonnet, F.; Goosse, H.; Fichefet, T.; Counillon, F.

    2014-07-01

    The choice of parameter values is crucial in the course of sea ice model development, since parameters largely affect the modeled mean sea ice state. Manual tuning of parameters will soon become impractical, as sea ice models will likely include more parameters to calibrate, leading to an exponential increase of the number of possible combinations to test. Objective and automatic methods for parameter calibration are thus progressively called on to replace the traditional heuristic, "trial-and-error" recipes. Here a method for calibration of parameters based on the ensemble Kalman filter is implemented, tested and validated in the ocean-sea ice model NEMO-LIM3. Three dynamic parameters are calibrated: the ice strength parameter P*, the ocean-sea ice drag parameter Cw, and the atmosphere-sea ice drag parameter Ca. In twin, perfect-model experiments, the default parameter values are retrieved within 1 year of simulation. Using 2007-2012 real sea ice drift data, the calibration of the ice strength parameter P* and the oceanic drag parameter Cw improves clearly the Arctic sea ice drift properties. It is found that the estimation of the atmospheric drag Ca is not necessary if P* and Cw are already estimated. The large reduction in the sea ice speed bias with calibrated parameters comes with a slight overestimation of the winter sea ice areal export through Fram Strait and a slight improvement in the sea ice thickness distribution. Overall, the estimation of parameters with the ensemble Kalman filter represents an encouraging alternative to manual tuning for ocean-sea ice models.

  6. Parameter space of general gauge mediation

    International Nuclear Information System (INIS)

    Rajaraman, Arvind; Shirman, Yuri; Smidt, Joseph; Yu, Felix

    2009-01-01

    We study a subspace of General Gauge Mediation (GGM) models which generalize models of gauge mediation. We find superpartner spectra that are markedly different from those of typical gauge and gaugino mediation scenarios. While typical gauge mediation predictions of either a neutralino or stau next-to-lightest supersymmetric particle (NLSP) are easily reproducible with the GGM parameters, chargino and sneutrino NLSPs are generic for many reasonable choices of GGM parameters.

  7. On selecting a prior for the precision parameter of Dirichlet process mixture models

    Science.gov (United States)

    Dorazio, R.M.

    2009-01-01

    In hierarchical mixture models the Dirichlet process is used to specify latent patterns of heterogeneity, particularly when the distribution of latent parameters is thought to be clustered (multimodal). The parameters of a Dirichlet process include a precision parameter ?? and a base probability measure G0. In problems where ?? is unknown and must be estimated, inferences about the level of clustering can be sensitive to the choice of prior assumed for ??. In this paper an approach is developed for computing a prior for the precision parameter ?? that can be used in the presence or absence of prior information about the level of clustering. This approach is illustrated in an analysis of counts of stream fishes. The results of this fully Bayesian analysis are compared with an empirical Bayes analysis of the same data and with a Bayesian analysis based on an alternative commonly used prior.

  8. Simultaneous fitting of statistical-model parameters to symmetric and asymmetric fission cross sections

    International Nuclear Information System (INIS)

    Mancusi, D; Charity, R J; Cugnon, J

    2013-01-01

    The de-excitation of compound nuclei has been successfully described for several decades by means of statistical models. However, accurate predictions require some fine-tuning of the model parameters. This task can be simplified by studying several entrance channels, which populate different regions of the parameter space of the compound nucleus. Fusion reactions play an important role in this strategy because they minimise the uncertainty on the entrance channel by fixing mass, charge and excitation energy of the compound nucleus. If incomplete fusion is negligible, the only uncertainty on the compound nucleus comes from the spin distribution. However, some de-excitation channels, such as fission, are quite sensitive to spin. Other entrance channels can then be used to discriminate between equivalent parameter sets. The focus of this work is on fission and intermediate-mass-fragment emission cross sections of compound nuclei with 70 70 ≲ A ≲ 240. 240. The statistical de-excitation model is GEMINI++. The choice of the observables is natural in the framework of GEMINI++, which describes fragment emission using a fissionlike formalism. Equivalent parameter sets for fusion reactions can be resolved using the spallation entrance channel. This promising strategy can lead to the identification of a minimal set of physical ingredients necessary for a unified quantitative description of nuclear de-excitation.

  9. A Conceptual Model of Leisure-Time Choice Behavior.

    Science.gov (United States)

    Bergier, Michel J.

    1981-01-01

    Methods of studying the gap between predisposition and actual behavior of consumers of spectator sports is discussed. A model is drawn from the areas of behavioral sciences, consumer behavior, and leisure research. The model is constructed around the premise that choice is primarily a function of personal, product, and environmental factors. (JN)

  10. Significance of settling model structures and parameter subsets in modelling WWTPs under wet-weather flow and filamentous bulking conditions.

    Science.gov (United States)

    Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen; Plósz, Benedek Gy

    2014-10-15

    Current research focuses on predicting and mitigating the impacts of high hydraulic loadings on centralized wastewater treatment plants (WWTPs) under wet-weather conditions. The maximum permissible inflow to WWTPs depends not only on the settleability of activated sludge in secondary settling tanks (SSTs) but also on the hydraulic behaviour of SSTs. The present study investigates the impacts of ideal and non-ideal flow (dry and wet weather) and settling (good settling and bulking) boundary conditions on the sensitivity of WWTP model outputs to uncertainties intrinsic to the one-dimensional (1-D) SST model structures and parameters. We identify the critical sources of uncertainty in WWTP models through global sensitivity analysis (GSA) using the Benchmark simulation model No. 1 in combination with first- and second-order 1-D SST models. The results obtained illustrate that the contribution of settling parameters to the total variance of the key WWTP process outputs significantly depends on the influent flow and settling conditions. The magnitude of the impact is found to vary, depending on which type of 1-D SST model is used. Therefore, we identify and recommend potential parameter subsets for WWTP model calibration, and propose optimal choice of 1-D SST models under different flow and settling boundary conditions. Additionally, the hydraulic parameters in the second-order SST model are found significant under dynamic wet-weather flow conditions. These results highlight the importance of developing a more mechanistic based flow-dependent hydraulic sub-model in second-order 1-D SST models in the future. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Classical algorithms for automated parameter-search methods in compartmental neural models - A critical survey based on simulations using neuron

    International Nuclear Information System (INIS)

    Mutihac, R.; Mutihac, R.C.; Cicuttin, A.

    2001-09-01

    Parameter-search methods are problem-sensitive. All methods depend on some meta-parameters of their own, which must be determined experimentally in advance. A better choice of these intrinsic parameters for a certain parameter-search method may improve its performance. Moreover, there are various implementations of the same method, which may also affect its performance. The choice of the matching (error) function has a great impact on the search process in terms of finding the optimal parameter set and minimizing the computational cost. An initial assessment of the matching function ability to distinguish between good and bad models is recommended, before launching exhaustive computations. However, different runs of a parameter search method may result in the same optimal parameter set or in different parameter sets (the model is insufficiently constrained to accurately characterize the real system). Robustness of the parameter set is expressed by the extent to which small perturbations in the parameter values are not affecting the best solution. A parameter set that is not robust is unlikely to be physiologically relevant. Robustness can also be defined as the stability of the optimal parameter set to small variations of the inputs. When trying to estimate things like the minimum, or the least-squares optimal parameters of a nonlinear system, the existence of multiple local minima can cause problems with the determination of the global optimum. Techniques such as Newton's method, the Simplex method and Least-squares Linear Taylor Differential correction technique can be useful provided that one is lucky enough to start sufficiently close to the global minimum. All these methods suffer from the inability to distinguish a local minimum from a global one because they follow the local gradients towards the minimum, even if some methods are resetting the search direction when it is likely to get stuck in presumably a local minimum. Deterministic methods based on

  12. The choice of forest site for recreation

    DEFF Research Database (Denmark)

    Agimass, Fitalew; Lundhede, Thomas; Panduro, Toke Emil

    2018-01-01

    logit as well as a random parameter logit model. The variables that are found to affect the choice of forest site to a visit for recreation include: forest area, tree species composition, forest density, availability of historical sites, terrain difference, state ownership, and distance. Regarding......In this paper, we investigate the factors that can influence the site choice of forest recreation. Relevant attributes are identified by using spatial data analysis from a questionnaire asking people to indicate their most recent forest visits by pinpointing on a map. The main objectives...

  13. Empirical study of travel mode forecasting improvement for the combined revealed preference/stated preference data–based discrete choice model

    Directory of Open Access Journals (Sweden)

    Yanfu Qiao

    2016-01-01

    Full Text Available The combined revealed preference/stated preference data–based discrete choice model has provided the actual choice-making restraints as well as reduced the prediction errors. But the random error variance of alternatives belonging to different data would impact its universality. In this article, we studied the traffic corridor between Chengdu and Longquan with the revealed preference/stated preference joint model, and the single stated preference data model separately predicted the choice probability of each mode. We found the revealed preference/stated preference joint model is universal only when there is a significant difference between the random error terms in different data. The single stated preference data would amplify the travelers’ preference and cause prediction error. We proposed a universal way that uses revealed preference data to modify the single stated preference data parameter estimation results to achieve the composite utility and reduce the prediction error. And the result suggests that prediction results are more reasonable based on the composite utility than the results based on the single stated preference data, especially forecasting the mode share of bus. The future metro line will be the main travel mode in this corridor, and 45% of passenger flow will transfer to the metro.

  14. Parameter estimation techniques and uncertainty in ground water flow model predictions

    International Nuclear Information System (INIS)

    Zimmerman, D.A.; Davis, P.A.

    1990-01-01

    Quantification of uncertainty in predictions of nuclear waste repository performance is a requirement of Nuclear Regulatory Commission regulations governing the licensing of proposed geologic repositories for high-level radioactive waste disposal. One of the major uncertainties in these predictions is in estimating the ground-water travel time of radionuclides migrating from the repository to the accessible environment. The cause of much of this uncertainty has been attributed to a lack of knowledge about the hydrogeologic properties that control the movement of radionuclides through the aquifers. A major reason for this lack of knowledge is the paucity of data that is typically available for characterizing complex ground-water flow systems. Because of this, considerable effort has been put into developing parameter estimation techniques that infer property values in regions where no measurements exist. Currently, no single technique has been shown to be superior or even consistently conservative with respect to predictions of ground-water travel time. This work was undertaken to compare a number of parameter estimation techniques and to evaluate how differences in the parameter estimates and the estimation errors are reflected in the behavior of the flow model predictions. That is, we wished to determine to what degree uncertainties in flow model predictions may be affected simply by the choice of parameter estimation technique used. 3 refs., 2 figs

  15. Model for understanding consumer textural food choice.

    Science.gov (United States)

    Jeltema, Melissa; Beckley, Jacqueline; Vahalik, Jennifer

    2015-05-01

    The current paradigm for developing products that will match the marketing messaging is flawed because the drivers of product choice and satisfaction based on texture are misunderstood. Qualitative research across 10 years has led to the thesis explored in this research that individuals have a preferred way to manipulate food in their mouths (i.e., mouth behavior) and that this behavior is a major driver of food choice, satisfaction, and the desire to repurchase. Texture, which is currently thought to be a major driver of product choice, is a secondary factor, and is important only in that it supports the primary driver-mouth behavior. A model for mouth behavior is proposed and the qualitative research supporting the identification of different mouth behaviors is presented. The development of a trademarked typing tool for characterizing mouth behavior is described along with quantitative substantiation of the tool's ability to group individuals by mouth behavior. The use of these four groups to understand textural preferences and the implications for a variety of areas including product design and weight management are explored.

  16. Test policy optimization for a complex system: an application for the differential model for equivalent parameters (DMEP)

    International Nuclear Information System (INIS)

    Vasseur, D.; Eid, M.

    1996-01-01

    One of EDF's current priorities is the optimisation of the preventive maintenance in all French nuclear power stations. This optimisation involves a rationalization of the choice of equipments to be maintained and maintenance tasks to be carried out, as well as a judicious choice of intervals between these tasks. This work is being carried out in cooperation between EDF and the CEA (Atomic Energy Commission), and suggests a procedure to provide assistance in optimising intervals between maintenance tasks respecting a global unavailability target. This work is based on the differential model for equivalent parameters (DMEP). (authors)

  17. Modeling metabolic networks in C. glutamicum: a comparison of rate laws in combination with various parameter optimization strategies

    Directory of Open Access Journals (Sweden)

    Oldiges Marco

    2009-01-01

    Full Text Available Abstract Background To understand the dynamic behavior of cellular systems, mathematical modeling is often necessary and comprises three steps: (1 experimental measurement of participating molecules, (2 assignment of rate laws to each reaction, and (3 parameter calibration with respect to the measurements. In each of these steps the modeler is confronted with a plethora of alternative approaches, e. g., the selection of approximative rate laws in step two as specific equations are often unknown, or the choice of an estimation procedure with its specific settings in step three. This overall process with its numerous choices and the mutual influence between them makes it hard to single out the best modeling approach for a given problem. Results We investigate the modeling process using multiple kinetic equations together with various parameter optimization methods for a well-characterized example network, the biosynthesis of valine and leucine in C. glutamicum. For this purpose, we derive seven dynamic models based on generalized mass action, Michaelis-Menten and convenience kinetics as well as the stochastic Langevin equation. In addition, we introduce two modeling approaches for feedback inhibition to the mass action kinetics. The parameters of each model are estimated using eight optimization strategies. To determine the most promising modeling approaches together with the best optimization algorithms, we carry out a two-step benchmark: (1 coarse-grained comparison of the algorithms on all models and (2 fine-grained tuning of the best optimization algorithms and models. To analyze the space of the best parameters found for each model, we apply clustering, variance, and correlation analysis. Conclusion A mixed model based on the convenience rate law and the Michaelis-Menten equation, in which all reactions are assumed to be reversible, is the most suitable deterministic modeling approach followed by a reversible generalized mass action kinetics

  18. Institutional influences on business model choice by new ventures in the microgenerated energy industry

    Energy Technology Data Exchange (ETDEWEB)

    Provance, Mike, E-mail: mprovanc@odu.edu [Old Dominion University, Norfolk, VA 23529 (United States); Donnelly, Richard G.; Carayannis, Elias G. [George Washington University, Washington, DC 20052 (United States)

    2011-09-15

    Business model choice plays an important source of competitive advantage for new ventures in the microgeneration sector. Yet, existing literature focuses on strategic management of internal resources as the constraints in this choice process. In the energy sector, external factors may be at least as influential in shaping these business models. This paper examines the roles of politico-institutional and socio-institutional dynamics in the choice of business models for microgeneration ventures. Business models have traditionally been viewed as constructions of the internal values, strategies, and resources of organizations. But, this perspective overlooks the role that external forces have on these models, particularly in more highly institutionalized contexts like microgeneration. When these factors are introduced into the existing framework for business model choice, the business model based less on firm decision-making and more about variables that exist within national innovation systems and political structure, local socio-technological conditions, and cognitive abilities of the entrepreneur and corresponding stakeholders. - Highlights: > This work provides theoretical foundation for variation in microgeneration business models. > Explores institutional influences on strategic view of business model choice. > Compares the nature of microgeneration across geo-political contexts.

  19. Institutional influences on business model choice by new ventures in the microgenerated energy industry

    International Nuclear Information System (INIS)

    Provance, Mike; Donnelly, Richard G.; Carayannis, Elias G.

    2011-01-01

    Business model choice plays an important source of competitive advantage for new ventures in the microgeneration sector. Yet, existing literature focuses on strategic management of internal resources as the constraints in this choice process. In the energy sector, external factors may be at least as influential in shaping these business models. This paper examines the roles of politico-institutional and socio-institutional dynamics in the choice of business models for microgeneration ventures. Business models have traditionally been viewed as constructions of the internal values, strategies, and resources of organizations. But, this perspective overlooks the role that external forces have on these models, particularly in more highly institutionalized contexts like microgeneration. When these factors are introduced into the existing framework for business model choice, the business model based less on firm decision-making and more about variables that exist within national innovation systems and political structure, local socio-technological conditions, and cognitive abilities of the entrepreneur and corresponding stakeholders. - Highlights: → This work provides theoretical foundation for variation in microgeneration business models. → Explores institutional influences on strategic view of business model choice. → Compares the nature of microgeneration across geo-political contexts.

  20. Simple model for multiple-choice collective decision making.

    Science.gov (United States)

    Lee, Ching Hua; Lucas, Andrew

    2014-11-01

    We describe a simple model of heterogeneous, interacting agents making decisions between n≥2 discrete choices. For a special class of interactions, our model is the mean field description of random field Potts-like models and is effectively solved by finding the extrema of the average energy E per agent. In these cases, by studying the propagation of decision changes via avalanches, we argue that macroscopic dynamics is well captured by a gradient flow along E. We focus on the permutation symmetric case, where all n choices are (on average) the same, and spontaneous symmetry breaking (SSB) arises purely from cooperative social interactions. As examples, we show that bimodal heterogeneity naturally provides a mechanism for the spontaneous formation of hierarchies between decisions and that SSB is a preferred instability to discontinuous phase transitions between two symmetric points. Beyond the mean field limit, exponentially many stable equilibria emerge when we place this model on a graph of finite mean degree. We conclude with speculation on decision making with persistent collective oscillations. Throughout the paper, we emphasize analogies between methods of solution to our model and common intuition from diverse areas of physics, including statistical physics and electromagnetism.

  1. A discrete choice approach to define individual parking choice behaviour for the Parkagent model

    NARCIS (Netherlands)

    Khaliq, A.; Van Der Waerden, P.J.H.J.; Janssens, D.

    2017-01-01

    PARKAGENT is an agent based model for simulating parking search in the city. In PARKAGENT, the agents choose a parking spot based on the expected number of free parking spaces, distance to destination and length of parking space. For a true representation of underlying parking choice behaviour of

  2. Pairwise Choice Markov Chains

    OpenAIRE

    Ragain, Stephen; Ugander, Johan

    2016-01-01

    As datasets capturing human choices grow in richness and scale---particularly in online domains---there is an increasing need for choice models that escape traditional choice-theoretic axioms such as regularity, stochastic transitivity, and Luce's choice axiom. In this work we introduce the Pairwise Choice Markov Chain (PCMC) model of discrete choice, an inferentially tractable model that does not assume any of the above axioms while still satisfying the foundational axiom of uniform expansio...

  3. Understanding the formation and influence of attitudes in patients' treatment choices for lower back pain: Testing the benefits of a hybrid choice model approach

    DEFF Research Database (Denmark)

    Kløjgaard, Mirja Elisabeth; Hess, S.

    2014-01-01

    A growing number of studies across different fields are making use of a new class of choice models, labelled variably as hybrid model structures or integrated choice and latent variable models, and incorporating the role of attitudes in decision making. To date, this technique has not been used...... in spring/summer 2012. We show how the hybrid model structure is able to make a link between attitudinal questions and treatment choices, and also explains variation of these attitudes across key socio-demographic groups. However, we also show how, in this case, only a small share of the overall...

  4. Bayesian Poisson hierarchical models for crash data analysis: Investigating the impact of model choice on site-specific predictions.

    Science.gov (United States)

    Khazraee, S Hadi; Johnson, Valen; Lord, Dominique

    2018-08-01

    The Poisson-gamma (PG) and Poisson-lognormal (PLN) regression models are among the most popular means for motor vehicle crash data analysis. Both models belong to the Poisson-hierarchical family of models. While numerous studies have compared the overall performance of alternative Bayesian Poisson-hierarchical models, little research has addressed the impact of model choice on the expected crash frequency prediction at individual sites. This paper sought to examine whether there are any trends among candidate models predictions e.g., that an alternative model's prediction for sites with certain conditions tends to be higher (or lower) than that from another model. In addition to the PG and PLN models, this research formulated a new member of the Poisson-hierarchical family of models: the Poisson-inverse gamma (PIGam). Three field datasets (from Texas, Michigan and Indiana) covering a wide range of over-dispersion characteristics were selected for analysis. This study demonstrated that the model choice can be critical when the calibrated models are used for prediction at new sites, especially when the data are highly over-dispersed. For all three datasets, the PIGam model would predict higher expected crash frequencies than would the PLN and PG models, in order, indicating a clear link between the models predictions and the shape of their mixing distributions (i.e., gamma, lognormal, and inverse gamma, respectively). The thicker tail of the PIGam and PLN models (in order) may provide an advantage when the data are highly over-dispersed. The analysis results also illustrated a major deficiency of the Deviance Information Criterion (DIC) in comparing the goodness-of-fit of hierarchical models; models with drastically different set of coefficients (and thus predictions for new sites) may yield similar DIC values, because the DIC only accounts for the parameters in the lowest (observation) level of the hierarchy and ignores the higher levels (regression coefficients

  5. Building aggregate timber supply models from individual harvest choice

    Science.gov (United States)

    Maksym Polyakov; David N. Wear; Robert Huggett

    2009-01-01

    Timber supply has traditionally been modelled using aggregate data. In this paper, we build aggregate supply models for four roundwood products for the US state of North Carolina from a stand-level harvest choice model applied to detailed forest inventory. The simulated elasticities of pulpwood supply are much lower than reported by previous studies. Cross price...

  6. Model parameter updating using Bayesian networks

    International Nuclear Information System (INIS)

    Treml, C.A.; Ross, Timothy J.

    2004-01-01

    This paper outlines a model parameter updating technique for a new method of model validation using a modified model reference adaptive control (MRAC) framework with Bayesian Networks (BNs). The model parameter updating within this method is generic in the sense that the model/simulation to be validated is treated as a black box. It must have updateable parameters to which its outputs are sensitive, and those outputs must have metrics that can be compared to that of the model reference, i.e., experimental data. Furthermore, no assumptions are made about the statistics of the model parameter uncertainty, only upper and lower bounds need to be specified. This method is designed for situations where a model is not intended to predict a complete point-by-point time domain description of the item/system behavior; rather, there are specific points, features, or events of interest that need to be predicted. These specific points are compared to the model reference derived from actual experimental data. The logic for updating the model parameters to match the model reference is formed via a BN. The nodes of this BN consist of updateable model input parameters and the specific output values or features of interest. Each time the model is executed, the input/output pairs are used to adapt the conditional probabilities of the BN. Each iteration further refines the inferred model parameters to produce the desired model output. After parameter updating is complete and model inputs are inferred, reliabilities for the model output are supplied. Finally, this method is applied to a simulation of a resonance control cooling system for a prototype coupled cavity linac. The results are compared to experimental data.

  7. Robustness of public choice models of voting behavior

    Directory of Open Access Journals (Sweden)

    Mihai UNGUREANU

    2013-05-01

    Full Text Available Modern economics modeling practice involves highly unrealistic assumptions. Since testing such models is not always an easy enterprise, researchers face the problem of determining whether a result is dependent (or not on the unrealistic details of the model. A solution for this problem is conducting robustness analysis. In its classical form, robustness analysis is a non-empirical method of confirmation – it raises our trust in a given result by implying it with from several different models. In this paper I argue that robustness analysis could be thought as a method of post-empirical failure. This form of robustness analysis involves assigning guilt for the empirical failure to a certain part of the model. Starting from this notion of robustness, I analyze a case of empirical failure from public choice theory or the economic approach of politics. Using the fundamental methodological principles of neoclassical economics, the first model of voting behavior implied that almost no one would vote. This was clearly an empirical failure. Public choice scholars faced the problem of either restraining the domain of their discipline or giving up to some of their neoclassical methodological features. The second solution was chosen and several different models of voting behavior were built. I will treat these models as a case for performing robustness analysis and I will determine which assumption from the original model is guilty for the empirical failure.

  8. Optimal Effort in Consumer Choice : Theory and Experimental Evidence for Binary Choice

    NARCIS (Netherlands)

    Conlon, B.J.; Dellaert, B.G.C.; van Soest, A.H.O.

    2001-01-01

    This paper develops a theoretical model of optimal effort in consumer choice.The model extends previous consumer choice models in that the consumer not only chooses a product, but also decides how much effort to apply to a given choice problem.The model yields a unique optimal level of effort, which

  9. PARAMETER ESTIMATION IN BREAD BAKING MODEL

    Directory of Open Access Journals (Sweden)

    Hadiyanto Hadiyanto

    2012-05-01

    Full Text Available Bread product quality is highly dependent to the baking process. A model for the development of product quality, which was obtained by using quantitative and qualitative relationships, was calibrated by experiments at a fixed baking temperature of 200°C alone and in combination with 100 W microwave powers. The model parameters were estimated in a stepwise procedure i.e. first, heat and mass transfer related parameters, then the parameters related to product transformations and finally product quality parameters. There was a fair agreement between the calibrated model results and the experimental data. The results showed that the applied simple qualitative relationships for quality performed above expectation. Furthermore, it was confirmed that the microwave input is most meaningful for the internal product properties and not for the surface properties as crispness and color. The model with adjusted parameters was applied in a quality driven food process design procedure to derive a dynamic operation pattern, which was subsequently tested experimentally to calibrate the model. Despite the limited calibration with fixed operation settings, the model predicted well on the behavior under dynamic convective operation and on combined convective and microwave operation. It was expected that the suitability between model and baking system could be improved further by performing calibration experiments at higher temperature and various microwave power levels.  Abstrak  PERKIRAAN PARAMETER DALAM MODEL UNTUK PROSES BAKING ROTI. Kualitas produk roti sangat tergantung pada proses baking yang digunakan. Suatu model yang telah dikembangkan dengan metode kualitatif dan kuantitaif telah dikalibrasi dengan percobaan pada temperatur 200oC dan dengan kombinasi dengan mikrowave pada 100 Watt. Parameter-parameter model diestimasi dengan prosedur bertahap yaitu pertama, parameter pada model perpindahan masa dan panas, parameter pada model transformasi, dan

  10. Interneuronal Mechanism for Tinbergen’s Hierarchical Model of Behavioral Choice

    Science.gov (United States)

    Pirger, Zsolt; Crossley, Michael; László, Zita; Naskar, Souvik; Kemenes, György; O’Shea, Michael; Benjamin, Paul R.; Kemenes, Ildikó

    2014-01-01

    Summary Recent studies of behavioral choice support the notion that the decision to carry out one behavior rather than another depends on the reconfiguration of shared interneuronal networks [1]. We investigated another decision-making strategy, derived from the classical ethological literature [2, 3], which proposes that behavioral choice depends on competition between autonomous networks. According to this model, behavioral choice depends on inhibitory interactions between incompatible hierarchically organized behaviors. We provide evidence for this by investigating the interneuronal mechanisms mediating behavioral choice between two autonomous circuits that underlie whole-body withdrawal [4, 5] and feeding [6] in the pond snail Lymnaea. Whole-body withdrawal is a defensive reflex that is initiated by tactile contact with predators. As predicted by the hierarchical model, tactile stimuli that evoke whole-body withdrawal responses also inhibit ongoing feeding in the presence of feeding stimuli. By recording neurons from the feeding and withdrawal networks, we found no direct synaptic connections between the interneuronal and motoneuronal elements that generate the two behaviors. Instead, we discovered that behavioral choice depends on the interaction between two unique types of interneurons with asymmetrical synaptic connectivity that allows withdrawal to override feeding. One type of interneuron, the Pleuro-Buccal (PlB), is an extrinsic modulatory neuron of the feeding network that completely inhibits feeding when excited by touch-induced monosynaptic input from the second type of interneuron, Pedal-Dorsal12 (PeD12). PeD12 plays a critical role in behavioral choice by providing a synaptic pathway joining the two behavioral networks that underlies the competitive dominance of whole-body withdrawal over feeding. PMID:25155505

  11. The role of respondents’ comfort for variance in stated choice surveys

    DEFF Research Database (Denmark)

    Emang, Diana; Lundhede, Thomas; Thorsen, Bo Jellesmark

    2017-01-01

    they complete surveys correlates with the error variance in stated choice models of their responses. Comfort-related variables are included in the scale functions of the scaled multinomial logit models. The hypothesis was that higher comfort reduces error variance in answers, as revealed by a higher scale...... parameter and vice versa. Information on, e.g., sleep and time since eating (higher comfort) correlated with scale heterogeneity, and produced lower error variance when controlled for in the model. That respondents’ comfort may influence choice behavior suggests that knowledge of the respondents’ activity......Preference elicitation among outdoor recreational users is subject to measurement errors that depend, in part, on survey planning. This study uses data from a choice experiment survey on recreational SCUBA diving to investigate whether self-reported information on respondents’ comfort when...

  12. Assessing the value of museums with a combined discrete choice/ count data model

    NARCIS (Netherlands)

    Rouwendal, J.; Boter, J.

    2009-01-01

    This article assesses the value of Dutch museums using information about destination choice as well as about the number of trips undertaken by an actor. Destination choice is analysed by means of a mixed logit model, and a count data model is used to explain trip generation. We use a

  13. Acquisition of choice in concurrent chains: Assessing the cumulative decision model.

    Science.gov (United States)

    Grace, Randolph C

    2016-05-01

    Concurrent chains is widely used to study pigeons' choice between terminal links that can vary in delay, magnitude, or probability of reinforcement. We review research on the acquisition of choice in this procedure. Acquisition has been studied with a variety of research designs, and some studies have incorporated no-food trials to allow for timing and choice to be observed concurrently. Results show that: Choice can be acquired rapidly within sessions when terminal links change unpredictably; under steady-state conditions, acquisition depends on both initial- and terminal-link schedules; and initial-link responding is mediated by learning about the terminal-link stimulus-reinforcer relations. The cumulative decision model (CDM) proposed by Christensen and Grace (2010) and Grace and McLean (2006, 2015) provides a good description of within-session acquisition, and correctly predicts the effects of initial and terminal-link schedules in steady-state designs (Grace, 2002a). Questions for future research include how abrupt shifts in preference within individual sessions and temporal control of terminal-link responding can be modeled. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Robust estimation of hydrological model parameters

    Directory of Open Access Journals (Sweden)

    A. Bárdossy

    2008-11-01

    Full Text Available The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.

  15. Photovoltaic module parameters acquisition model

    Energy Technology Data Exchange (ETDEWEB)

    Cibira, Gabriel, E-mail: cibira@lm.uniza.sk; Koščová, Marcela, E-mail: mkoscova@lm.uniza.sk

    2014-09-01

    Highlights: • Photovoltaic five-parameter model is proposed using Matlab{sup ®} and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model.

  16. Photovoltaic module parameters acquisition model

    International Nuclear Information System (INIS)

    Cibira, Gabriel; Koščová, Marcela

    2014-01-01

    Highlights: • Photovoltaic five-parameter model is proposed using Matlab ® and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model

  17. Estimating volatility and model parameters of stochastic volatility models with jumps using particle filter

    NARCIS (Netherlands)

    Aihara, ShinIchi; Bagchi, Arunabha; Saha, S.

    Despite the success of particle filter, there are two factors which cause difficulties in its implementation. The first one is the choice of importance functions commonly used in the literature which are far from being optimal. The second one is the combined state and parameter estimation problem.

  18. Investigation on Insar Time Series Deformation Model Considering Rheological Parameters for Soft Clay Subgrade Monitoring

    Science.gov (United States)

    Xing, X.; Yuan, Z.; Chen, L. F.; Yu, X. Y.; Xiao, L.

    2018-04-01

    The stability control is one of the major technical difficulties in the field of highway subgrade construction engineering. Building deformation model is a crucial step for InSAR time series deformation monitoring. Most of the InSAR deformation models for deformation monitoring are pure empirical mathematical models, without considering the physical mechanism of the monitored object. In this study, we take rheology into consideration, inducing rheological parameters into traditional InSAR deformation models. To assess the feasibility and accuracy for our new model, both simulation and real deformation data over Lungui highway (a typical highway built on soft clay subgrade in Guangdong province, China) are investigated with TerraSAR-X satellite imagery. In order to solve the unknows of the non-linear rheological model, three algorithms: Gauss-Newton (GN), Levenberg-Marquarat (LM), and Genetic Algorithm (GA), are utilized and compared to estimate the unknown parameters. Considering both the calculation efficiency and accuracy, GA is chosen as the final choice for the new model in our case study. Preliminary real data experiment is conducted with use of 17 TerraSAR-X Stripmap images (with a 3-m resolution). With the new deformation model and GA aforementioned, the unknown rheological parameters over all the high coherence points are obtained and the LOS deformation (the low-pass component) sequences are generated.

  19. A comparative study of machine learning classifiers for modeling travel mode choice

    NARCIS (Netherlands)

    Hagenauer, J; Helbich, M

    2017-01-01

    The analysis of travel mode choice is an important task in transportation planning and policy making in order to understand and predict travel demands. While advances in machine learning have led to numerous powerful classifiers, their usefulness for modeling travel mode choice remains largely

  20. Nutrieconomic model can facilitate healthy and low-cost food choices.

    Science.gov (United States)

    Primavesi, Laura; Caccavelli, Giovanna; Ciliberto, Alessandra; Pauze, Emmanuel

    2015-04-01

    Promotion of healthy eating can no longer be postponed as a priority, given the alarming growth rate of chronic degenerative diseases in Western countries. We elaborated a nutrieconomic model to assess and identify the most nutritious and affordable food choices. Seventy-one food items representing the main food categories were included and their nationally representative prices monitored. Food composition was determined using CRA-NUT (Centro di Ricerca per gli Alimenti e la Nutrizione) and IEO (Istituto Europeo di Oncologia) databases. To define food nutritional quality, the mean adequacy ratio and mean excess ratio were combined. Both prices and nutritional quality were normalised for the edible food content and for the recommended serving sizes for the Italian adult population. Stores located in different provinces throughout Italy. Not applicable. Cereals and legumes presented very similar nutritional qualities and prices per serving. Seasonal fruits and vegetables presented differentiated nutritional qualities and almost equal prices. Products of animal origin showed similar nutritional qualities and varied prices: the best nutrieconomic choices were milk, oily fish and poultry for the dairy products, fish and meat groups, respectively. Analysing two balanced weekly menus, our nutrieconomic model was able to note a significant decrease in cost of approximately 30 % by varying animal-protein sources without affecting nutritional quality. Healthy eating does not necessarily imply spending large amounts of money but rather being able to make nutritionally optimal choices. The nutrieconomic model is an innovative and practical way to help consumers make correct food choices and nutritionists increase the compliance of their patients.

  1. A novel concurrent pictorial choice model of mood-induced relapse in hazardous drinkers.

    Science.gov (United States)

    Hardy, Lorna; Hogarth, Lee

    2017-12-01

    This study tested whether a novel concurrent pictorial choice procedure, inspired by animal self-administration models, is sensitive to the motivational effect of negative mood induction on alcohol-seeking in hazardous drinkers. Forty-eight hazardous drinkers (scoring ≥7 on the Alcohol Use Disorders Inventory) recruited from the community completed measures of alcohol dependence, depression, and drinking coping motives. Baseline alcohol-seeking was measured by percent choice to enlarge alcohol- versus food-related thumbnail images in two alternative forced-choice trials. Negative and positive mood was then induced in succession by means of self-referential affective statements and music, and percent alcohol choice was measured after each induction in the same way as baseline. Baseline alcohol choice correlated with alcohol dependence severity, r = .42, p = .003, drinking coping motives (in two questionnaires, r = .33, p = .02 and r = .46, p = .001), and depression symptoms, r = .31, p = .03. Alcohol choice was increased by negative mood over baseline (p choice was not related to gender, alcohol dependence, drinking to cope, or depression symptoms (ps ≥ .37). The concurrent pictorial choice measure is a sensitive index of the relative value of alcohol, and provides an accessible experimental model to study negative mood-induced relapse mechanisms in hazardous drinkers. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  2. (1) H-MRS processing parameters affect metabolite quantification

    DEFF Research Database (Denmark)

    Bhogal, Alex A; Schür, Remmelt R; Houtepen, Lotte C

    2017-01-01

    investigated the influence of model parameters and spectral quantification software on fitted metabolite concentration values. Sixty spectra in 30 individuals (repeated measures) were acquired using a 7-T MRI scanner. Data were processed by four independent research groups with the freedom to choose their own...... + NAAG/Cr + PCr and Glu/Cr + PCr, respectively. Metabolite quantification using identical (1) H-MRS data was influenced by processing parameters, basis sets and software choice. Locally preferred processing choices affected metabolite quantification, even when using identical software. Our results......Proton magnetic resonance spectroscopy ((1) H-MRS) can be used to quantify in vivo metabolite levels, such as lactate, γ-aminobutyric acid (GABA) and glutamate (Glu). However, there are considerable analysis choices which can alter the accuracy or precision of (1) H-MRS metabolite quantification...

  3. A framework for estimating health state utility values within a discrete choice experiment: modeling risky choices.

    Science.gov (United States)

    Robinson, Angela; Spencer, Anne; Moffatt, Peter

    2015-04-01

    There has been recent interest in using the discrete choice experiment (DCE) method to derive health state utilities for use in quality-adjusted life year (QALY) calculations, but challenges remain. We set out to develop a risk-based DCE approach to derive utility values for health states that allowed 1) utility values to be anchored directly to normal health and death and 2) worse than dead health states to be assessed in the same manner as better than dead states. Furthermore, we set out to estimate alternative models of risky choice within a DCE model. A survey was designed that incorporated a risk-based DCE and a "modified" standard gamble (SG). Health state utility values were elicited for 3 EQ-5D health states assuming "standard" expected utility (EU) preferences. The DCE model was then generalized to allow for rank-dependent expected utility (RDU) preferences, thereby allowing for probability weighting. A convenience sample of 60 students was recruited and data collected in small groups. Under the assumption of "standard" EU preferences, the utility values derived within the DCE corresponded fairly closely to the mean results from the modified SG. Under the assumption of RDU preferences, the utility values estimated are somewhat lower than under the assumption of standard EU, suggesting that the latter may be biased upward. Applying the correct model of risky choice is important whether a modified SG or a risk-based DCE is deployed. It is, however, possible to estimate a probability weighting function within a DCE and estimate "unbiased" utility values directly, which is not possible within a modified SG. We conclude by setting out the relative strengths and weaknesses of the 2 approaches in this context. © The Author(s) 2014.

  4. Multitasking as a choice: a perspective.

    Science.gov (United States)

    Broeker, Laura; Liepelt, Roman; Poljac, Edita; Künzell, Stefan; Ewolds, Harald; de Oliveira, Rita F; Raab, Markus

    2018-01-01

    Performance decrements in multitasking have been explained by limitations in cognitive capacity, either modelled as static structural bottlenecks or as the scarcity of overall cognitive resources that prevent humans, or at least restrict them, from processing two tasks at the same time. However, recent research has shown that individual differences, flexible resource allocation, and prioritization of tasks cannot be fully explained by these accounts. We argue that understanding human multitasking as a choice and examining multitasking performance from the perspective of judgment and decision-making (JDM), may complement current dual-task theories. We outline two prominent theories from the area of JDM, namely Simple Heuristics and the Decision Field Theory, and adapt these theories to multitasking research. Here, we explain how computational modelling techniques and decision-making parameters used in JDM may provide a benefit to understanding multitasking costs and argue that these techniques and parameters have the potential to predict multitasking behavior in general, and also individual differences in behavior. Finally, we present the one-reason choice metaphor to explain a flexible use of limited capacity as well as changes in serial and parallel task processing. Based on this newly combined approach, we outline a concrete interdisciplinary future research program that we think will help to further develop multitasking research.

  5. Model of twelve properties of a set of organic solvents with graph-theoretical and/or experimental parameters.

    Science.gov (United States)

    Pogliani, Lionello

    2010-01-30

    Twelve properties of a highly heterogeneous class of organic solvents have been modeled with a graph-theoretical molecular connectivity modified (MC) method, which allows to encode the core electrons and the hydrogen atoms. The graph-theoretical method uses the concepts of simple, general, and complete graphs, where these last types of graphs are used to encode the core electrons. The hydrogen atoms have been encoded by the aid of a graph-theoretical perturbation parameter, which contributes to the definition of the valence delta, delta(v), a key parameter in molecular connectivity studies. The model of the twelve properties done with a stepwise search algorithm is always satisfactory, and it allows to check the influence of the hydrogen content of the solvent molecules on the choice of the type of descriptor. A similar argument holds for the influence of the halogen atoms on the type of core electron representation. In some cases the molar mass, and in a minor way, special "ad hoc" parameters have been used to improve the model. A very good model of the surface tension could be obtained by the aid of five experimental parameters. A mixed model method based on experimental parameters plus molecular connectivity indices achieved, instead, to consistently improve the model quality of five properties. To underline is the importance of the boiling point temperatures as descriptors in these last two model methodologies. Copyright 2009 Wiley Periodicals, Inc.

  6. The Answering Process for Multiple-Choice Questions in Collaborative Learning: A Mathematical Learning Model Analysis

    Science.gov (United States)

    Nakamura, Yasuyuki; Nishi, Shinnosuke; Muramatsu, Yuta; Yasutake, Koichi; Yamakawa, Osamu; Tagawa, Takahiro

    2014-01-01

    In this paper, we introduce a mathematical model for collaborative learning and the answering process for multiple-choice questions. The collaborative learning model is inspired by the Ising spin model and the model for answering multiple-choice questions is based on their difficulty level. An intensive simulation study predicts the possibility of…

  7. Sample selection and taste correlation in discrete choice transport modelling

    DEFF Research Database (Denmark)

    Mabit, Stefan Lindhard

    2008-01-01

    explain counterintuitive results in value of travel time estimation. However, the results also point at the difficulty of finding suitable instruments for the selection mechanism. Taste heterogeneity is another important aspect of discrete choice modelling. Mixed logit models are designed to capture...... the question for a broader class of models. It is shown that the original result may be somewhat generalised. Another question investigated is whether mode choice operates as a self-selection mechanism in the estimation of the value of travel time. The results show that self-selection can at least partly...... of taste correlation in willingness-to-pay estimation are presented. The first contribution addresses how to incorporate taste correlation in the estimation of the value of travel time for public transport. Given a limited dataset the approach taken is to use theory on the value of travel time as guidance...

  8. Application of rrm as behavior mode choice on modelling transportation

    Science.gov (United States)

    Surbakti, M. S.; Sadullah, A. F.

    2018-03-01

    Transportation mode selection, the first step in transportation planning process, is probably one of the most important planning elements. The development of models that can explain the preference of passengers regarding their chosen mode of public transport option will contribute to the improvement and development of existing public transport. Logit models have been widely used to determine the mode choice models in which the alternative are different transport modes. Random Regret Minimization (RRM) theory is a theory developed from the behavior to choose (choice behavior) in a state of uncertainty. During its development, the theory was used in various disciplines, such as marketing, micro economy, psychology, management, and transportation. This article aims to show the use of RRM in various modes of selection, from the results of various studies that have been conducted both in north sumatera and western Java.

  9. Model of parameters controlling resistance of pipeline steels to hydrogen-induced cracking

    KAUST Repository

    Traidia, Abderrazak

    2014-01-01

    NACE MR0175/ISO 15156-2 standard provides test conditions and acceptance criteria to evaluate the resistance of carbon and low-alloy steels to hydrogen-induced cracking (HIC). The second option proposed by this standard offers a large flexibility on the choice of test parameters (pH, H2S partial pressure, and test duration), with zero tolerance to HIC initiation as an acceptance condition. The present modeling work is a contribution for a better understanding on how the test parameters and inclusion size can influence HIC initiation, and is therefore of potential interest for both steel makers and endusers. A model able to link the test operating parameters (pH, partial pressure of H2S, and temperature) to the maximum hydrogen pressure generated in the microstructural defects is proposed. The model results are then used to back calculate the minimum fracture toughness below which HIC extends. A minimum fracture toughness of 400 MPa√mm, at the segregation zone, prevents HIC occurrence and leads to successfully pass the HIC qualification test, even under extreme test conditions. The computed results show that the maximum generated pressure can reach up to 1,500 MPa. The results emphasize that the H2S partial pressure and test temperature can both have a strong influence on the final test results, whereas the influence of the pH of the test solution is less significant. © 2014, NACE International.

  10. Airport Choice in Sao Paulo Metropolitan Area: An Application of the Conditional Logit Model

    Science.gov (United States)

    Moreno, Marcelo Baena; Muller, Carlos

    2003-01-01

    Using the conditional LOGIT model, this paper addresses the airport choice in the Sao Paulo Metropolitan Area. In this region, Guarulhos International Airport (GRU) and Congonhas Airport (CGH) compete for passengers flying to several domestic destinations. The airport choice is believed to be a result of the tradeoff passengers perform considering airport access characteristics, airline level of service characteristics and passenger experience with the analyzed airports. It was found that access time to the airports better explain the airport choice than access distance, whereas direct flight frequencies gives better explanation to the airport choice than the indirect (connections and stops) and total (direct plus indirect) flight frequencies. Out of 15 tested variables, passenger experience with the analyzed airports was the variable that best explained the airport choice in the region. Model specifications considering 1, 2 or 3 variables were tested. The model specification most adjusted to the observed data considered access time, direct flight frequencies in the travel period (morning or afternoon peak) and passenger experience with the analyzed airports. The influence of these variables was therefore analyzed across market segments according to departure airport and flight duration criteria. The choice of GRU (located neighboring Sao Paulo city) is not well explained by the rationality of access time economy and the increase of the supply of direct flight frequencies, while the choice of CGH (located inside Sao Paulo city) is. Access time was found to be more important to passengers flying shorter distances while direct flight frequencies in the travel period were more significant to those flying longer distances. Keywords: Airport choice, Multiple airport region, Conditional LOGIT model, Access time, Flight frequencies, Passenger experience with the analyzed airports, Transportation planning

  11. Parameter Estimation of Partial Differential Equation Models.

    Science.gov (United States)

    Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Carroll, Raymond J; Maity, Arnab

    2013-01-01

    Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown, and need to be estimated from the measurements of the dynamic system in the present of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE, and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from LIDAR data.

  12. Parameter Identification of Ship Maneuvering Models Using Recursive Least Square Method Based on Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Man Zhu

    2017-03-01

    Full Text Available Determination of ship maneuvering models is a tough task of ship maneuverability prediction. Among several prime approaches of estimating ship maneuvering models, system identification combined with the full-scale or free- running model test is preferred. In this contribution, real-time system identification programs using recursive identification method, such as the recursive least square method (RLS, are exerted for on-line identification of ship maneuvering models. However, this method seriously depends on the objects of study and initial values of identified parameters. To overcome this, an intelligent technology, i.e., support vector machines (SVM, is firstly used to estimate initial values of the identified parameters with finite samples. As real measured motion data of the Mariner class ship always involve noise from sensors and external disturbances, the zigzag simulation test data include a substantial quantity of Gaussian white noise. Wavelet method and empirical mode decomposition (EMD are used to filter the data corrupted by noise, respectively. The choice of the sample number for SVM to decide initial values of identified parameters is extensively discussed and analyzed. With de-noised motion data as input-output training samples, parameters of ship maneuvering models are estimated using RLS and SVM-RLS, respectively. The comparison between identification results and true values of parameters demonstrates that both the identified ship maneuvering models from RLS and SVM-RLS have reasonable agreements with simulated motions of the ship, and the increment of the sample for SVM positively affects the identification results. Furthermore, SVM-RLS using data de-noised by EMD shows the highest accuracy and best convergence.

  13. Modelling Stochastic Route Choice Behaviours with a Closed-Form Mixed Logit Model

    Directory of Open Access Journals (Sweden)

    Xinjun Lai

    2015-01-01

    Full Text Available A closed-form mixed Logit approach is proposed to model the stochastic route choice behaviours. It combines both the advantages of Probit and Logit to provide a flexible form in alternatives correlation and a tractable form in expression; besides, the heterogeneity in alternative variance can also be addressed. Paths are compared by pairs where the superiority of the binary Probit can be fully used. The Probit-based aggregation is also used for a nested Logit structure. Case studies on both numerical and empirical examples demonstrate that the new method is valid and practical. This paper thus provides an operational solution to incorporate the normal distribution in route choice with an analytical expression.

  14. Discrete Choice and Rational Inattention

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; Melo, Emerson; de Palma, André

    2017-01-01

    This paper establishes a general equivalence between discrete choice and rational inattention models. Matejka and McKay (2015, AER) showed that when information costs are modelled using the Shannon entropy, the result- ing choice probabilities in the rational inattention model take the multinomial...... logit form. We show that when information costs are modelled using a class of generalized entropies, then the choice probabilities in any rational inattention model are observationally equivalent to some additive random utility discrete choice model and vice versa. This equivalence arises from convex...

  15. On the estimability of parameters in undifferenced, uncombined GNSS network and PPP-RTK user models by means of $mathcal {S}$ S -system theory

    Science.gov (United States)

    Odijk, Dennis; Zhang, Baocheng; Khodabandeh, Amir; Odolinski, Robert; Teunissen, Peter J. G.

    2016-01-01

    The concept of integer ambiguity resolution-enabled Precise Point Positioning (PPP-RTK) relies on appropriate network information for the parameters that are common between the single-receiver user that applies and the network that provides this information. Most of the current methods for PPP-RTK are based on forming the ionosphere-free combination using dual-frequency Global Navigation Satellite System (GNSS) observations. These methods are therefore restrictive in the light of the development of new multi-frequency GNSS constellations, as well as from the point of view that the PPP-RTK user requires ionospheric corrections to obtain integer ambiguity resolution results based on short observation time spans. The method for PPP-RTK that is presented in this article does not have above limitations as it is based on the undifferenced, uncombined GNSS observation equations, thereby keeping all parameters in the model. Working with the undifferenced observation equations implies that the models are rank-deficient; not all parameters are unbiasedly estimable, but only combinations of them. By application of S-system theory the model is made of full rank by constraining a minimum set of parameters, or S-basis. The choice of this S-basis determines the estimability and the interpretation of the parameters that are transmitted to the PPP-RTK users. As this choice is not unique, one has to be very careful when comparing network solutions in different S-systems; in that case the S-transformation, which is provided by the S-system method, should be used to make the comparison. Knowing the estimability and interpretation of the parameters estimated by the network is shown to be crucial for a correct interpretation of the estimable PPP-RTK user parameters, among others the essential ambiguity parameters, which have the integer property which is clearly following from the interpretation of satellite phase biases from the network. The flexibility of the S-system method is

  16. The Effects of Land Use Patterns on Tour Type Choice. The Application of a Hybrid Choice Model

    DEFF Research Database (Denmark)

    de Abreu e Silva, João; Sottile, Eleonora; Cherchi, Elisabetta

    2014-01-01

    to travel. Workers who reside in more central, mixed and traditional urban spaces tend to have a higher propensity to travel. Workers who live in more diverse areas have a higher probability of engaging in more complex work related tours. Working in more suburban areas reduces the probability of engaging......The relations between travel behavior and land use patterns have been the object of intensive research in the last two decades. Due to their immediate policy implications, mode choice and vehicle miles of travel (VMT) have been the main focus of attention. Other relevant dimensions, like trip...... of the latent propensity to travel in the discrete choice among types of tours. This model is applied to a travel diary of workers collected in the Lisbon Metropolitan Area in 2009. Different model specifications were built, testing the inclusion of purportedly built land use factors, which have the advantage...

  17. Quality assessment for radiological model parameters

    International Nuclear Information System (INIS)

    Funtowicz, S.O.

    1989-01-01

    A prototype framework for representing uncertainties in radiological model parameters is introduced. This follows earlier development in this journal of a corresponding framework for representing uncertainties in radiological data. Refinements and extensions to the earlier framework are needed in order to take account of the additional contextual factors consequent on using data entries to quantify model parameters. The parameter coding can in turn feed in to methods for evaluating uncertainties in calculated model outputs. (author)

  18. Advertising effects on awareness, consideration and brand choice using tracking data

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans); M. Vriens

    2004-01-01

    textabstractUsing weekly data on advertising expenditures in various media and response data on awareness, consideration and choice, we test the hierarchy of effects hypothesis. Our empirical results, based on a simultaneous equations model with pooled parameters across brands, suggest that we can

  19. Simultaneous modeling of visual saliency and value computation improves predictions of economic choice.

    Science.gov (United States)

    Towal, R Blythe; Mormann, Milica; Koch, Christof

    2013-10-01

    Many decisions we make require visually identifying and evaluating numerous alternatives quickly. These usually vary in reward, or value, and in low-level visual properties, such as saliency. Both saliency and value influence the final decision. In particular, saliency affects fixation locations and durations, which are predictive of choices. However, it is unknown how saliency propagates to the final decision. Moreover, the relative influence of saliency and value is unclear. Here we address these questions with an integrated model that combines a perceptual decision process about where and when to look with an economic decision process about what to choose. The perceptual decision process is modeled as a drift-diffusion model (DDM) process for each alternative. Using psychophysical data from a multiple-alternative, forced-choice task, in which subjects have to pick one food item from a crowded display via eye movements, we test four models where each DDM process is driven by (i) saliency or (ii) value alone or (iii) an additive or (iv) a multiplicative combination of both. We find that models including both saliency and value weighted in a one-third to two-thirds ratio (saliency-to-value) significantly outperform models based on either quantity alone. These eye fixation patterns modulate an economic decision process, also described as a DDM process driven by value. Our combined model quantitatively explains fixation patterns and choices with similar or better accuracy than previous models, suggesting that visual saliency has a smaller, but significant, influence than value and that saliency affects choices indirectly through perceptual decisions that modulate economic decisions.

  20. Constructing food choice decisions.

    Science.gov (United States)

    Sobal, Jeffery; Bisogni, Carole A

    2009-12-01

    Food choice decisions are frequent, multifaceted, situational, dynamic, and complex and lead to food behaviors where people acquire, prepare, serve, give away, store, eat, and clean up. Many disciplines and fields examine decision making. Several classes of theories are applicable to food decision making, including social behavior, social facts, and social definition perspectives. Each offers some insights but also makes limiting assumptions that prevent fully explaining food choice decisions. We used constructionist social definition perspectives to inductively develop a food choice process model that organizes a broad scope of factors and dynamics involved in food behaviors. This food choice process model includes (1) life course events and experiences that establish a food choice trajectory through transitions, turning points, timing, and contexts; (2) influences on food choices that include cultural ideals, personal factors, resources, social factors, and present contexts; and (3) a personal system that develops food choice values, negotiates and balances values, classifies foods and situations, and forms/revises food choice strategies, scripts, and routines. The parts of the model dynamically interact to make food choice decisions leading to food behaviors. No single theory can fully explain decision making in food behavior. Multiple perspectives are needed, including constructionist thinking.

  1. Multi-choice stochastic transportation problem involving general form of distributions.

    Science.gov (United States)

    Quddoos, Abdul; Ull Hasan, Md Gulzar; Khalid, Mohammad Masood

    2014-01-01

    Many authors have presented studies of multi-choice stochastic transportation problem (MCSTP) where availability and demand parameters follow a particular probability distribution (such as exponential, weibull, cauchy or extreme value). In this paper an MCSTP is considered where availability and demand parameters follow general form of distribution and a generalized equivalent deterministic model (GMCSTP) of MCSTP is obtained. It is also shown that all previous models obtained by different authors can be deduced with the help of GMCSTP. MCSTP with pareto, power function or burr-XII distributions are also considered and equivalent deterministic models are obtained. To illustrate the proposed model two numerical examples are presented and solved using LINGO 13.0 software package.

  2. Parameter Estimation of Partial Differential Equation Models

    KAUST Repository

    Xun, Xiaolei

    2013-09-01

    Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from long-range infrared light detection and ranging data. Supplementary materials for this article are available online. © 2013 American Statistical Association.

  3. A note on identification in discrete choice models with partial observability

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; Ranjan, Abhishek

    2017-01-01

    This note establishes a new identification result for additive random utility discrete choice models. A decision-maker associates a random utility Uj+ mj to each alternative in a finite set j∈ {1 , … , J} , where U= {U1, … , UJ} is unobserved by the researcher and random with an unknown joint dis...... for applications where choices are observed aggregated into groups while prices and attributes vary at the level of individual alternatives....

  4. Loss Aversion and Inhibition in Dynamical Models of Multialternative Choice

    Science.gov (United States)

    Usher, Marius; McClelland, James L.

    2004-01-01

    The roles of loss aversion and inhibition among alternatives are examined in models of the similarity, compromise, and attraction effects that arise in choices among 3 alternatives differing on 2 attributes. R. M. Roe, J. R. Busemeyer, and J. T. Townsend (2001) have proposed a linear model in which effects previously attributed to loss aversion…

  5. Westinghouse-GOTHIC distributed parameter modelling for HDR test E11.2

    International Nuclear Information System (INIS)

    Narula, J.S.; Woodcock, J.

    1994-01-01

    The Westinghouse-GOTHIC (WGOTHIC) code is a sophisticated mathematical computer code designed specifically for the thermal hydraulic analysis of nuclear power plant containment and auxiliary buildings. The code is capable of sophisticated flow analysis via the solution of mass, momentum, and energy conservation equations. Westinghouse has investigated the use of subdivided noding to model the flow patterns of hydrogen following its release into a containment atmosphere. For the investigation, several simple models were constructed to represent a scale similar to the German HDR containment. The calculational models were simplified to test the basic capability of the plume modeling methods to predict stratification while minimizing the number of parameters. A large empty volume was modeled, with the same volume and height as HDR. A scenario was selected that would be expected to stably stratify, and the effects of noding on the prediction of stratification was studied. A single phase hot gas was injected into the volume at a height similar to that of HDR test E11.2, and there were no heat sinks modeled. Helium was released into the calculational models, and the resulting flow patterns were judged relative to the expected results. For each model, only the number of subdivisions within the containment volume was varied. The results of the investigation of noding schemes has provided evidence of the capability of subdivided (distributed parameter) noding. The results also showed that highly inaccurate flow patterns could be obtained by using an insufficient number of subdivided nodes. This presents a significant challenge to the containment analyst, who must weigh the benefits of increased noding with the penalties the noding may incur on computational efficiency. Clearly, however, an incorrect noding choice may yield erroneous results even if great care has been taken in modeling accurately all other characteristics of containments. (author). 9 refs., 9 figs

  6. Advanced Nuclear Fuel Cycle Transitions: Optimization, Modeling Choices, and Disruptions

    Science.gov (United States)

    Carlsen, Robert W.

    Many nuclear fuel cycle simulators have evolved over time to help understan the nuclear industry/ecosystem at a macroscopic level. Cyclus is one of th first fuel cycle simulators to accommodate larger-scale analysis with it liberal open-source licensing and first-class Linux support. Cyclus also ha features that uniquely enable investigating the effects of modeling choices o fuel cycle simulators and scenarios. This work is divided into thre experiments focusing on optimization, effects of modeling choices, and fue cycle uncertainty. Effective optimization techniques are developed for automatically determinin desirable facility deployment schedules with Cyclus. A novel method fo mapping optimization variables to deployment schedules is developed. Thi allows relationships between reactor types and scenario constraints to b represented implicitly in the variable definitions enabling the usage o optimizers lacking constraint support. It also prevents wasting computationa resources evaluating infeasible deployment schedules. Deployed power capacit over time and deployment of non-reactor facilities are also included a optimization variables There are many fuel cycle simulators built with different combinations o modeling choices. Comparing results between them is often difficult. Cyclus flexibility allows comparing effects of many such modeling choices. Reacto refueling cycle synchronization and inter-facility competition among othe effects are compared in four cases each using combinations of fleet of individually modeled reactors with 1-month or 3-month time steps. There are noticeable differences in results for the different cases. The larges differences occur during periods of constrained reactor fuel availability This and similar work can help improve the quality of fuel cycle analysi generally There is significant uncertainty associated deploying new nuclear technologie such as time-frames for technology availability and the cost of buildin advanced reactors

  7. A Model of Boundedly Rational Consumer Choice

    OpenAIRE

    Thomas Riechmann

    2000-01-01

    The paper presents an extended version of the standard textbook problem of consumer choice. As usual, agents have to decide about their desired quatities of various consumption goods, at the same time taking into account their limited budget. Prices for the goods are not fixed but arise from a Walrasian interaction of total demand and a stilized supply function for each of the goods. After showing that this type of model cannot be solved analytically, three different types of evolutionary alg...

  8. Automated parameter estimation for biological models using Bayesian statistical model checking.

    Science.gov (United States)

    Hussain, Faraz; Langmead, Christopher J; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram; Jha, Sumit K

    2015-01-01

    Probabilistic models have gained widespread acceptance in the systems biology community as a useful way to represent complex biological systems. Such models are developed using existing knowledge of the structure and dynamics of the system, experimental observations, and inferences drawn from statistical analysis of empirical data. A key bottleneck in building such models is that some system variables cannot be measured experimentally. These variables are incorporated into the model as numerical parameters. Determining values of these parameters that justify existing experiments and provide reliable predictions when model simulations are performed is a key research problem. Using an agent-based model of the dynamics of acute inflammation, we demonstrate a novel parameter estimation algorithm by discovering the amount and schedule of doses of bacterial lipopolysaccharide that guarantee a set of observed clinical outcomes with high probability. We synthesized values of twenty-eight unknown parameters such that the parameterized model instantiated with these parameter values satisfies four specifications describing the dynamic behavior of the model. We have developed a new algorithmic technique for discovering parameters in complex stochastic models of biological systems given behavioral specifications written in a formal mathematical logic. Our algorithm uses Bayesian model checking, sequential hypothesis testing, and stochastic optimization to automatically synthesize parameters of probabilistic biological models.

  9. Towards models of strategic spatial choice behaviour: theory and application issues

    NARCIS (Netherlands)

    Han, Q.; Timmermans, H.J.P.

    2005-01-01

    Models of spatial choice behaviour have been around in urban planning for decades to assess the feasibility of planning actions or to predict external (competition) effects on existing destinations. The well known spatial interaction models of the 1970s have gradually been replaced by discrete

  10. Kinetic models and parameters estimation study of biomass and ...

    African Journals Online (AJOL)

    compaq

    2017-01-11

    Jan 11, 2017 ... Unstructured models were proposed using the logistic equation for growth, the ... analysis of variance (ANOVA) was also used to validate the proposed models. ... production but their choice depends on the cost and the.

  11. Clinical validation of the LKB model and parameter sets for predicting radiation-induced pneumonitis from breast cancer radiotherapy

    International Nuclear Information System (INIS)

    Tsougos, Ioannis; Mavroidis, Panayiotis; Theodorou, Kyriaki; Rajala, J; Pitkaenen, M A; Holli, K; Ojala, A T; Hyoedynmaa, S; Jaervenpaeae, Ritva; Lind, Bengt K; Kappas, Constantin

    2006-01-01

    The choice of the appropriate model and parameter set in determining the relation between the incidence of radiation pneumonitis and dose distribution in the lung is of great importance, especially in the case of breast radiotherapy where the observed incidence is fairly low. From our previous study based on 150 breast cancer patients, where the fits of dose-volume models to clinical data were estimated (Tsougos et al 2005 Evaluation of dose-response models and parameters predicting radiation induced pneumonitis using clinical data from breast cancer radiotherapy Phys. Med. Biol. 50 3535-54), one could get the impression that the relative seriality is significantly better than the LKB NTCP model. However, the estimation of the different NTCP models was based on their goodness-of-fit on clinical data, using various sets of published parameters from other groups, and this fact may provisionally justify the results. Hence, we sought to investigate further the LKB model, by applying different published parameter sets for the very same group of patients, in order to be able to compare the results. It was shown that, depending on the parameter set applied, the LKB model is able to predict the incidence of radiation pneumonitis with acceptable accuracy, especially when implemented on a sub-group of patients (120) receiving D-bar-bar vertical bar EUD higher than 8 Gy. In conclusion, the goodness-of-fit of a certain radiobiological model on a given clinical case is closely related to the selection of the proper scoring criteria and parameter set as well as to the compatibility of the clinical case from which the data were derived. (letter to the editor)

  12. The influence of model parameters on catchment-response

    International Nuclear Information System (INIS)

    Shah, S.M.S.; Gabriel, H.F.; Khan, A.A.

    2002-01-01

    This paper deals with the study of influence of influence of conceptual rainfall-runoff model parameters on catchment response (runoff). A conceptual modified watershed yield model is employed to study the effects of model-parameters on catchment-response, i.e. runoff. The model is calibrated, using manual parameter-fitting approach, also known as trial and error parameter-fitting. In all, there are twenty one (21) parameters that control the functioning of the model. A lumped parametric approach is used. The detailed analysis was performed on Ling River near Kahuta, having catchment area of 56 sq. miles. The model includes physical parameters like GWSM, PETS, PGWRO, etc. fitting coefficients like CINF, CGWS, etc. and initial estimates of the surface-water and groundwater storages i.e. srosp and gwsp. Sensitivity analysis offers a good way, without repetititious computations, the proper weight and consideration that must be taken when each of the influencing factor is evaluated. Sensitivity-analysis was performed to evaluate the influence of model-parameters on runoff. The sensitivity and relative contributions of model parameters influencing catchment-response are studied. (author)

  13. The role of intention as mediator between latent effects and behavior: application of a hybrid choice model to study departure time choices

    DEFF Research Database (Denmark)

    Thorhauge, Mikkel; Cherchi, Elisabetta; Walker, Joan L.

    2017-01-01

    of them consider the effect of intention and its role as mediator between those psychological effects and the choice, as implied in the Theory of Planned Behavior. In this paper we contribute to the literature in this field by specifically studying the direct effect of the intention on the actual behavior......, while attitude, social norms, and perceived behavioral control affect the intention to behave in a given way. We apply a hybrid choice model to study the departure time choice. For this, we use data from Danish commuters in the morning rush hours in the Greater Copenhagen area. We find a significant...

  14. How the health belief model helps the tobacco industry: individuals, choice, and "information".

    Science.gov (United States)

    Balbach, Edith D; Smith, Elizabeth A; Malone, Ruth E

    2006-12-01

    To analyse trial and deposition testimony of tobacco industry executives to determine how they use the concepts of "information" and "choice" and consider how these concepts are related to theoretical models of health behaviour change. We coded and analysed transcripts of trial and deposition testimony of 14 high-level executives representing six companies plus the Tobacco Institute. We conducted an interpretive analysis of industry executives' characterisation of the industry's role as information provider and the agency of tobacco consumers in making "choices". Tobacco industry executives deployed the concept of "information" as a mechanism that shifted to consumers full moral responsibility for the harms caused by tobacco products. The industry's role was characterised as that of impartial supplier of value-free "information", without regard to its quality, accuracy and truthfulness. Tobacco industry legal defences rely on assumptions congruent with and supported by individual rational choice theories, particularly those that emphasise individual, autonomous decision-makers. Tobacco control advocates and health educators must challenge the industry's preferred framing, pointing out that "information" is not value-free. Multi-level, multi-sectoral interventions are critical to tobacco use prevention. Over-reliance on individual and interpersonal rational choice models may have the effect of validating the industry's model of smoking and cessation behaviour, absolving it of responsibility and rendering invisible the "choices" the industry has made and continues to make in promoting the most deadly consumer product ever made.

  15. A Joint Modeling Analysis of Passengers’ Intercity Travel Destination and Mode Choices in Yangtze River Delta Megaregion of China

    Directory of Open Access Journals (Sweden)

    Yanli Wang

    2016-01-01

    Full Text Available Joint destination-mode travel choice models are developed for intercity long-distance travel among sixteen cities in Yangtze River Delta Megaregion of China. The model is developed for all the trips in the sample and also by two different trip purposes, work-related business and personal business trips, to accommodate different time values and attraction factors. A nested logit modeling framework is applied to model trip destination and mode choices in two different levels, where the lower level is a mode choice model and the upper level is a destination choice model. The utility values from various travel modes in the lower level are summarized into a composite utility, which is then specified into the destination choice model as an intercity impedance factor. The model is then applied to predict the change in passenger number from Shanghai to Yangzhou between scenarios with and without high-speed rail service to demonstrate the applicability. It is helpful for understanding and modeling megaregional travel destination and mode choice behaviors in the context of developing country.

  16. Do Methodological Choices in Environmental Modeling Bias Rebound Effects? A Case Study on Electric Cars.

    Science.gov (United States)

    Font Vivanco, David; Tukker, Arnold; Kemp, René

    2016-10-18

    Improvements in resource efficiency often underperform because of rebound effects. Calculations of the size of rebound effects are subject to various types of bias, among which methodological choices have received particular attention. Modellers have primarily focused on choices related to changes in demand, however, choices related to modeling the environmental burdens from such changes have received less attention. In this study, we analyze choices in the environmental assessment methods (life cycle assessment (LCA) and hybrid LCA) and environmental input-output databases (E3IOT, Exiobase and WIOD) used as a source of bias. The analysis is done for a case study on battery electric and hydrogen cars in Europe. The results describe moderate rebound effects for both technologies in the short term. Additionally, long-run scenarios are calculated by simulating the total cost of ownership, which describe notable rebound effect sizes-from 26 to 59% and from 18 to 28%, respectively, depending on the methodological choices-with favorable economic conditions. Relevant sources of bias are found to be related to incomplete background systems, technology assumptions and sectorial aggregation. These findings highlight the importance of the method setup and of sensitivity analyses of choices related to environmental modeling in rebound effect assessments.

  17. End use technology choice in the National Energy Modeling System (NEMS): An analysis of the residential and commercial building sectors

    International Nuclear Information System (INIS)

    Wilkerson, Jordan T.; Cullenward, Danny; Davidian, Danielle; Weyant, John P.

    2013-01-01

    The National Energy Modeling System (NEMS) is arguably the most influential energy model in the United States. The U.S. Energy Information Administration uses NEMS to generate the federal government's annual long-term forecast of national energy consumption and to evaluate prospective federal energy policies. NEMS is considered such a standard tool that other models are calibrated to its forecasts, in both government and academic practice. As a result, NEMS has a significant influence over expert opinions of plausible energy futures. NEMS is a massively detailed model whose inner workings, despite its prominence, receive relatively scant critical attention. This paper analyzes how NEMS projects energy demand in the residential and commercial sectors. In particular, we focus on the role of consumers' preferences and financial constraints, investigating how consumers choose appliances and other end-use technologies. We identify conceptual issues in the approach the model takes to the same question across both sectors. Running the model with a range of consumer preferences, we estimate the extent to which this issue impacts projected consumption relative to the baseline model forecast for final energy demand in the year 2035. In the residential sector, the impact ranges from a decrease of 0.73 quads (− 6.0%) to an increase of 0.24 quads (+ 2.0%). In the commercial sector, the impact ranges from a decrease of 1.0 quads (− 9.0%) to an increase of 0.99 quads (+ 9.0%). - Highlights: • This paper examines the impact of consumer preferences on final energy in the Commercial and Residential sectors of the National Energy Modeling System (NEMS). • We describe the conceptual and empirical basis for modeling consumer technology choice in NEMS. • We offer a range of alternative parameters to show the energy demand sensitivity to technology choice. • We show there are significant potential savings available in both building sectors. • Because the model uses its own

  18. On parameter estimation in deformable models

    DEFF Research Database (Denmark)

    Fisker, Rune; Carstensen, Jens Michael

    1998-01-01

    Deformable templates have been intensively studied in image analysis through the last decade, but despite its significance the estimation of model parameters has received little attention. We present a method for supervised and unsupervised model parameter estimation using a general Bayesian form...

  19. It's the parameters, stupid! Moving beyond multi-model and multi-physics approaches to characterize and reduce predictive uncertainty in process-based hydrological models

    Science.gov (United States)

    Clark, Martyn; Samaniego, Luis; Freer, Jim

    2014-05-01

    Multi-model and multi-physics approaches are a popular tool in environmental modelling, with many studies focusing on optimally combining output from multiple model simulations to reduce predictive errors and better characterize predictive uncertainty. However, a careful and systematic analysis of different hydrological models reveals that individual models are simply small permutations of a master modeling template, and inter-model differences are overwhelmed by uncertainty in the choice of the parameter values in the model equations. Furthermore, inter-model differences do not explicitly represent the uncertainty in modeling a given process, leading to many situations where different models provide the wrong results for the same reasons. In other cases, the available morphological data does not support the very fine spatial discretization of the landscape that typifies many modern applications of process-based models. To make the uncertainty characterization problem worse, the uncertain parameter values in process-based models are often fixed (hard-coded), and the models lack the agility necessary to represent the tremendous heterogeneity in natural systems. This presentation summarizes results from a systematic analysis of uncertainty in process-based hydrological models, where we explicitly analyze the myriad of subjective decisions made throughout both the model development and parameter estimation process. Results show that much of the uncertainty is aleatory in nature - given a "complete" representation of dominant hydrologic processes, uncertainty in process parameterizations can be represented using an ensemble of model parameters. Epistemic uncertainty associated with process interactions and scaling behavior is still important, and these uncertainties can be represented using an ensemble of different spatial configurations. Finally, uncertainty in forcing data can be represented using ensemble methods for spatial meteorological analysis. Our systematic

  20. Cell size spatial convergence analysis on GOTHIC distributed parameter models for studying hydrogen mixing behaviour in CANDU containments

    International Nuclear Information System (INIS)

    Yim, K.; Wong, R.C.

    1995-01-01

    Gas mixing phenomena can be modelled using distributed parameter codes such as GOTHIC, but the selection of the optimum cell size is an important user input. The tradeoff between accuracy and practical computation times affect the choice of cell sizes, where small cells provide better accuracy at the expense of longer computing time. A study on cell size effect on hydrogen distribution is presented for the problem of hydrogen mixing behaviour in a typical CANDU reactor containment following a severe reactor accident. Optimal cell sizes were found for different room volumes, hydrogen release profiles and elevations using spatial convergence criteria. The findings of this study provide the technical basis for the cell size selection in the GOTHIC distributed parameter models used for analysing hydrogen mixing behaviour. (author). 1 ref., 1 tab., 13 figs

  1. Factoring out nondecision time in choice reaction time data: Theory and implications.

    Science.gov (United States)

    Verdonck, Stijn; Tuerlinckx, Francis

    2016-03-01

    Choice reaction time (RT) experiments are an invaluable tool in psychology and neuroscience. A common assumption is that the total choice response time is the sum of a decision and a nondecision part (time spent on perceptual and motor processes). While the decision part is typically modeled very carefully (commonly with diffusion models), a simple and ad hoc distribution (mostly uniform) is assumed for the nondecision component. Nevertheless, it has been shown that the misspecification of the nondecision time can severely distort the decision model parameter estimates. In this article, we propose an alternative approach to the estimation of choice RT models that elegantly bypasses the specification of the nondecision time distribution by means of an unconventional convolution of data and decision model distributions (hence called the D*M approach). Once the decision model parameters have been estimated, it is possible to compute a nonparametric estimate of the nondecision time distribution. The technique is tested on simulated data, and is shown to systematically remove traditional estimation bias related to misspecified nondecision time, even for a relatively small number of observations. The shape of the actual underlying nondecision time distribution can also be recovered. Next, the D*M approach is applied to a selection of existing diffusion model application articles. For all of these studies, substantial quantitative differences with the original analyses are found. For one study, these differences radically alter its final conclusions, underlining the importance of our approach. Additionally, we find that strongly right skewed nondecision time distributions are not at all uncommon. (c) 2016 APA, all rights reserved).

  2. Voltage stability, bifurcation parameters and continuation methods

    Energy Technology Data Exchange (ETDEWEB)

    Alvarado, F L [Wisconsin Univ., Madison, WI (United States)

    1994-12-31

    This paper considers the importance of the choice of bifurcation parameter in the determination of the voltage stability limit and the maximum power load ability of a system. When the bifurcation parameter is power demand, the two limits are equivalent. However, when other types of load models and bifurcation parameters are considered, the two concepts differ. The continuation method is considered as a method for determination of voltage stability margins. Three variants of the continuation method are described: the continuation parameter is the bifurcation parameter the continuation parameter is initially the bifurcation parameter, but is free to change, and the continuation parameter is a new `arc length` parameter. Implementations of voltage stability software using continuation methods are described. (author) 23 refs., 9 figs.

  3. Noisy preferences in risky choice: A cautionary note.

    Science.gov (United States)

    Bhatia, Sudeep; Loomes, Graham

    2017-10-01

    We examine the effects of multiple sources of noise in risky decision making. Noise in the parameters that characterize an individual's preferences can combine with noise in the response process to distort observed choice proportions. Thus, underlying preferences that conform to expected value maximization can appear to show systematic risk aversion or risk seeking. Similarly, core preferences that are consistent with expected utility theory, when perturbed by such noise, can appear to display nonlinear probability weighting. For this reason, modal choices cannot be used simplistically to infer underlying preferences. Quantitative model fits that do not allow for both sorts of noise can lead to wrong conclusions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  4. A flexible, interactive software tool for fitting the parameters of neuronal models.

    Science.gov (United States)

    Friedrich, Péter; Vella, Michael; Gulyás, Attila I; Freund, Tamás F; Káli, Szabolcs

    2014-01-01

    The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible) the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation) of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problems of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire) neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting tool.

  5. A flexible, interactive software tool for fitting the parameters of neuronal models

    Directory of Open Access Journals (Sweden)

    Péter eFriedrich

    2014-07-01

    Full Text Available The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problem of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting

  6. Effect of social influence on consumer choice behavior using a sequential stated choice experiment: A study of city trip itinerary choice

    NARCIS (Netherlands)

    Pan, X.; Rasouli, S.; Timmermans, H.J.P.

    2018-01-01

    This paper introduces a model that captures the effect of social influence on individual choice behavior. The suggested model shares with previous models the idea to add a term to the deterministic utility function of the choice alternative, chosen by a social network member, to measure an

  7. The sensitivity of ecosystem service models to choices of input data and spatial resolution

    Science.gov (United States)

    Bagstad, Kenneth J.; Cohen, Erika; Ancona, Zachary H.; McNulty, Steven; Sun, Ge

    2018-01-01

    Although ecosystem service (ES) modeling has progressed rapidly in the last 10–15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study, we compared the results of different models to address these questions at national, provincial, and subwatershed scales in Rwanda. We compared results for carbon, water, and sediment as modeled using InVEST and WaSSI using (1) land cover data at 30 and 300 m resolution and (2) three different input land cover datasets. WaSSI and simpler InVEST models (carbon storage and annual water yield) were relatively insensitive to the choice of spatial resolution, but more complex InVEST models (seasonal water yield and sediment regulation) produced large differences when applied at differing resolution. Six out of nine ES metrics (InVEST annual and seasonal water yield and WaSSI) gave similar predictions for at least two different input land cover datasets. Despite differences in mean values when using different data sources and resolution, we found significant and highly correlated results when using Spearman's rank correlation, indicating consistent spatial patterns of high and low values. Our results confirm and extend conclusions of past studies, showing that in certain cases (e.g., simpler models and national-scale analyses), results can be robust to data and modeling choices. For more complex models, those with different output metrics, and subnational to site-based analyses in heterogeneous environments, data and model choices may strongly influence study findings.

  8. Modeling hurricane evacuation traffic : testing the gravity and intervening opportunity models as models of destination choice in hurricane evacuation.

    Science.gov (United States)

    2006-09-01

    The test was conducted by estimating the models on a portion of evacuation data from South Carolina following Hurricane Floyd, and then observing how well the models reproduced destination choice at the county level on the remaining data. The tests s...

  9. Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver

    Science.gov (United States)

    Kang, Ling; Zhou, Liwei

    2018-02-01

    Abstract . The Muskingum model is an effective flood routing technology in hydrology and water resources Engineering. With the development of optimization technology, more and more variable-parameter Muskingum models were presented to improve effectiveness of the Muskingum model in recent decades. A variable-parameter nonlinear Muskingum model (NVPNLMM) was proposed in this paper. According to the results of two real and frequently-used case studies by various models, the NVPNLMM could obtain better values of evaluation criteria, which are used to describe the superiority of the estimated outflows and compare the accuracies of flood routing using various models, and the optimal estimated outflows by the NVPNLMM were closer to the observed outflows than the ones by other models.

  10. Analyzing Multiple-Choice Questions by Model Analysis and Item Response Curves

    Science.gov (United States)

    Wattanakasiwich, P.; Ananta, S.

    2010-07-01

    In physics education research, the main goal is to improve physics teaching so that most students understand physics conceptually and be able to apply concepts in solving problems. Therefore many multiple-choice instruments were developed to probe students' conceptual understanding in various topics. Two techniques including model analysis and item response curves were used to analyze students' responses from Force and Motion Conceptual Evaluation (FMCE). For this study FMCE data from more than 1000 students at Chiang Mai University were collected over the past three years. With model analysis, we can obtain students' alternative knowledge and the probabilities for students to use such knowledge in a range of equivalent contexts. The model analysis consists of two algorithms—concentration factor and model estimation. This paper only presents results from using the model estimation algorithm to obtain a model plot. The plot helps to identify a class model state whether it is in the misconception region or not. Item response curve (IRC) derived from item response theory is a plot between percentages of students selecting a particular choice versus their total score. Pros and cons of both techniques are compared and discussed.

  11. A Day-to-Day Route Choice Model Based on Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Fangfang Wei

    2014-01-01

    Full Text Available Day-to-day traffic dynamics are generated by individual traveler’s route choice and route adjustment behaviors, which are appropriate to be researched by using agent-based model and learning theory. In this paper, we propose a day-to-day route choice model based on reinforcement learning and multiagent simulation. Travelers’ memory, learning rate, and experience cognition are taken into account. Then the model is verified and analyzed. Results show that the network flow can converge to user equilibrium (UE if travelers can remember all the travel time they have experienced, but which is not necessarily the case under limited memory; learning rate can strengthen the flow fluctuation, but memory leads to the contrary side; moreover, high learning rate results in the cyclical oscillation during the process of flow evolution. Finally, both the scenarios of link capacity degradation and random link capacity are used to illustrate the model’s applications. Analyses and applications of our model demonstrate the model is reasonable and useful for studying the day-to-day traffic dynamics.

  12. Choice probability generating functions

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; McFadden, Daniel; Bierlaire, Michel

    2010-01-01

    This paper establishes that every random utility discrete choice model (RUM) has a representation that can be characterized by a choice-probability generating function (CPGF) with specific properties, and that every function with these specific properties is consistent with a RUM. The choice...... probabilities from the RUM are obtained from the gradient of the CPGF. Mixtures of RUM are characterized by logarithmic mixtures of their associated CPGF. The paper relates CPGF to multivariate extreme value distributions, and reviews and extends methods for constructing generating functions for applications....... The choice probabilities of any ARUM may be approximated by a cross-nested logit model. The results for ARUM are extended to competing risk survival models....

  13. Exploring alternatives to rational choice in models of Behaviour:An investigation using travel mode choice

    OpenAIRE

    Thomas, Gregory Owen

    2014-01-01

    The car is the most popular travel mode in the UK, but reliance on the car has numerous negative effects on health, the economy, and the environment. Encouraging sustainable travel mode choices (modal choice) can minimise these problems. To promote behaviour change, psychologists have an interest in understanding modal choice. Historically, modal choice has been understood as a reasoned and rational decision that requires a conscious assessment of thoughts and attitudes: but evidence suggests...

  14. Perceived and Implicit Ranking of Academic Journals: An Optimization Choice Model

    Science.gov (United States)

    Xie, Frank Tian; Cai, Jane Z.; Pan, Yue

    2012-01-01

    A new system of ranking academic journals is proposed in this study and optimization choice model used to analyze data collected from 346 faculty members in a business discipline. The ranking model uses the aggregation of perceived, implicit sequencing of academic journals by academicians, therefore eliminating several key shortcomings of previous…

  15. Role of deceleration parameter and interacting dark energy in singularity avoidance

    Science.gov (United States)

    Abdussattar; Prajapati, S. R.

    2011-02-01

    A class of non-singular bouncing FRW models are obtained by constraining the deceleration parameter in the presence of an interacting dark energy represented by a time-varying cosmological constant. The models being geometrically closed, initially accelerate for a certain period of time and decelerate thereafter and are also free from the entropy and cosmological constant problems. Taking a constant of integration equal to zero one particular model is discussed in some detail and the variation of different cosmological parameters are shown graphically for specific values of the parameters of the model. For some specific choice of the parameters of the model the ever expanding models of Ozer & Taha and Abdel-Rahman and the decelerating models of Berman and also the Einstein de-Sitter model may be obtained as special cases of this particular model.

  16. The selection of a mode of urban transportation: Integrating psychological variables to discrete choice models

    International Nuclear Information System (INIS)

    Cordoba Maquilon, Jorge E; Gonzalez Calderon, Carlos A; Posada Henao, John J

    2011-01-01

    A study using revealed preference surveys and psychological tests was conducted. Key psychological variables of behavior involved in the choice of transportation mode in a population sample of the Metropolitan Area of the Valle de Aburra were detected. The experiment used the random utility theory for discrete choice models and reasoned action in order to assess beliefs. This was used as a tool for analysis of the psychological variables using the sixteen personality factor questionnaire (16PF test). In addition to the revealed preference surveys, two other surveys were carried out: one with socio-economic characteristics and the other with latent indicators. This methodology allows for an integration of discrete choice models and latent variables. The integration makes the model operational and quantifies the unobservable psychological variables. The most relevant result obtained was that anxiety affects the choice of urban transportation mode and shows that physiological alterations, as well as problems in perception and beliefs, can affect the decision-making process.

  17. Importance of the habitat choice behavior assumed when modeling the effects of food and temperature on fish populations

    Science.gov (United States)

    Wildhaber, Mark L.; Lamberson, Peter J.

    2004-01-01

    Various mechanisms of habitat choice in fishes based on food and/or temperature have been proposed: optimal foraging for food alone; behavioral thermoregulation for temperature alone; and behavioral energetics and discounted matching for food and temperature combined. Along with development of habitat choice mechanisms, there has been a major push to develop and apply to fish populations individual-based models that incorporate various forms of these mechanisms. However, it is not known how the wide variation in observed and hypothesized mechanisms of fish habitat choice could alter fish population predictions (e.g. growth, size distributions, etc.). We used spatially explicit, individual-based modeling to compare predicted fish populations using different submodels of patch choice behavior under various food and temperature distributions. We compared predicted growth, temperature experience, food consumption, and final spatial distribution using the different models. Our results demonstrated that the habitat choice mechanism assumed in fish population modeling simulations was critical to predictions of fish distribution and growth rates. Hence, resource managers who use modeling results to predict fish population trends should be very aware of and understand the underlying patch choice mechanisms used in their models to assure that those mechanisms correctly represent the fish populations being modeled.

  18. Universally sloppy parameter sensitivities in systems biology models.

    Directory of Open Access Journals (Sweden)

    Ryan N Gutenkunst

    2007-10-01

    Full Text Available Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

  19. Universally sloppy parameter sensitivities in systems biology models.

    Science.gov (United States)

    Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

    2007-10-01

    Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

  20. Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

    Directory of Open Access Journals (Sweden)

    Jonathan R Karr

    2015-05-01

    Full Text Available Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.

  1. Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models

    Science.gov (United States)

    Mizukami, Naoki; Clark, Martyn P.; Gutmann, Ethan D.; Mendoza, Pablo A.; Newman, Andrew J.; Nijssen, Bart; Livneh, Ben; Hay, Lauren E.; Arnold, Jeffrey R.; Brekke, Levi D.

    2016-01-01

    Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.

  2. Quantum Cournot equilibrium for the Hotelling–Smithies model of product choice

    International Nuclear Information System (INIS)

    Rahaman, Ramij; Majumdar, Priyadarshi; Basu, B

    2012-01-01

    This paper demonstrates the quantization of a spatial Cournot duopoly model with product choice, a two stage game focusing on non-cooperation in locations and quantities. With quantization, the players can access a continuous set of strategies, using a continuous variable quantum mechanical approach. The presence of quantum entanglement in the initial state identifies a quantity equilibrium for each location pair choice with any transport cost. Also higher profit is obtained by the firms at Nash equilibrium. Adoption of quantum strategies rewards us by the existence of a larger quantum strategic space at equilibrium. (paper)

  3. A choice modelling analysis on the similarity between distribution utilities' and industrial customers' price and quality preferences

    International Nuclear Information System (INIS)

    Soederberg, Magnus

    2008-01-01

    The Swedish Electricity Act states that electricity distribution must comply with both price and quality requirements. In order to maintain efficient regulation it is necessary to firstly, define quality attributes and secondly, determine a customer's priorities concerning price and quality attributes. If distribution utilities gain an understanding of customer preferences and incentives for reporting them, the regulator can save a lot of time by surveying them rather than their customers. This study applies a choice modelling methodology where utilities and industrial customers are asked to evaluate the same twelve choice situations in which price and four specific quality attributes are varied. The preferences expressed by the utilities, and estimated by a random parameter logit, correspond quite well with the preferences expressed by the largest industrial customers. The preferences expressed by the utilities are reasonably homogenous in relation to forms of association (private limited, public and trading partnership). If the regulator acts according to the preferences expressed by the utilities, smaller industrial customers will have to pay for quality they have not asked for. (author)

  4. Socio-demographic characteristics affecting sport tourism choices: A structural model

    Directory of Open Access Journals (Sweden)

    Nataša Slak Valek

    2014-03-01

    Full Text Available Background: Effective tourism management in the field of sports tourism requires an understanding of differences in socioeconomic characteristics both within and between different market segments. Objective: In the broad tourism market demographic characteristics have been extensively analyzed for differences in destination choices, however little is known about demographic factors affecting sport tourists' decisions. Methods: A sample of Slovenian sports tourists was analyzed using data from a comprehensive survey of local and outbound tourist activity conducted by the Statistical Office of the Republic of Slovenia in 2008. After data weighting the information for 353,783 sports related trips were available for analysis. The research model adopted suggests that four socio-demographic characteristics (gender, age, level of education and income significantly affect a tourist's choice of sports related travel either locally within Slovenia or to a foreign country. Furthermore the destination (local or foreign has an influence on the choice of the type of accommodation selected and the tourist's total expenditure for the trip. For testing the first part of our model (the socio-demographic characteristics effects a linear regression was used, and for the final part of the model (the selection of accommodation type and travel expenditure t-test were applied. Results: The result shows the standardized β regression coefficients are all statistically significant at the .001 level for the tested socio-demographic characteristics and also the overall regression model was statistically significant at .001 level. Conclusions: With these results the study confirmed that all the selected socio-demographic characteristics have a significant influence on the sport-active tourist when choosing between a domestic and foreign tourism destination which in turn affect the type of accommodation chosen and the level of expenditure while travelling.

  5. An Empirical Study of Parameter Estimation for Stated Preference Experimental Design

    Directory of Open Access Journals (Sweden)

    Fei Yang

    2014-01-01

    Full Text Available The stated preference experimental design can affect the reliability of the parameters estimation in discrete choice model. Some scholars have proposed some new experimental designs, such as D-efficient, Bayesian D-efficient. But insufficient empirical research has been conducted on the effectiveness of these new designs and there has been little comparative analysis of the new designs against the traditional designs. In this paper, a new metro connecting Chengdu and its satellite cities is taken as the research subject to demonstrate the validity of the D-efficient and Bayesian D-efficient design. Comparisons between these new designs and orthogonal design were made by the fit of model and standard deviation of parameters estimation; then the best model result is obtained to analyze the travel choice behavior. The results indicate that Bayesian D-efficient design works better than D-efficient design. Some of the variables can affect significantly the choice behavior of people, including the waiting time and arrival time. The D-efficient and Bayesian D-efficient design for MNL can acquire reliability result in ML model, but the ML model cannot develop the theory advantages of these two designs. Finally, the metro can handle over 40% passengers flow if the metro will be operated in the future.

  6. Systematic parameter inference in stochastic mesoscopic modeling

    Energy Technology Data Exchange (ETDEWEB)

    Lei, Huan; Yang, Xiu [Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Li, Zhen [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States)

    2017-02-01

    We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.

  7. A Bayesian multidimensional scaling procedure for the spatial analysis of revealed choice data

    NARCIS (Netherlands)

    DeSarbo, WS; Kim, Y; Fong, D

    1999-01-01

    We present a new Bayesian formulation of a vector multidimensional scaling procedure for the spatial analysis of binary choice data. The Gibbs sampler is gainfully employed to estimate the posterior distribution of the specified scalar products, bilinear model parameters. The computational procedure

  8. Test models for improving filtering with model errors through stochastic parameter estimation

    International Nuclear Information System (INIS)

    Gershgorin, B.; Harlim, J.; Majda, A.J.

    2010-01-01

    The filtering skill for turbulent signals from nature is often limited by model errors created by utilizing an imperfect model for filtering. Updating the parameters in the imperfect model through stochastic parameter estimation is one way to increase filtering skill and model performance. Here a suite of stringent test models for filtering with stochastic parameter estimation is developed based on the Stochastic Parameterization Extended Kalman Filter (SPEKF). These new SPEKF-algorithms systematically correct both multiplicative and additive biases and involve exact formulas for propagating the mean and covariance including the parameters in the test model. A comprehensive study is presented of robust parameter regimes for increasing filtering skill through stochastic parameter estimation for turbulent signals as the observation time and observation noise are varied and even when the forcing is incorrectly specified. The results here provide useful guidelines for filtering turbulent signals in more complex systems with significant model errors.

  9. Рassenger survey on public transport in Zhitomir and evaluation of the main technical and operational parameters for the choice of city buses

    Directory of Open Access Journals (Sweden)

    Rudzynskyi V.V.

    2016-08-01

    Full Text Available The parameters of the passenger movements in the direction of public transport in Zhitomir are defined and conformity assessment of technical and operational parameters of urban shuttle buses is folded. Firstly, the amount of passenger traffic affects the optimal choice of passenger vehicles and secondly, the intensity of road traffic on the streets of areas where passengers pass routes. It should also be kept in mind that passenger traffic can fluctuate significantly depending on the time of day and days of the week. But virtually all carriers can be replaced within days with rolling at a large passenger capacity, and vice versa. Therefore, the choice of one type of rolling stock, the capacity of which is set taking into account the data on hourly passenger capacity on the most loaded part of the route up to an hour "peak", or its capacity per day on the route as a whole. Thus the research work on inspection of passenger-route passenger transport, and public electric transport in Zhitomir is conducted. Primary data was estimated to select the main criteria for urban passenger bus. It was found that the buses in the "peak" hours move on passenger congestion. Preliminary conclusions and recommendations on the criteria of optimal rolling of choice for the city bus route network are provided.

  10. A comprehensive dwelling unit choice model accommodating psychological constructs within a search strategy for consideration set formation.

    Science.gov (United States)

    2015-12-01

    This study adopts a dwelling unit level of analysis and considers a probabilistic choice set generation approach for residential choice modeling. In doing so, we accommodate the fact that housing choices involve both characteristics of the dwelling u...

  11. Sensorimotor learning biases choice behavior: a learning neural field model for decision making.

    Directory of Open Access Journals (Sweden)

    Christian Klaes

    Full Text Available According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action

  12. Emerging Australian Education Markets: A Discrete Choice Model of Taiwanese and Indonesian Student Intended Study Destination.

    Science.gov (United States)

    Kemp, Steven; Madden, Gary; Simpson, Michael

    1998-01-01

    Isolates factors influencing choice of Australia as a preferred destination for international students in emerging regional markets. Uses data obtained from a survey of students in Indonesia and Taiwan to estimate a U.S./Australia and rest-of-world/Australia discrete destination-choice model. This model identifies key factors determining country…

  13. A Stochastic Route Choice Model for Car Travellers in the Copenhagen Region

    DEFF Research Database (Denmark)

    Nielsen, Otto Anker; Frederiksen, Rasmus Dyhr; Daly, A.

    2002-01-01

    The paper presents a large-scale stochastic road traffic assignment model for the Copenhagen Region. The model considers several classes of passenger cars (different trip purposes), vans and trucks, each with its own utility function on which route choices are based. The utility functions include...

  14. Model complexity and choice of model approaches for practical simulations of CO2 injection, migration, leakage and long-term fate

    Energy Technology Data Exchange (ETDEWEB)

    Celia, Michael A. [Princeton Univ., NJ (United States)

    2016-12-30

    This report documents the accomplishments achieved during the project titled “Model complexity and choice of model approaches for practical simulations of CO2 injection,migration, leakage and long-term fate” funded by the US Department of Energy, Office of Fossil Energy. The objective of the project was to investigate modeling approaches of various levels of complexity relevant to geologic carbon storage (GCS) modeling with the goal to establish guidelines on choice of modeling approach.

  15. How urban environment affects travel behavior? Integrated Choice and Latent Variable Model for Travel Schedules

    DEFF Research Database (Denmark)

    La Paix, Lissy; Bierlaire, Michel; Cherchi, Elisabetta

    2013-01-01

    The relationship between urban environment and travel behaviour is not a new problem. Neighbourhood characteristics may affect mobility of dwellers in different ways, such as frequency of trips, mode used, structure of the tours, and so on. At the same time, qualitative issues related...... to the individual attitude towards specific behaviour have recently become important in transport modelling contributing to a better understanding of travel demand. Following this research line, in this paper we study the effect of neighbourhood characteristics in the choice of the type of tours performed, but we...... assume that neighbourhood characteristics can also affect the individual propensity to travel and hence the choice of the tours throughout the propensity to travel. Since the propensity to travel is not observed, we employ hybrid choice models to estimate jointly the discrete choice of tours...

  16. Modelling the Choices of Romanian Consumers in the Context of the Current Economic Crisis

    Directory of Open Access Journals (Sweden)

    Madalina Balau

    2012-05-01

    Full Text Available Consumption is a key factor of the nowadays post-industrial society, while it is a real engine ofproduction, diversity of offer and demand, and motive for innovation. On the other side, consumption can beharmful to the same society and to environment if it develops in an un-sustainable way. That is why,understanding the consumer behaviour is of great importance not only to satisfy his or her needs but also tofind appropriate means to educate people and issue policies that can lead to sustainable consumption anddevelopment. The paper presents some models and theories regarding the consumer behaviour and proposesmeans to influence consumption characteristics and habits of people. The modelling approach isdeterministic, using Expectancy-Value theory, taking into account not only explicit (rational choices but alsohabits or incentives (non-rational choices, in a weighted quantitative model. The novelty of the approachconsists in the way non-rational choices are taken into consideration for the existing model, and on how it isused in determining directions for sustainable consumption. The study is developed on public data regardingconsumers of general goods in Romania.

  17. Exploiting intrinsic fluctuations to identify model parameters.

    Science.gov (United States)

    Zimmer, Christoph; Sahle, Sven; Pahle, Jürgen

    2015-04-01

    Parameterisation of kinetic models plays a central role in computational systems biology. Besides the lack of experimental data of high enough quality, some of the biggest challenges here are identification issues. Model parameters can be structurally non-identifiable because of functional relationships. Noise in measured data is usually considered to be a nuisance for parameter estimation. However, it turns out that intrinsic fluctuations in particle numbers can make parameters identifiable that were previously non-identifiable. The authors present a method to identify model parameters that are structurally non-identifiable in a deterministic framework. The method takes time course recordings of biochemical systems in steady state or transient state as input. Often a functional relationship between parameters presents itself by a one-dimensional manifold in parameter space containing parameter sets of optimal goodness. Although the system's behaviour cannot be distinguished on this manifold in a deterministic framework it might be distinguishable in a stochastic modelling framework. Their method exploits this by using an objective function that includes a measure for fluctuations in particle numbers. They show on three example models, immigration-death, gene expression and Epo-EpoReceptor interaction, that this resolves the non-identifiability even in the case of measurement noise with known amplitude. The method is applied to partially observed recordings of biochemical systems with measurement noise. It is simple to implement and it is usually very fast to compute. This optimisation can be realised in a classical or Bayesian fashion.

  18. Investigating Spatial Interdependence in E-Bike Choice Using Spatially Autoregressive Model

    Directory of Open Access Journals (Sweden)

    Chengcheng Xu

    2017-08-01

    Full Text Available Increased attention has been given to promoting e-bike usage in recent years. However, the research gap still exists in understanding the effects of spatial interdependence on e-bike choice. This study investigated how spatial interdependence affected the e-bike choice. The Moran’s I statistic test showed that spatial interdependence exists in e-bike choice at aggregated level. Bayesian spatial autoregressive logistic analyses were then used to investigate the spatial interdependence at individual level. Separate models were developed for commuting and non-commuting trips. The factors affecting e-bike choice are different between commuting and non-commuting trips. Spatial interdependence exists at both origin and destination sides of commuting and non-commuting trips. Travellers are more likely to choose e-bikes if their neighbours at the trip origin and destination also travel by e-bikes. And the magnitude of this spatial interdependence is different across various traffic analysis zones. The results suggest that, without considering spatial interdependence, the traditional methods may have biased estimation results and make systematic forecasting errors.

  19. Food and energy choices for India: a programming model with partial endogenous energy requirements.

    Science.gov (United States)

    Parikh, K S; Srinivasan, T N

    1980-09-01

    This paper presents a mathematical model for all matter-energy processing subsystems at the level of the society, specifically India. It explores India's choices in the food and energy sectors over the coming decades. Alternative land intensive, irrigation energy intensive, and fertilizer intensive techniques of food production are identified using a nonlinear programming model. The land saved is devoted to growing firewood. The optimum combination of railway (steam, diesel, and electric traction) and road (automobiles, diesel trucks, and diesel and gasoline buses) transport is determined. For the oil sector, two alternative sources of supply of crude oil and petroleum products are included, namely, domestic production and imports. The optimum choice is determined through a linear programming model. While the model is basically a static one, designed to determine the optimal choice for the target year of 2000-2001, certain intertemporal detail is incorporated for electricity generation. The model minimizes the costs of meeting the needs for food, transport in terms of passenger kilometers and goods per ton per kilometer, energy needs for domestic cooking and lighting, and the energy needs of the rest of the economy.

  20. Incorporating model parameter uncertainty into inverse treatment planning

    International Nuclear Information System (INIS)

    Lian Jun; Xing Lei

    2004-01-01

    Radiobiological treatment planning depends not only on the accuracy of the models describing the dose-response relation of different tumors and normal tissues but also on the accuracy of tissue specific radiobiological parameters in these models. Whereas the general formalism remains the same, different sets of model parameters lead to different solutions and thus critically determine the final plan. Here we describe an inverse planning formalism with inclusion of model parameter uncertainties. This is made possible by using a statistical analysis-based frameset developed by our group. In this formalism, the uncertainties of model parameters, such as the parameter a that describes tissue-specific effect in the equivalent uniform dose (EUD) model, are expressed by probability density function and are included in the dose optimization process. We found that the final solution strongly depends on distribution functions of the model parameters. Considering that currently available models for computing biological effects of radiation are simplistic, and the clinical data used to derive the models are sparse and of questionable quality, the proposed technique provides us with an effective tool to minimize the effect caused by the uncertainties in a statistical sense. With the incorporation of the uncertainties, the technique has potential for us to maximally utilize the available radiobiology knowledge for better IMRT treatment

  1. The axiom of choice

    CERN Document Server

    Jech, Thomas J

    2008-01-01

    Comprehensive in its selection of topics and results, this self-contained text examines the relative strengths and consequences of the axiom of choice. Each chapter contains several problems, graded according to difficulty, and concludes with some historical remarks.An introduction to the use of the axiom of choice is followed by explorations of consistency, permutation models, and independence. Subsequent chapters examine embedding theorems, models with finite supports, weaker versions of the axiom, and nontransferable statements. The final sections consider mathematics without choice, cardin

  2. Parameter discovery in stochastic biological models using simulated annealing and statistical model checking.

    Science.gov (United States)

    Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J

    2014-01-01

    Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.

  3. Establishing statistical models of manufacturing parameters

    International Nuclear Information System (INIS)

    Senevat, J.; Pape, J.L.; Deshayes, J.F.

    1991-01-01

    This paper reports on the effect of pilgering and cold-work parameters on contractile strain ratio and mechanical properties that were investigated using a large population of Zircaloy tubes. Statistical models were established between: contractile strain ratio and tooling parameters, mechanical properties (tensile test, creep test) and cold-work parameters, and mechanical properties and stress-relieving temperature

  4. Some tests for parameter constancy in cointegrated VAR-models

    DEFF Research Database (Denmark)

    Hansen, Henrik; Johansen, Søren

    1999-01-01

    Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations, and anot...... be applied to test the constancy of the long-run parameters in the cointegrated VAR-model. All results are illustrated using a model for the term structure of interest rates on US Treasury securities. ......Some methods for the evaluation of parameter constancy in vector autoregressive (VAR) models are discussed. Two different ways of re-estimating the VAR model are proposed; one in which all parameters are estimated recursively based upon the likelihood function for the first observations......, and another in which the cointegrating relations are estimated recursively from a likelihood function, where the short-run parameters have been concentrated out. We suggest graphical procedures based on recursively estimated eigenvalues to evaluate the constancy of the long-run parameters in the model...

  5. Edge Modeling by Two Blur Parameters in Varying Contrasts.

    Science.gov (United States)

    Seo, Suyoung

    2018-06-01

    This paper presents a method of modeling edge profiles with two blur parameters, and estimating and predicting those edge parameters with varying brightness combinations and camera-to-object distances (COD). First, the validity of the edge model is proven mathematically. Then, it is proven experimentally with edges from a set of images captured for specifically designed target sheets and with edges from natural images. Estimation of the two blur parameters for each observed edge profile is performed with a brute-force method to find parameters that produce global minimum errors. Then, using the estimated blur parameters, actual blur parameters of edges with arbitrary brightness combinations are predicted using a surface interpolation method (i.e., kriging). The predicted surfaces show that the two blur parameters of the proposed edge model depend on both dark-side edge brightness and light-side edge brightness following a certain global trend. This is similar across varying CODs. The proposed edge model is compared with a one-blur parameter edge model using experiments of the root mean squared error for fitting the edge models to each observed edge profile. The comparison results suggest that the proposed edge model has superiority over the one-blur parameter edge model in most cases where edges have varying brightness combinations.

  6. Decision-Tree Models of Categorization Response Times, Choice Proportions, and Typicality Judgments

    Science.gov (United States)

    Lafond, Daniel; Lacouture, Yves; Cohen, Andrew L.

    2009-01-01

    The authors present 3 decision-tree models of categorization adapted from T. Trabasso, H. Rollins, and E. Shaughnessy (1971) and use them to provide a quantitative account of categorization response times, choice proportions, and typicality judgments at the individual-participant level. In Experiment 1, the decision-tree models were fit to…

  7. Housing land transaction data and structural econometric estimation of preference parameters for urban economic simulation models.

    Science.gov (United States)

    Caruso, Geoffrey; Cavailhès, Jean; Peeters, Dominique; Thomas, Isabelle; Frankhauser, Pierre; Vuidel, Gilles

    2015-12-01

    This paper describes a dataset of 6284 land transactions prices and plot surfaces in 3 medium-sized cities in France (Besançon, Dijon and Brest). The dataset includes road accessibility as obtained from a minimization algorithm, and the amount of green space available to households in the neighborhood of the transactions, as evaluated from a land cover dataset. Further to the data presentation, the paper describes how these variables can be used to estimate the non-observable parameters of a residential choice function explicitly derived from a microeconomic model. The estimates are used by Caruso et al. (2015) to run a calibrated microeconomic urban growth simulation model where households are assumed to trade-off accessibility and local green space amenities.

  8. Housing land transaction data and structural econometric estimation of preference parameters for urban economic simulation models

    Science.gov (United States)

    Caruso, Geoffrey; Cavailhès, Jean; Peeters, Dominique; Thomas, Isabelle; Frankhauser, Pierre; Vuidel, Gilles

    2015-01-01

    This paper describes a dataset of 6284 land transactions prices and plot surfaces in 3 medium-sized cities in France (Besançon, Dijon and Brest). The dataset includes road accessibility as obtained from a minimization algorithm, and the amount of green space available to households in the neighborhood of the transactions, as evaluated from a land cover dataset. Further to the data presentation, the paper describes how these variables can be used to estimate the non-observable parameters of a residential choice function explicitly derived from a microeconomic model. The estimates are used by Caruso et al. (2015) to run a calibrated microeconomic urban growth simulation model where households are assumed to trade-off accessibility and local green space amenities. PMID:26958606

  9. Momentous Choices: Testing nonstandard decision models in health and housing markets

    NARCIS (Netherlands)

    M. Filko (Martin)

    2013-01-01

    markdownabstract__Abstract__ During more than half a century, several strands of research contributed to the development of decision theory. The standard normative model for choice under uncertainty – expected utility – was given a foundation by von Neumann and Morgenstern (1944) and Savage

  10. MATHEMATICAL MODELLING OF PREFERED SOLUTIONS CHOICE FUNCTION FOR TUBULAR GAS HEATERS BY EXPERIMENTAL INFORMATIONS

    Directory of Open Access Journals (Sweden)

    BARSUK R. V.

    2016-08-01

    Full Text Available Annotation. Problems formulation. The article deals with choice functions building of preferred solutions by experimental information for tubular gas heater working on fuel granules - pellets.Further choice functions using for making technical solutions by tubular gas heaters construction and designing. Recently research analysis. There are works about choice functions construction by separate presents are examined. But full chose functions building by separate presents are not examined. Aims and tasks. There are setting aim to develop full choice functions mathematical model on separate presents by authors. The expert are connect to primary experimental data’s evaluation that estimates separate results by output functions (criteria. Its evaluations issue in experimental points paired comparison’s table form. Thus, there are necessary construct binary choice relations presents on experimental “points” set by expert that then using for full choice function’s constructing. Conclusions. There are choice function’s construction’s sequence are sets. There are posed point comparison results that characterized tubular gas heater’s condition with expert’s evaluation using. Also posed output functions comparisons by which can be characterized improving tubular gas heater’s performance or vice versa.

  11. Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

    Science.gov (United States)

    da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G

    2016-07-08

    Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.

  12. Choice probability generating functions

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; McFadden, Daniel; Bierlaire, Michel

    2013-01-01

    This paper considers discrete choice, with choice probabilities coming from maximization of preferences from a random utility field perturbed by additive location shifters (ARUM). Any ARUM can be characterized by a choice-probability generating function (CPGF) whose gradient gives the choice...... probabilities, and every CPGF is consistent with an ARUM. We relate CPGF to multivariate extreme value distributions, and review and extend methods for constructing CPGF for applications. The choice probabilities of any ARUM may be approximated by a cross-nested logit model. The results for ARUM are extended...

  13. Environmental Transport Input Parameters for the Biosphere Model

    Energy Technology Data Exchange (ETDEWEB)

    M. A. Wasiolek

    2003-06-27

    This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699

  14. Environmental Transport Input Parameters for the Biosphere Model

    International Nuclear Information System (INIS)

    Wasiolek, M. A.

    2003-01-01

    This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (TWP) (BSC 2003 [163602]). Some documents in Figure 1-1 may be under development and not available when this report is issued. This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA), but access to the listed documents is not required to understand the contents of this report. This report is one of the reports that develops input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2003 [160699]) describes the conceptual model, the mathematical model, and the input parameters. The purpose of this analysis is to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or volcanic ash). The analysis was performed in accordance with the TWP (BSC 2003 [163602]). This analysis develops values of parameters associated with many features, events, and processes (FEPs) applicable to the reference biosphere (DTN: M00303SEPFEPS2.000 [162452]), which are addressed in the biosphere model (BSC 2003 [160699]). The treatment of these FEPs is described in BSC (2003 [160699], Section 6.2). Parameter values

  15. Parameter estimation in stochastic rainfall-runoff models

    DEFF Research Database (Denmark)

    Jonsdottir, Harpa; Madsen, Henrik; Palsson, Olafur Petur

    2006-01-01

    A parameter estimation method for stochastic rainfall-runoff models is presented. The model considered in the paper is a conceptual stochastic model, formulated in continuous-discrete state space form. The model is small and a fully automatic optimization is, therefore, possible for estimating all...... the parameter values are optimal for simulation or prediction. The data originates from Iceland and the model is designed for Icelandic conditions, including a snow routine for mountainous areas. The model demands only two input data series, precipitation and temperature and one output data series...

  16. Economic incentives and individuals choice between welfare programmes and work in Denmark

    DEFF Research Database (Denmark)

    Rasmussen, Martin

    We estimate the effect of welfare benefits and wages on individuals' choice between working or collecting one of three welfare programmes. We compare the magnitude of transitions between various welfare programmes with transitions between, say, work and disability benefit. We use simulation methods...... to estimate random parameters. Estimation results show significant effects of economic incentives and significant variations of estimated parameters. Experiments with the estimated model show that transitions within welfare programmes are important relative to transitions between such programmes and work....

  17. A method for model identification and parameter estimation

    International Nuclear Information System (INIS)

    Bambach, M; Heinkenschloss, M; Herty, M

    2013-01-01

    We propose and analyze a new method for the identification of a parameter-dependent model that best describes a given system. This problem arises, for example, in the mathematical modeling of material behavior where several competing constitutive equations are available to describe a given material. In this case, the models are differential equations that arise from the different constitutive equations, and the unknown parameters are coefficients in the constitutive equations. One has to determine the best-suited constitutive equations for a given material and application from experiments. We assume that the true model is one of the N possible parameter-dependent models. To identify the correct model and the corresponding parameters, we can perform experiments, where for each experiment we prescribe an input to the system and observe a part of the system state. Our approach consists of two stages. In the first stage, for each pair of models we determine the experiment, i.e. system input and observation, that best differentiates between the two models, and measure the distance between the two models. Then we conduct N(N − 1) or, depending on the approach taken, N(N − 1)/2 experiments and use the result of the experiments as well as the previously computed model distances to determine the true model. We provide sufficient conditions on the model distances and measurement errors which guarantee that our approach identifies the correct model. Given the model, we identify the corresponding model parameters in the second stage. The problem in the second stage is a standard parameter estimation problem and we use a method suitable for the given application. We illustrate our approach on three examples, including one where the models are elliptic partial differential equations with different parameterized right-hand sides and an example where we identify the constitutive equation in a problem from computational viscoplasticity. (paper)

  18. Accounting for perception in random regret choice models: Weberian and generalized Weberian specifications

    NARCIS (Netherlands)

    Jang, S.; Rasouli, S.; Timmermans, H.J.P.

    2016-01-01

    Recently, regret-based choice models have been introduced in the travel behavior research community as an alternative to expected/random utility models. The fundamental proposition underlying regret theory is that individuals minimize the amount of regret they (are expected to) experience when

  19. A discrete-continuous choice model of climate change impacts on energy

    International Nuclear Information System (INIS)

    Morrison, W.N.; Mendelsohn, R.

    1998-01-01

    This paper estimates a discrete-continuous fuel choice model in order to explore climate impacts on the energy sector. The model is estimated on a national data set of firms and households. The results reveal that actors switch from oil in cold climates to electricity and natural gas in warm climates and that fuel-specific expenditures follow a U-shaped relationship with respect to temperature. The model implies that warming will increase American energy expenditures, reflecting a sizable welfare damage

  20. Application of lumped-parameter models

    DEFF Research Database (Denmark)

    Ibsen, Lars Bo; Liingaard, Morten

    This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil (section 1.1). Subse...

  1. A simulation of water pollution model parameter estimation

    Science.gov (United States)

    Kibler, J. F.

    1976-01-01

    A parameter estimation procedure for a water pollution transport model is elaborated. A two-dimensional instantaneous-release shear-diffusion model serves as representative of a simple transport process. Pollution concentration levels are arrived at via modeling of a remote-sensing system. The remote-sensed data are simulated by adding Gaussian noise to the concentration level values generated via the transport model. Model parameters are estimated from the simulated data using a least-squares batch processor. Resolution, sensor array size, and number and location of sensor readings can be found from the accuracies of the parameter estimates.

  2. Identification of ecosystem parameters by SDE-modelling

    DEFF Research Database (Denmark)

    Stochastic differential equations (SDEs) for ecosystem modelling have attracted increasing attention during recent years. The modelling has mostly been through simulation experiments in order to analyse how system noise propagates through the ordinary differential equation formulation of ecosystem...... models. Estimation of parameters in SDEs is, however, possible by combining Kalman filter techniques and likelihood estimation. By modelling parameters as random walks it is possible to identify linear as well as non-linear interactions between ecosystem components. By formulating a simple linear SDE...

  3. Spatio-temporal modeling of nonlinear distributed parameter systems

    CERN Document Server

    Li, Han-Xiong

    2011-01-01

    The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein s

  4. Modeling tourists joint choices of transportation and destination : towards an analytical tool to support the marketing of complex tourism services

    NARCIS (Netherlands)

    Dellaert, B.G.C.; Borgers, A.W.J.; Timmermans, H.J.P.

    1993-01-01

    This paper introduces a model to describe tourists’ joint choices of transportation and destination. The proposed modeling approach is based on the principles and methodology of decompositional choice modeling. It represents an extension of the models that have traditionally been applied to single

  5. GEMSFITS: Code package for optimization of geochemical model parameters and inverse modeling

    International Nuclear Information System (INIS)

    Miron, George D.; Kulik, Dmitrii A.; Dmytrieva, Svitlana V.; Wagner, Thomas

    2015-01-01

    Highlights: • Tool for generating consistent parameters against various types of experiments. • Handles a large number of experimental data and parameters (is parallelized). • Has a graphical interface and can perform statistical analysis on the parameters. • Tested on fitting the standard state Gibbs free energies of aqueous Al species. • Example on fitting interaction parameters of mixing models and thermobarometry. - Abstract: GEMSFITS is a new code package for fitting internally consistent input parameters of GEM (Gibbs Energy Minimization) geochemical–thermodynamic models against various types of experimental or geochemical data, and for performing inverse modeling tasks. It consists of the gemsfit2 (parameter optimizer) and gfshell2 (graphical user interface) programs both accessing a NoSQL database, all developed with flexibility, generality, efficiency, and user friendliness in mind. The parameter optimizer gemsfit2 includes the GEMS3K chemical speciation solver ( (http://gems.web.psi.ch/GEMS3K)), which features a comprehensive suite of non-ideal activity- and equation-of-state models of solution phases (aqueous electrolyte, gas and fluid mixtures, solid solutions, (ad)sorption. The gemsfit2 code uses the robust open-source NLopt library for parameter fitting, which provides a selection between several nonlinear optimization algorithms (global, local, gradient-based), and supports large-scale parallelization. The gemsfit2 code can also perform comprehensive statistical analysis of the fitted parameters (basic statistics, sensitivity, Monte Carlo confidence intervals), thus supporting the user with powerful tools for evaluating the quality of the fits and the physical significance of the model parameters. The gfshell2 code provides menu-driven setup of optimization options (data selection, properties to fit and their constraints, measured properties to compare with computed counterparts, and statistics). The practical utility, efficiency, and

  6. Determinants of Awareness, Consideration, and Choice Set Size in University Choice.

    Science.gov (United States)

    Dawes, Philip L.; Brown, Jennifer

    2002-01-01

    Developed and tested a model of students' university "brand" choice using five individual-level variables (ethnic group, age, gender, number of parents going to university, and academic ability) and one situational variable (duration of search) to explain variation in the sizes of awareness, consideration, and choice decision sets. (EV)

  7. Taylor expansion of luminosity distance in Szekeres cosmological models: effects of local structures evolution on cosmographic parameters

    Energy Technology Data Exchange (ETDEWEB)

    Villani, Mattia, E-mail: villani@fi.infn.it [Sezione INFN di Firenze, Polo Scientifico Via Sansone 1, 50019, Sesto Fiorentino (Italy)

    2014-06-01

    We consider the Goode-Wainwright representation of the Szekeres cosmological models and calculate the Taylor expansion of the luminosity distance in order to study the effects of the inhomogeneities on cosmographic parameters. Without making a particular choice for the arbitrary functions defining the metric, we Taylor expand up to the second order in redshift for Family I and up to the third order for Family II Szekeres metrics under the hypotesis, based on observation, that local structure formation is over. In a conservative fashion, we also allow for the existence of a non null cosmological constant.

  8. Identification of parameters of discrete-continuous models

    International Nuclear Information System (INIS)

    Cekus, Dawid; Warys, Pawel

    2015-01-01

    In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible

  9. Identification of parameters of discrete-continuous models

    Energy Technology Data Exchange (ETDEWEB)

    Cekus, Dawid, E-mail: cekus@imipkm.pcz.pl; Warys, Pawel, E-mail: warys@imipkm.pcz.pl [Institute of Mechanics and Machine Design Foundations, Czestochowa University of Technology, Dabrowskiego 73, 42-201 Czestochowa (Poland)

    2015-03-10

    In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible.

  10. Identifying the connective strength between model parameters and performance criteria

    Directory of Open Access Journals (Sweden)

    B. Guse

    2017-11-01

    Full Text Available In hydrological models, parameters are used to represent the time-invariant characteristics of catchments and to capture different aspects of hydrological response. Hence, model parameters need to be identified based on their role in controlling the hydrological behaviour. For the identification of meaningful parameter values, multiple and complementary performance criteria are used that compare modelled and measured discharge time series. The reliability of the identification of hydrologically meaningful model parameter values depends on how distinctly a model parameter can be assigned to one of the performance criteria. To investigate this, we introduce the new concept of connective strength between model parameters and performance criteria. The connective strength assesses the intensity in the interrelationship between model parameters and performance criteria in a bijective way. In our analysis of connective strength, model simulations are carried out based on a latin hypercube sampling. Ten performance criteria including Nash–Sutcliffe efficiency (NSE, Kling–Gupta efficiency (KGE and its three components (alpha, beta and r as well as RSR (the ratio of the root mean square error to the standard deviation for different segments of the flow duration curve (FDC are calculated. With a joint analysis of two regression tree (RT approaches, we derive how a model parameter is connected to different performance criteria. At first, RTs are constructed using each performance criterion as the target variable to detect the most relevant model parameters for each performance criterion. Secondly, RTs are constructed using each parameter as the target variable to detect which performance criteria are impacted by changes in the values of one distinct model parameter. Based on this, appropriate performance criteria are identified for each model parameter. In this study, a high bijective connective strength between model parameters and performance criteria

  11. Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters

    Science.gov (United States)

    Harvey, Natalie J.; Huntley, Nathan; Dacre, Helen F.; Goldstein, Michael; Thomson, David; Webster, Helen

    2018-01-01

    Following the disruption to European airspace caused by the eruption of Eyjafjallajökull in 2010 there has been a move towards producing quantitative predictions of volcanic ash concentration using volcanic ash transport and dispersion simulators. However, there is no formal framework for determining the uncertainties of these predictions and performing many simulations using these complex models is computationally expensive. In this paper a Bayesian linear emulation approach is applied to the Numerical Atmospheric-dispersion Modelling Environment (NAME) to better understand the influence of source and internal model parameters on the simulator output. Emulation is a statistical method for predicting the output of a computer simulator at new parameter choices without actually running the simulator. A multi-level emulation approach is applied using two configurations of NAME with different numbers of model particles. Information from many evaluations of the computationally faster configuration is combined with results from relatively few evaluations of the slower, more accurate, configuration. This approach is effective when it is not possible to run the accurate simulator many times and when there is also little prior knowledge about the influence of parameters. The approach is applied to the mean ash column loading in 75 geographical regions on 14 May 2010. Through this analysis it has been found that the parameters that contribute the most to the output uncertainty are initial plume rise height, mass eruption rate, free tropospheric turbulence levels and precipitation threshold for wet deposition. This information can be used to inform future model development and observational campaigns and routine monitoring. The analysis presented here suggests the need for further observational and theoretical research into parameterisation of atmospheric turbulence. Furthermore it can also be used to inform the most important parameter perturbations for a small operational

  12. Agricultural and Environmental Input Parameters for the Biosphere Model

    International Nuclear Information System (INIS)

    Kaylie Rasmuson; Kurt Rautenstrauch

    2003-01-01

    This analysis is one of nine technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. It documents input parameters for the biosphere model, and supports the use of the model to develop Biosphere Dose Conversion Factors (BDCF). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in the biosphere Technical Work Plan (TWP, BSC 2003a). It should be noted that some documents identified in Figure 1-1 may be under development and therefore not available at the time this document is issued. The ''Biosphere Model Report'' (BSC 2003b) describes the ERMYN and its input parameters. This analysis report, ANL-MGR-MD-000006, ''Agricultural and Environmental Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. This report defines and justifies values for twelve parameters required in the biosphere model. These parameters are related to use of contaminated groundwater to grow crops. The parameter values recommended in this report are used in the soil, plant, and carbon-14 submodels of the ERMYN

  13. Verification Techniques for Parameter Selection and Bayesian Model Calibration Presented for an HIV Model

    Science.gov (United States)

    Wentworth, Mami Tonoe

    Uncertainty quantification plays an important role when making predictive estimates of model responses. In this context, uncertainty quantification is defined as quantifying and reducing uncertainties, and the objective is to quantify uncertainties in parameter, model and measurements, and propagate the uncertainties through the model, so that one can make a predictive estimate with quantified uncertainties. Two of the aspects of uncertainty quantification that must be performed prior to propagating uncertainties are model calibration and parameter selection. There are several efficient techniques for these processes; however, the accuracy of these methods are often not verified. This is the motivation for our work, and in this dissertation, we present and illustrate verification frameworks for model calibration and parameter selection in the context of biological and physical models. First, HIV models, developed and improved by [2, 3, 8], describe the viral infection dynamics of an HIV disease. These are also used to make predictive estimates of viral loads and T-cell counts and to construct an optimal control for drug therapy. Estimating input parameters is an essential step prior to uncertainty quantification. However, not all the parameters are identifiable, implying that they cannot be uniquely determined by the observations. These unidentifiable parameters can be partially removed by performing parameter selection, a process in which parameters that have minimal impacts on the model response are determined. We provide verification techniques for Bayesian model calibration and parameter selection for an HIV model. As an example of a physical model, we employ a heat model with experimental measurements presented in [10]. A steady-state heat model represents a prototypical behavior for heat conduction and diffusion process involved in a thermal-hydraulic model, which is a part of nuclear reactor models. We employ this simple heat model to illustrate verification

  14. A Monte Carlo study of the impact of the choice of rectum volume definition on estimates of equivalent uniform doses and the volume parameter

    International Nuclear Information System (INIS)

    Kvinnsland, Yngve; Muren, Ludvig Paul; Dahl, Olav

    2004-01-01

    Calculations of normal tissue complication probability (NTCP) values for the rectum are difficult because it is a hollow, non-rigid, organ. Finding the true cumulative dose distribution for a number of treatment fractions requires a CT scan before each treatment fraction. This is labour intensive, and several surrogate distributions have therefore been suggested, such as dose wall histograms, dose surface histograms and histograms for the solid rectum, with and without margins. In this study, a Monte Carlo method is used to investigate the relationships between the cumulative dose distributions based on all treatment fractions and the above-mentioned histograms that are based on one CT scan only, in terms of equivalent uniform dose. Furthermore, the effect of a specific choice of histogram on estimates of the volume parameter of the probit NTCP model was investigated. It was found that the solid rectum and the rectum wall histograms (without margins) gave equivalent uniform doses with an expected value close to the values calculated from the cumulative dose distributions in the rectum wall. With the number of patients available in this study the standard deviations of the estimates of the volume parameter were large, and it was not possible to decide which volume gave the best estimates of the volume parameter, but there were distinct differences in the mean values of the values obtained

  15. Zener Diode Compact Model Parameter Extraction Using Xyce-Dakota Optimization.

    Energy Technology Data Exchange (ETDEWEB)

    Buchheit, Thomas E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wilcox, Ian Zachary [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandoval, Andrew J [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Reza, Shahed [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-12-01

    This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction and portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.

  16. Brownian motion model with stochastic parameters for asset prices

    Science.gov (United States)

    Ching, Soo Huei; Hin, Pooi Ah

    2013-09-01

    The Brownian motion model may not be a completely realistic model for asset prices because in real asset prices the drift μ and volatility σ may change over time. Presently we consider a model in which the parameter x = (μ,σ) is such that its value x (t + Δt) at a short time Δt ahead of the present time t depends on the value of the asset price at time t + Δt as well as the present parameter value x(t) and m-1 other parameter values before time t via a conditional distribution. The Malaysian stock prices are used to compare the performance of the Brownian motion model with fixed parameter with that of the model with stochastic parameter.

  17. Study on Parameters Modeling of Wind Turbines Using SCADA Data

    Directory of Open Access Journals (Sweden)

    Yonglong YAN

    2014-08-01

    Full Text Available Taking the advantage of the current massive monitoring data from Supervisory Control and Data Acquisition (SCADA system of wind farm, it is of important significance for anomaly detection, early warning and fault diagnosis to build the data model of state parameters of wind turbines (WTs. The operational conditions and the relationships between the state parameters of wind turbines are complex. It is difficult to establish the model of state parameter accurately, and the modeling method of state parameters of wind turbines considering parameter selection is proposed. Firstly, by analyzing the characteristic of SCADA data, a reasonable range of data and monitoring parameters are chosen. Secondly, neural network algorithm is adapted, and the selection method of input parameters in the model is presented. Generator bearing temperature and cooling air temperature are regarded as target parameters, and the two models are built and input parameters of the models are selected, respectively. Finally, the parameter selection method in this paper and the method using genetic algorithm-partial least square (GA-PLS are analyzed comparatively, and the results show that the proposed methods are correct and effective. Furthermore, the modeling of two parameters illustrate that the method in this paper can applied to other state parameters of wind turbines.

  18. Seven-parameter statistical model for BRDF in the UV band.

    Science.gov (United States)

    Bai, Lu; Wu, Zhensen; Zou, Xiren; Cao, Yunhua

    2012-05-21

    A new semi-empirical seven-parameter BRDF model is developed in the UV band using experimentally measured data. The model is based on the five-parameter model of Wu and the fourteen-parameter model of Renhorn and Boreman. Surface scatter, bulk scatter and retro-reflection scatter are considered. An optimizing modeling method, the artificial immune network genetic algorithm, is used to fit the BRDF measurement data over a wide range of incident angles. The calculation time and accuracy of the five- and seven-parameter models are compared. After fixing the seven parameters, the model can well describe scattering data in the UV band.

  19. A conceptual model for determining career choice of CHROME alumna based on farmer's conceptual models

    Science.gov (United States)

    Moore, Lisa Simmons

    This qualitative program evaluation examines the career decision-making processes and career choices of nine, African American women who participated in the Cooperating Hampton Roads Organization for Minorities in Engineering (CHROME) and who graduated from urban, rural or suburban high schools in the year 2000. The CHROME program is a nonprofit, pre-college intervention program that encourages underrepresented minority and female students to enter science, technically related, engineering, and math (STEM) career fields. The study describes career choices and decisions made by each participant over a five-year period since high school graduation. Data was collected through an Annual Report, Post High School Questionnaires, Environmental Support Questionnaires, Career Choice Questionnaires, Senior Reports, and standardized open-ended interviews. Data was analyzed using a model based on Helen C. Farmer's Conceptual Models, John Ogbu's Caste Theory and Feminist Theory. The CHROME program, based on its stated goals and tenets, was also analyzed against study findings. Findings indicated that participants received very low levels of support from counselors and teachers to pursue STEM careers and high levels of support from parents and family, the CHROME program and financial backing. Findings of this study also indicated that the majority of CHROME alumna persisted in STEM careers. The most successful participants, in terms of undergraduate degree completion and occupational prestige, were the African American women who remained single, experienced no critical incidents, came from a middle class to upper middle class socioeconomic background, and did not have children.

  20. Lumped-parameter Model of a Bucket Foundation

    DEFF Research Database (Denmark)

    Andersen, Lars; Ibsen, Lars Bo; Liingaard, Morten

    2009-01-01

    efficient model that can be applied in aero-elastic codes for fast evaluation of the dynamic structural response of wind turbines. The target solutions, utilised for calibration of the lumped-parameter models, are obtained by a coupled finite-element/boundaryelement scheme in the frequency domain......, and the quality of the models are tested in the time and frequency domains. It is found that precise results are achieved by lumped-parameter models with two to four internal degrees of freedom per displacement or rotation of the foundation. Further, coupling between the horizontal sliding and rocking cannot...

  1. Source term modelling parameters for Project-90

    International Nuclear Information System (INIS)

    Shaw, W.; Smith, G.; Worgan, K.; Hodgkinson, D.; Andersson, K.

    1992-04-01

    This document summarises the input parameters for the source term modelling within Project-90. In the first place, the parameters relate to the CALIBRE near-field code which was developed for the Swedish Nuclear Power Inspectorate's (SKI) Project-90 reference repository safety assessment exercise. An attempt has been made to give best estimate values and, where appropriate, a range which is related to variations around base cases. It should be noted that the data sets contain amendments to those considered by KBS-3. In particular, a completely new set of inventory data has been incorporated. The information given here does not constitute a complete set of parameter values for all parts of the CALIBRE code. Rather, it gives the key parameter values which are used in the constituent models within CALIBRE and the associated studies. For example, the inventory data acts as an input to the calculation of the oxidant production rates, which influence the generation of a redox front. The same data is also an initial value data set for the radionuclide migration component of CALIBRE. Similarly, the geometrical parameters of the near-field are common to both sub-models. The principal common parameters are gathered here for ease of reference and avoidance of unnecessary duplication and transcription errors. (au)

  2. Determinants of choice of delivery place: Testing rational choice theory and habitus theory.

    Science.gov (United States)

    Broda, Anja; Krüger, Juliane; Schinke, Stephanie; Weber, Andreas

    2018-05-07

    The current study uses two antipodal social science theories, the rational choice theory and the habitus theory, and applies these to describe how women choose between intraclinical (i.e., hospital-run birth clinics) and extraclinical (i.e., midwife-led birth centres or home births) delivery places. Data were collected in a cross-sectional questionnaire-based survey among 189 women. A list of 22 determinants, conceptualized to capture the two theoretical concepts, were rated on a 7-point Likert scale with 1 = unimportant to 7 = very important. The analytic method was structural equation modelling. A model was built, in which the rational choice theory and the habitus theory as latent variables predicted the choice of delivery place. With regards to the choice of delivery place, 89.3% of the women wanted an intraclinical and 10.7% an extraclinical delivery place at the time of their last child's birth. Significant differences between women with a choice of an intraclinical or extraclinical delivery place were found for 14 of the 22 determinants. In the structural equation model, rational choice theory determinants predicted a choice of intraclinical delivery and habitus theory determinants predicted a choice of extraclinical delivery. The two theories had diametrically opposed effects on the choice of delivery place. Women are more likely to decide on intraclinical delivery when arguments such as high medical standards, positive evaluations, or good advanced information are rated important. In contrast, women are more likely to decide on extraclinical delivery when factors such as family atmosphere during birth, friendliness of health care professionals, or consideration of the woman's interests are deemed important. A practical implication of our study is that intraclinical deliveries may be promoted by providing comprehensive information, data and facts on various delivery-related issues, while extraclinical deliveries may be fostered by healthcare

  3. Does Correct Answer Distribution Influence Student Choices When Writing Multiple Choice Examinations?

    Science.gov (United States)

    Carnegie, Jacqueline A.

    2017-01-01

    Summative evaluation for large classes of first- and second-year undergraduate courses often involves the use of multiple choice question (MCQ) exams in order to provide timely feedback. Several versions of those exams are often prepared via computer-based question scrambling in an effort to deter cheating. An important parameter to consider when…

  4. The Role of Aspiration Level in Risky Choice: A Comparison of Cumulative Prospect Theory and SP/A Theory.

    Science.gov (United States)

    Lopes; Oden

    1999-06-01

    In recent years, descriptive models of risky choice have incorporated features that reflect the importance of particular outcome values in choice. Cumulative prospect theory (CPT) does this by inserting a reference point in the utility function. SP/A (security-potential/aspiration) theory uses aspiration level as a second criterion in the choice process. Experiment 1 compares the ability of the CPT and SP/A models to account for the same within-subjects data set and finds in favor of SP/A. Experiment 2 replicates the main finding of Experiment 1 in a between-subjects design. The final discussion brackets the SP/A result by showing the impact on fit of both decreasing and increasing the number of free parameters. We also suggest how the SP/A approach might be useful in modeling investment decision making in a descriptively more valid way and conclude with comments on the relation between descriptive and normative theories of risky choice. Copyright 1999 Academic Press.

  5. Tax-Response Heterogeneity and the Effects of Double Taxation Treaties on the Location Choices of Multinational Firms

    OpenAIRE

    Behrendt, Simon; Wamser, Georg

    2018-01-01

    This paper examines location choices of multinational enterprises (MNEs). We particularly focus on the consequences of double taxation treaties (DTTs) and corporate profit taxes on the probability to choose a location. DTTs have become a key policy instrument used by countries to regulate international tax issues related to the cross-border activities of MNEs. Based on three alternative location choice models, which all allow parameter estimates to vary randomly across firms, we show that fir...

  6. Agricultural and Environmental Input Parameters for the Biosphere Model

    Energy Technology Data Exchange (ETDEWEB)

    Kaylie Rasmuson; Kurt Rautenstrauch

    2003-06-20

    This analysis is one of nine technical reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. It documents input parameters for the biosphere model, and supports the use of the model to develop Biosphere Dose Conversion Factors (BDCF). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the repository at Yucca Mountain. The ERMYN provides the TSPA with the capability to perform dose assessments. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships between the major activities and their products (the analysis and model reports) that were planned in the biosphere Technical Work Plan (TWP, BSC 2003a). It should be noted that some documents identified in Figure 1-1 may be under development and therefore not available at the time this document is issued. The ''Biosphere Model Report'' (BSC 2003b) describes the ERMYN and its input parameters. This analysis report, ANL-MGR-MD-000006, ''Agricultural and Environmental Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. This report defines and justifies values for twelve parameters required in the biosphere model. These parameters are related to use of contaminated groundwater to grow crops. The parameter values recommended in this report are used in the soil, plant, and carbon-14 submodels of the ERMYN.

  7. Processing of recognition information and additional cues: A model-based analysis of choice, confidence, and response time

    Directory of Open Access Journals (Sweden)

    Andreas Glockner

    2011-02-01

    Full Text Available Research on the processing of recognition information has focused on testing the recognition heuristic (RH. On the aggregate, the noncompensatory use of recognition information postulated by the RH was rejected in several studies, while RH could still account for a considerable proportion of choices. These results can be explained if either a a part of the subjects used RH or b nobody used it but its choice predictions were accidentally in line with predictions of the strategy used. In the current study, which exemplifies a new approach to model testing, we determined individuals' decision strategies based on a maximum-likelihood classification method, taking into account choices, response times and confidence ratings simultaneously. Unlike most previous studies of the RH, our study tested the RH under conditions in which we provided information about cue values of unrecognized objects (which we argue is fairly common and thus of some interest. For 77.5% of the subjects, overall behavior was best explained by a compensatory parallel constraint satisfaction (PCS strategy. The proportion of subjects using an enhanced RH heuristic (RHe was negligible (up to 7.5%; 15% of the subjects seemed to use a take the best strategy (TTB. A more-fine grained analysis of the supplemental behavioral parameters conditional on strategy use supports PCS but calls into question process assumptions for apparent users of RH, RHe, and TTB within our experimental context. Our results are consistent with previous literature highlighting the importance of individual strategy classification as compared to aggregated analyses.

  8. The mobilisation model and parameter sensitivity

    International Nuclear Information System (INIS)

    Blok, B.M.

    1993-12-01

    In the PRObabillistic Safety Assessment (PROSA) of radioactive waste in a salt repository one of the nuclide release scenario's is the subrosion scenario. A new subrosion model SUBRECN has been developed. In this model the combined effect of a depth-dependent subrosion, glass dissolution, and salt rise has been taken into account. The subrosion model SUBRECN and the implementation of this model in the German computer program EMOS4 is presented. A new computer program PANTER is derived from EMOS4. PANTER models releases of radionuclides via subrosion from a disposal site in a salt pillar into the biosphere. For uncertainty and sensitivity analyses the new subrosion model Latin Hypercube Sampling has been used for determine the different values for the uncertain parameters. The influence of the uncertainty in the parameters on the dose calculations has been investigated by the following sensitivity techniques: Spearman Rank Correlation Coefficients, Partial Rank Correlation Coefficients, Standardised Rank Regression Coefficients, and the Smirnov Test. (orig./HP)

  9. Mutated hilltop inflation: a natural choice for early universe

    International Nuclear Information System (INIS)

    Pal, Barun Kumar; Pal, Supratik; Basu, B.

    2010-01-01

    We propose a model of inflation with a suitable potential for a single scalar field which falls in the wide class of hilltop inflation. We derive the analytical expressions for most of the physical quantities related to inflation and show that all of them represent the true behavior as required from a model of inflation. We further subject the results to observational verification by formulating the theory of perturbations based on our model followed by an estimation for the values of those observable parameters. Our model is found to be in excellent agreement with observational data. Thus, the features related to the model leads us to infer that this type of hilltop inflation may be a natural choice for explaining the early universe

  10. Modeling duration choice in space–time multi-state supernetworks for individual activity-travel scheduling

    NARCIS (Netherlands)

    Liao, F.

    2016-01-01

    Multi-state supernetworks have been advanced recently for modeling individual activity-travel scheduling decisions. The main advantage is that multi-dimensional choice facets are modeled simultaneously within an integral framework, supporting systematic assessments of a large spectrum of policies

  11. Impact of the second semester University Modeling Instruction course on students’ representation choices

    Directory of Open Access Journals (Sweden)

    Daryl McPadden

    2017-11-01

    Full Text Available Representation use is a critical skill for learning, problem solving, and communicating in science, especially in physics where multiple representations often scaffold the understanding of a phenomenon. University Modeling Instruction, which is an active-learning, research-based introductory physics curriculum centered on students’ use of scientific models, has made representation use a primary learning goal with explicit class time devoted to introducing and coordinating representations as part of the model building process. However, because of the semester break, the second semester course, Modeling Instruction-Electricity and Magnetism (MI-EM, contains a mixture of students who are returning from the Modeling Instruction-mechanics course (to whom we refer to as “returning students” and students who are new to Modeling Instruction with the MI-EM course (to whom we refer to as “new students”. In this study, we analyze the impact of MI-EM on students’ representation choices across the introductory physics content for these different groups of students by examining both what individual representations students choose and their average number of representations on a modified card-sort survey with a variety of mechanics and EM questions. Using Wilcoxon-signed-rank tests, Wilcoxon-Mann-Whitney tests, Cliff’s delta effect sizes, and box plots, we compare students’ representation choices from pre- to postsemester, from new and returning students, and from mechanics and EM content. We find that there is a significant difference between returning and new students’ representation choices, which serves as a baseline comparison between Modeling Instruction and traditional lecture-based physics classes. We also find that returning students maintain a high representation use across the MI-EM semester, while new students see significant growth in their representation use regardless of content.

  12. Alterations in choice behavior by manipulations of world model.

    Science.gov (United States)

    Green, C S; Benson, C; Kersten, D; Schrater, P

    2010-09-14

    How to compute initially unknown reward values makes up one of the key problems in reinforcement learning theory, with two basic approaches being used. Model-free algorithms rely on the accumulation of substantial amounts of experience to compute the value of actions, whereas in model-based learning, the agent seeks to learn the generative process for outcomes from which the value of actions can be predicted. Here we show that (i) "probability matching"-a consistent example of suboptimal choice behavior seen in humans-occurs in an optimal Bayesian model-based learner using a max decision rule that is initialized with ecologically plausible, but incorrect beliefs about the generative process for outcomes and (ii) human behavior can be strongly and predictably altered by the presence of cues suggestive of various generative processes, despite statistically identical outcome generation. These results suggest human decision making is rational and model based and not consistent with model-free learning.

  13. Modeling the Choice of Telecommuting Frequency in California: An Exploratory Analysis

    OpenAIRE

    Mannering, Jill S.; Mokhtarian, Patricia L.

    1995-01-01

    This study explores the individual's choice of telecommuting frequency as a function of demographic, travel, work and attitudinal factors. To do this, multinomial logit models are estimated using data collected in a recent survey of employees from three public agencies in California. Separate models are estimated, one for data collected from the Franchise Tax Board in Sacramento, one for data from the Public Utilities Commission in San Francisco, and one for data collected from employees of t...

  14. Multimodal route choice models of public transport passengers in the Greater Copenhagen Area

    DEFF Research Database (Denmark)

    Anderson, Marie Karen; Nielsen, Otto Anker; Prato, Carlo Giacomo

    2014-01-01

    Understanding route choice behavior is crucial to explain travelers’ preferences and to predict traffic flows under different scenarios. A growing body of literature has concentrated on public transport users without, however, concentrating on multimodal public transport networks because......,641 public transport users in the Greater Copenhagen Area.A two-stage approach consisting of choice set generation and route choice model estimation allowed uncovering the preferences of the users of this multimodal large-scale public transport network. The results illustrate the rates of substitution...... not only of the in-vehicle times for different public transport modes, but also of the other time components (e.g., access, walking, waiting, transfer) composing the door-to-door experience of using a multimodal public transport network, differentiating by trip length and purpose, and accounting...

  15. Bayesian estimation of parameters in a regional hydrological model

    Directory of Open Access Journals (Sweden)

    K. Engeland

    2002-01-01

    Full Text Available This study evaluates the applicability of the distributed, process-oriented Ecomag model for prediction of daily streamflow in ungauged basins. The Ecomag model is applied as a regional model to nine catchments in the NOPEX area, using Bayesian statistics to estimate the posterior distribution of the model parameters conditioned on the observed streamflow. The distribution is calculated by Markov Chain Monte Carlo (MCMC analysis. The Bayesian method requires formulation of a likelihood function for the parameters and three alternative formulations are used. The first is a subjectively chosen objective function that describes the goodness of fit between the simulated and observed streamflow, as defined in the GLUE framework. The second and third formulations are more statistically correct likelihood models that describe the simulation errors. The full statistical likelihood model describes the simulation errors as an AR(1 process, whereas the simple model excludes the auto-regressive part. The statistical parameters depend on the catchments and the hydrological processes and the statistical and the hydrological parameters are estimated simultaneously. The results show that the simple likelihood model gives the most robust parameter estimates. The simulation error may be explained to a large extent by the catchment characteristics and climatic conditions, so it is possible to transfer knowledge about them to ungauged catchments. The statistical models for the simulation errors indicate that structural errors in the model are more important than parameter uncertainties. Keywords: regional hydrological model, model uncertainty, Bayesian analysis, Markov Chain Monte Carlo analysis

  16. Prospect theory based estimation of drivers' risk attitudes in route choice behaviors.

    Science.gov (United States)

    Zhou, Lizhen; Zhong, Shiquan; Ma, Shoufeng; Jia, Ning

    2014-12-01

    This paper applied prospect theory (PT) to describe drivers' route choice behavior under Variable Message Sign (VMS), which presented visual traffic information to assist them to make route choice decisions. A quite rich empirical data from questionnaire and field spot was used to estimate parameters of PT. In order to make the parameters more realistic with drivers' attitudes, they were classified into different types by significant factors influencing their behaviors. Based on the travel time distribution of alternative routes and route choice results from questionnaire, the parameterized value function of each category was figured out, which represented drivers' risk attitudes and choice characteristics. The empirical verification showed that the estimates were acceptable and effective. The result showed drivers' risk attitudes and route choice characteristics could be captured by PT under real-time information shown on VMS. For practical application, once drivers' route choice characteristics and parameters were identified, their route choice behavior under different road conditions could be predicted accurately, which was the basis of traffic guidance measures formulation and implementation for targeted traffic management. Moreover, the heterogeneous risk attitudes among drivers should be considered when releasing traffic information and regulating traffic flow. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Models and parameters for environmental radiological assessments

    International Nuclear Information System (INIS)

    Miller, C.W.

    1983-01-01

    This article reviews the forthcoming book Models and Parameters for Environmental Radiological Assessments, which presents a unified compilation of models and parameters for assessing the impact on man of radioactive discharges, both routine and accidental, into the environment. Models presented in this book include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Summaries are presented for each of the transport and dosimetry areas previously for each of the transport and dosimetry areas previously mentioned, and details are available in the literature cited. A chapter of example problems illustrates many of the methodologies presented throughout the text. Models and parameters presented are based on the results of extensive literature reviews and evaluations performed primarily by the staff of the Health and Safety Research Division of Oak Ridge National Laboratory

  18. Choice Rules and Accumulator Networks

    Science.gov (United States)

    2015-01-01

    This article presents a preference accumulation model that can be used to implement a number of different multi-attribute heuristic choice rules, including the lexicographic rule, the majority of confirming dimensions (tallying) rule and the equal weights rule. The proposed model differs from existing accumulators in terms of attribute representation: Leakage and competition, typically applied only to preference accumulation, are also assumed to be involved in processing attribute values. This allows the model to perform a range of sophisticated attribute-wise comparisons, including comparisons that compute relative rank. The ability of a preference accumulation model composed of leaky competitive networks to mimic symbolic models of heuristic choice suggests that these 2 approaches are not incompatible, and that a unitary cognitive model of preferential choice, based on insights from both these approaches, may be feasible. PMID:28670592

  19. Parameter Estimation of Nonlinear Models in Forestry.

    OpenAIRE

    Fekedulegn, Desta; Mac Siúrtáin, Máirtín Pádraig; Colbert, Jim J.

    1999-01-01

    Partial derivatives of the negative exponential, monomolecular, Mitcherlich, Gompertz, logistic, Chapman-Richards, von Bertalanffy, Weibull and the Richard’s nonlinear growth models are presented. The application of these partial derivatives in estimating the model parameters is illustrated. The parameters are estimated using the Marquardt iterative method of nonlinear regression relating top height to age of Norway spruce (Picea abies L.) from the Bowmont Norway Spruce Thinnin...

  20. The sensitivity of ecosystem service models to choices of input data and spatial resolution

    Science.gov (United States)

    Kenneth J. Bagstad; Erika Cohen; Zachary H. Ancona; Steven. G. McNulty; Ge   Sun

    2018-01-01

    Although ecosystem service (ES) modeling has progressed rapidly in the last 10–15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study, we compared the results of different models to address...

  1. Learning about physical parameters: the importance of model discrepancy

    International Nuclear Information System (INIS)

    Brynjarsdóttir, Jenný; O'Hagan, Anthony

    2014-01-01

    Science-based simulation models are widely used to predict the behavior of complex physical systems. It is also common to use observations of the physical system to solve the inverse problem, that is, to learn about the values of parameters within the model, a process which is often called calibration. The main goal of calibration is usually to improve the predictive performance of the simulator but the values of the parameters in the model may also be of intrinsic scientific interest in their own right. In order to make appropriate use of observations of the physical system it is important to recognize model discrepancy, the difference between reality and the simulator output. We illustrate through a simple example that an analysis that does not account for model discrepancy may lead to biased and over-confident parameter estimates and predictions. The challenge with incorporating model discrepancy in statistical inverse problems is being confounded with calibration parameters, which will only be resolved with meaningful priors. For our simple example, we model the model-discrepancy via a Gaussian process and demonstrate that through accounting for model discrepancy our prediction within the range of data is correct. However, only with realistic priors on the model discrepancy do we uncover the true parameter values. Through theoretical arguments we show that these findings are typical of the general problem of learning about physical parameters and the underlying physical system using science-based mechanistic models. (paper)

  2. Obligatory Effort [Hishtadlut] as an Explanatory Model: A Critique of Reproductive Choice and Control.

    Science.gov (United States)

    Teman, Elly; Ivry, Tsipy; Goren, Heela

    2016-06-01

    Studies on reproductive technologies often examine women's reproductive lives in terms of choice and control. Drawing on 48 accounts of procreative experiences of religiously devout Jewish women in Israel and the US, we examine their attitudes, understandings and experiences of pregnancy, reproductive technologies and prenatal testing. We suggest that the concept of hishtadlut-"obligatory effort"-works as an explanatory model that organizes Haredi women's reproductive careers and their negotiations of reproductive technologies. As an elastic category with negotiable and dynamic boundaries, hishtadlut gives ultra-orthodox Jewish women room for effort without the assumption of control; it allows them to exercise discretion in relation to medical issues without framing their efforts in terms of individual choice. Haredi women hold themselves responsible for making their obligatory effort and not for pregnancy outcomes. We suggest that an alternative paradigm to autonomous choice and control emerges from cosmological orders where reproductive duties constitute "obligatory choices."

  3. Wind Farm Decentralized Dynamic Modeling With Parameters

    DEFF Research Database (Denmark)

    Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran

    2010-01-01

    Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...... local models. The results of this report are especially useful, but not limited, to design a decentralized wind farm controller, since in centralized controller design one can also use the model and update it in a central computing node.......Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...

  4. An agent-based simulation model of patient choice of health care providers in accountable care organizations.

    Science.gov (United States)

    Alibrahim, Abdullah; Wu, Shinyi

    2018-03-01

    Accountable care organizations (ACO) in the United States show promise in controlling health care costs while preserving patients' choice of providers. Understanding the effects of patient choice is critical in novel payment and delivery models like ACO that depend on continuity of care and accountability. The financial, utilization, and behavioral implications associated with a patient's decision to forego local health care providers for more distant ones to access higher quality care remain unknown. To study this question, we used an agent-based simulation model of a health care market composed of providers able to form ACO serving patients and embedded it in a conditional logit decision model to examine patients capable of choosing their care providers. This simulation focuses on Medicare beneficiaries and their congestive heart failure (CHF) outcomes. We place the patient agents in an ACO delivery system model in which provider agents decide if they remain in an ACO and perform a quality improving CHF disease management intervention. Illustrative results show that allowing patients to choose their providers reduces the yearly payment per CHF patient by $320, reduces mortality rates by 0.12 percentage points and hospitalization rates by 0.44 percentage points, and marginally increases provider participation in ACO. This study demonstrates a model capable of quantifying the effects of patient choice in a theoretical ACO system and provides a potential tool for policymakers to understand implications of patient choice and assess potential policy controls.

  5. Relationships between models of concurrency

    DEFF Research Database (Denmark)

    Nielsen, Mogens; Sassone, Vladimiro; Winskel, Glynn

    1994-01-01

    Models for concurrency can be classified with respect to the three relevant parameters: behaviour/system, interleaving/noninterleaving, linear/branching time. When modelling a process, a choice concerning such parameters corresponds to choosing the level of abstraction of the resulting semantics....

  6. Optimizing incomplete sample designs for item response model parameters

    NARCIS (Netherlands)

    van der Linden, Willem J.

    Several models for optimizing incomplete sample designs with respect to information on the item parameters are presented. The following cases are considered: (1) known ability parameters; (2) unknown ability parameters; (3) item sets with multiple ability scales; and (4) response models with

  7. High resolution land surface modeling utilizing remote sensing parameters and the Noah-UCM: a case study in the Los Angeles Basin

    Science.gov (United States)

    Vahmani, P.; Hogue, T. S.

    2014-07-01

    In the current work we investigate the utility of remote sensing based surface parameters in the Noah-UCM (urban canopy model) over a highly developed urban area. Landsat and fused Landsat-MODIS data are utilized to generate high resolution (30 m) monthly spatial maps of green vegetation fraction (GVF), impervious surface area (ISA), albedo, leaf area index (LAI), and emissivity in the Los Angeles metropolitan area. The gridded remotely sensed parameter datasets are directly substituted for the land-use/lookup-table values in the Noah-UCM modeling framework. Model performance in reproducing ET (evapotranspiration) and LST (land surface temperature) fields is evaluated utilizing Landsat-based LST and ET estimates from CIMIS (California Irrigation Management Information System) stations as well as in-situ measurements. Our assessment shows that the large deviations between the spatial distributions and seasonal fluctuations of the default and measured parameter sets lead to significant errors in the model predictions of monthly ET fields (RMSE = 22.06 mm month-1). Results indicate that implemented satellite derived parameter maps, particularly GVF, enhance the Noah-UCM capability to reproduce observed ET patterns over vegetated areas in the urban domains (RMSE = 11.77 mm month-1). GVF plays the most significant role in reproducing the observed ET fields, likely due to the interaction with other parameters in the model. Our analysis also shows that remotely sensed GVF and ISA improve the model capability to predict the LST differences between fully vegetated pixels and highly developed areas. However, the model still underestimates remotely sensed LST values over highly developed areas. We hypothesize that the LST underestimation is due to structural formulation in the UCM and cannot be immediately solved with available parameter choices.

  8. Factors that influence beverage choices at meal times. An application of the food choice kaleidoscope framework.

    Science.gov (United States)

    Mueller Loose, S; Jaeger, S R

    2012-12-01

    Beverages are consumed at almost every meal occasion, but knowledge about the factors that influence beverage choice is less than for food choice. The aim of this research was to characterize and quantify factors that influence beverage choices at meal times. Insights into what beverages are chosen by whom, when and where can be helpful for manufacturers, dieticians/health care providers, and health policy makers. A descriptive framework - the food choice kaleidoscope (Jaeger et al., 2011) - was applied to self-reported 24h food recall data from a sample of New Zealand consumers. Participants (n=164) described 8356 meal occasions in terms of foods and beverages consumed, and the contextual characteristics of the occasion. Beverage choice was explored with random-parameter logit regressions to reveal influences linked to food items eaten, context factors and person factors. Thereby this study contributed to the food choice kaleidoscope research approach by expressing the degree of context dependency in the form of odds ratios and according significance levels. The exploration of co-occurrence of beverages with food items suggests that beverage-meal item combinations can be meal specific. Furthermore, this study integrates psychographic variables into the 'person' mirror of the food choice kaleidoscope. A measure of habit in beverage choice was obtained from the inter-participant correlation. Copyright © 2012 Elsevier Ltd. All rights reserved.

  9. Environmental Transport Input Parameters for the Biosphere Model

    International Nuclear Information System (INIS)

    M. Wasiolek

    2004-01-01

    This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573])

  10. Environmental Transport Input Parameters for the Biosphere Model

    Energy Technology Data Exchange (ETDEWEB)

    M. Wasiolek

    2004-09-10

    This analysis report is one of the technical reports documenting the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment for the license application (TSPA-LA) for the geologic repository at Yucca Mountain. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows relationships among the reports developed for biosphere modeling and biosphere abstraction products for the TSPA-LA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (BSC 2004 [DIRS 169573]) (TWP). This figure provides an understanding of how this report contributes to biosphere modeling in support of the license application (LA). This report is one of the five reports that develop input parameter values for the biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the conceptual model and the mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed description of the model input parameters. The output of this report is used as direct input in the ''Nominal Performance Biosphere Dose Conversion Factor Analysis'' and in the ''Disruptive Event Biosphere Dose Conversion Factor Analysis'' that calculate the values of biosphere dose conversion factors (BDCFs) for the groundwater and volcanic ash exposure scenarios, respectively. The purpose of this analysis was to develop biosphere model parameter values related to radionuclide transport and accumulation in the environment. These parameters support calculations of radionuclide concentrations in the environmental media (e.g., soil, crops, animal products, and air) resulting from a given radionuclide concentration at the source of contamination (i.e., either in groundwater or in volcanic ash). The analysis

  11. Parameters and error of a theoretical model

    International Nuclear Information System (INIS)

    Moeller, P.; Nix, J.R.; Swiatecki, W.

    1986-09-01

    We propose a definition for the error of a theoretical model of the type whose parameters are determined from adjustment to experimental data. By applying a standard statistical method, the maximum-likelihoodlmethod, we derive expressions for both the parameters of the theoretical model and its error. We investigate the derived equations by solving them for simulated experimental and theoretical quantities generated by use of random number generators. 2 refs., 4 tabs

  12. Application of multi-parameter chorus and plasmaspheric hiss wave models in radiation belt modeling

    Science.gov (United States)

    Aryan, H.; Kang, S. B.; Balikhin, M. A.; Fok, M. C. H.; Agapitov, O. V.; Komar, C. M.; Kanekal, S. G.; Nagai, T.; Sibeck, D. G.

    2017-12-01

    Numerical simulation studies of the Earth's radiation belts are important to understand the acceleration and loss of energetic electrons. The Comprehensive Inner Magnetosphere-Ionosphere (CIMI) model along with many other radiation belt models require inputs for pitch angle, energy, and cross diffusion of electrons, due to chorus and plasmaspheric hiss waves. These parameters are calculated using statistical wave distribution models of chorus and plasmaspheric hiss amplitudes. In this study we incorporate recently developed multi-parameter chorus and plasmaspheric hiss wave models based on geomagnetic index and solar wind parameters. We perform CIMI simulations for two geomagnetic storms and compare the flux enhancement of MeV electrons with data from the Van Allen Probes and Akebono satellites. We show that the relativistic electron fluxes calculated with multi-parameter wave models resembles the observations more accurately than the relativistic electron fluxes calculated with single-parameter wave models. This indicates that wave models based on a combination of geomagnetic index and solar wind parameters are more effective as inputs to radiation belt models.

  13. Modelling hydrodynamic parameters to predict flow assisted corrosion

    International Nuclear Information System (INIS)

    Poulson, B.; Greenwell, B.; Chexal, B.; Horowitz, J.

    1992-01-01

    During the past 15 years, flow assisted corrosion has been a worldwide problem in the power generating industry. The phenomena is complex and depends on environment, material composition, and hydrodynamic factors. Recently, modeling of flow assisted corrosion has become a subject of great importance. A key part of this effort is modeling the hydrodynamic aspects of this issue. This paper examines which hydrodynamic parameter should be used to correlate the occurrence and rate of flow assisted corrosion with physically meaningful parameters, discusses ways of measuring the relevant hydrodynamic parameter, and describes how the hydrodynamic data is incorporated into the predictive model

  14. Random regret minimization : Exploration of a new choice model for environmental and resource economics

    NARCIS (Netherlands)

    Thiene, M.; Boeri, M.; Chorus, C.G.

    2011-01-01

    This paper introduces the discrete choice model-paradigm of Random Regret Minimization (RRM) to the field of environmental and resource economics. The RRM-approach has been very recently developed in the context of travel demand modelling and presents a tractable, regret-based alternative to the

  15. MFV Reductions of MSSM Parameter Space

    CERN Document Server

    AbdusSalam, S.S.; Quevedo, F.

    2015-01-01

    The 100+ free parameters of the minimal supersymmetric standard model (MSSM) make it computationally difficult to compare systematically with data, motivating the study of specific parameter reductions such as the cMSSM and pMSSM. Here we instead study the reductions of parameter space implied by using minimal flavour violation (MFV) to organise the R-parity conserving MSSM, with a view towards systematically building in constraints on flavour-violating physics. Within this framework the space of parameters is reduced by expanding soft supersymmetry-breaking terms in powers of the Cabibbo angle, leading to a 24-, 30- or 42-parameter framework (which we call MSSM-24, MSSM-30, and MSSM-42 respectively), depending on the order kept in the expansion. We provide a Bayesian global fit to data of the MSSM-30 parameter set to show that this is manageable with current tools. We compare the MFV reductions to the 19-parameter pMSSM choice and show that the pMSSM is not contained as a subset. The MSSM-30 analysis favours...

  16. WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...

    African Journals Online (AJOL)

    Preferred Customer

    Page 1 ... corresponding single-parameter Winkler model presented in this work. Keywords: Heterogeneous subgrade, Reissner's simplified continuum, Shear interaction, Simplified continuum, Winkler ... model in practical applications and its long time familiarity among practical engineers, its usage has endured to this date ...

  17. The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks

    OpenAIRE

    Ratcliff, Roger; McKoon, Gail

    2008-01-01

    The diffusion decision model allows detailed explanations of behavior in two-choice discrimination tasks. In this article, the model is reviewed to show how it translates behavioral data—accuracy, mean response times, and response time distributions—into components of cognitive processing. Three experiments are used to illustrate experimental manipulations of three components: stimulus difficulty affects the quality of information on which a decision is based; instructions emphasizing either ...

  18. Insight into model mechanisms through automatic parameter fitting: a new methodological framework for model development.

    Science.gov (United States)

    Tøndel, Kristin; Niederer, Steven A; Land, Sander; Smith, Nicolas P

    2014-05-20

    Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input-output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard deviation of on

  19. Modelling of intermittent microwave convective drying: parameter sensitivity

    Directory of Open Access Journals (Sweden)

    Zhang Zhijun

    2017-06-01

    Full Text Available The reliability of the predictions of a mathematical model is a prerequisite to its utilization. A multiphase porous media model of intermittent microwave convective drying is developed based on the literature. The model considers the liquid water, gas and solid matrix inside of food. The model is simulated by COMSOL software. Its sensitivity parameter is analysed by changing the parameter values by ±20%, with the exception of several parameters. The sensitivity analysis of the process of the microwave power level shows that each parameter: ambient temperature, effective gas diffusivity, and evaporation rate constant, has significant effects on the process. However, the surface mass, heat transfer coefficient, relative and intrinsic permeability of the gas, and capillary diffusivity of water do not have a considerable effect. The evaporation rate constant has minimal parameter sensitivity with a ±20% value change, until it is changed 10-fold. In all results, the temperature and vapour pressure curves show the same trends as the moisture content curve. However, the water saturation at the medium surface and in the centre show different results. Vapour transfer is the major mass transfer phenomenon that affects the drying process.

  20. Risk preferences impose a hidden distortion on measures of choice impulsivity

    Science.gov (United States)

    Konova, Anna B.; Louie, Kenway; Glimcher, Paul W.

    2018-01-01

    Measuring temporal discounting through the use of intertemporal choice tasks is now the gold standard method for quantifying human choice impulsivity (impatience) in neuroscience, psychology, behavioral economics, public health and computational psychiatry. A recent area of growing interest is individual differences in discounting levels, as these may predispose to (or protect from) mental health disorders, addictive behaviors, and other diseases. At the same time, more and more studies have been dedicated to the quantification of individual attitudes towards risk, which have been measured in many clinical and non-clinical populations using closely related techniques. Economists have pointed to interactions between measurements of time preferences and risk preferences that may distort estimations of the discount rate. However, although becoming standard practice in economics, discount rates and risk preferences are rarely measured simultaneously in the same subjects in other fields, and the magnitude of the imposed distortion is unknown in the assessment of individual differences. Here, we show that standard models of temporal discounting —such as a hyperbolic discounting model widely present in the literature which fails to account for risk attitudes in the estimation of discount rates— result in a large and systematic pattern of bias in estimated discounting parameters. This can lead to the spurious attribution of differences in impulsivity between individuals when in fact differences in risk attitudes account for observed behavioral differences. We advance a model which, when applied to standard choice tasks typically used in psychology and neuroscience, provides both a better fit to the data and successfully de-correlates risk and impulsivity parameters. This results in measures that are more accurate and thus of greater utility to the many fields interested in individual differences in impulsivity. PMID:29373590

  1. Risk preferences impose a hidden distortion on measures of choice impulsivity.

    Directory of Open Access Journals (Sweden)

    Silvia Lopez-Guzman

    Full Text Available Measuring temporal discounting through the use of intertemporal choice tasks is now the gold standard method for quantifying human choice impulsivity (impatience in neuroscience, psychology, behavioral economics, public health and computational psychiatry. A recent area of growing interest is individual differences in discounting levels, as these may predispose to (or protect from mental health disorders, addictive behaviors, and other diseases. At the same time, more and more studies have been dedicated to the quantification of individual attitudes towards risk, which have been measured in many clinical and non-clinical populations using closely related techniques. Economists have pointed to interactions between measurements of time preferences and risk preferences that may distort estimations of the discount rate. However, although becoming standard practice in economics, discount rates and risk preferences are rarely measured simultaneously in the same subjects in other fields, and the magnitude of the imposed distortion is unknown in the assessment of individual differences. Here, we show that standard models of temporal discounting -such as a hyperbolic discounting model widely present in the literature which fails to account for risk attitudes in the estimation of discount rates- result in a large and systematic pattern of bias in estimated discounting parameters. This can lead to the spurious attribution of differences in impulsivity between individuals when in fact differences in risk attitudes account for observed behavioral differences. We advance a model which, when applied to standard choice tasks typically used in psychology and neuroscience, provides both a better fit to the data and successfully de-correlates risk and impulsivity parameters. This results in measures that are more accurate and thus of greater utility to the many fields interested in individual differences in impulsivity.

  2. Risk preferences impose a hidden distortion on measures of choice impulsivity.

    Science.gov (United States)

    Lopez-Guzman, Silvia; Konova, Anna B; Louie, Kenway; Glimcher, Paul W

    2018-01-01

    Measuring temporal discounting through the use of intertemporal choice tasks is now the gold standard method for quantifying human choice impulsivity (impatience) in neuroscience, psychology, behavioral economics, public health and computational psychiatry. A recent area of growing interest is individual differences in discounting levels, as these may predispose to (or protect from) mental health disorders, addictive behaviors, and other diseases. At the same time, more and more studies have been dedicated to the quantification of individual attitudes towards risk, which have been measured in many clinical and non-clinical populations using closely related techniques. Economists have pointed to interactions between measurements of time preferences and risk preferences that may distort estimations of the discount rate. However, although becoming standard practice in economics, discount rates and risk preferences are rarely measured simultaneously in the same subjects in other fields, and the magnitude of the imposed distortion is unknown in the assessment of individual differences. Here, we show that standard models of temporal discounting -such as a hyperbolic discounting model widely present in the literature which fails to account for risk attitudes in the estimation of discount rates- result in a large and systematic pattern of bias in estimated discounting parameters. This can lead to the spurious attribution of differences in impulsivity between individuals when in fact differences in risk attitudes account for observed behavioral differences. We advance a model which, when applied to standard choice tasks typically used in psychology and neuroscience, provides both a better fit to the data and successfully de-correlates risk and impulsivity parameters. This results in measures that are more accurate and thus of greater utility to the many fields interested in individual differences in impulsivity.

  3. Retrospective forecast of ETAS model with daily parameters estimate

    Science.gov (United States)

    Falcone, Giuseppe; Murru, Maura; Console, Rodolfo; Marzocchi, Warner; Zhuang, Jiancang

    2016-04-01

    We present a retrospective ETAS (Epidemic Type of Aftershock Sequence) model based on the daily updating of free parameters during the background, the learning and the test phase of a seismic sequence. The idea was born after the 2011 Tohoku-Oki earthquake. The CSEP (Collaboratory for the Study of Earthquake Predictability) Center in Japan provided an appropriate testing benchmark for the five 1-day submitted models. Of all the models, only one was able to successfully predict the number of events that really happened. This result was verified using both the real time and the revised catalogs. The main cause of the failure was in the underestimation of the forecasted events, due to model parameters maintained fixed during the test. Moreover, the absence in the learning catalog of an event similar to the magnitude of the mainshock (M9.0), which drastically changed the seismicity in the area, made the learning parameters not suitable to describe the real seismicity. As an example of this methodological development we show the evolution of the model parameters during the last two strong seismic sequences in Italy: the 2009 L'Aquila and the 2012 Reggio Emilia episodes. The achievement of the model with daily updated parameters is compared with that of same model where the parameters remain fixed during the test time.

  4. Parameter identification in multinomial processing tree models

    NARCIS (Netherlands)

    Schmittmann, V.D.; Dolan, C.V.; Raijmakers, M.E.J.; Batchelder, W.H.

    2010-01-01

    Multinomial processing tree models form a popular class of statistical models for categorical data that have applications in various areas of psychological research. As in all statistical models, establishing which parameters are identified is necessary for model inference and selection on the basis

  5. Dispersion parameters: impact on calculated reactor accident consequences

    Energy Technology Data Exchange (ETDEWEB)

    Aldrich, D.C.

    1979-01-01

    Much attention has been given in recent years to the modeling of the atmospheric dispersion of pollutants released from a point source. Numerous recommendations have been made concerning the choice of appropriate dispersion parameters. A series of calculations has been performed to determine the impact of these recommendations on the calculated consequences of large reactor accidents. Results are presented and compared in this paper.

  6. A joint model of mode and shipment size choice using the first generation of Commodity Flow Survey Public Use Microdata

    Directory of Open Access Journals (Sweden)

    Monique Stinson

    2017-12-01

    Full Text Available A behavior-based supply chain and freight transportation model was developed and implemented for the Maricopa Association of Governments (MAG and Pima Association of Governments (PAG. This innovative, data-driven modeling system simulates commodity flows to, from and within Phoenix and Tucson Megaregion and is used for regional planning purposes. This paper details the logistics choice component of the system and describes the position and functioning of this component in the overall framework. The logistics choice model uses a nested logit formulation to evaluate mode choice and shipment size jointly. Modeling decisions related to integrating this component within the overall framework are discussed. This paper also describes practical insights gained from using the 2012 Commodity Flow Survey Public Use Microdata (released in 2015, which was the principal data source used to estimate the joint shipment size-mode choice nested logit model. Finally, the validation effort and related lessons learned are described.

  7. On competition in a Stackelberg location-design model with deterministic supplier choice

    NARCIS (Netherlands)

    Hendrix, E.M.T.

    2016-01-01

    We study a market situation where two firms maximize market capture by deciding on the location in the plane and investing in a competing quality against investment cost. Clients choose one of the suppliers; i.e. deterministic supplier choice. To study this situation, a game theoretic model is

  8. Optimal parameters for the FFA-Beddoes dynamic stall model

    Energy Technology Data Exchange (ETDEWEB)

    Bjoerck, A; Mert, M [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden); Madsen, H A [Risoe National Lab., Roskilde (Denmark)

    1999-03-01

    Unsteady aerodynamic effects, like dynamic stall, must be considered in calculation of dynamic forces for wind turbines. Models incorporated in aero-elastic programs are of semi-empirical nature. Resulting aerodynamic forces therefore depend on values used for the semi-empiricial parameters. In this paper a study of finding appropriate parameters to use with the Beddoes-Leishman model is discussed. Minimisation of the `tracking error` between results from 2D wind tunnel tests and simulation with the model is used to find optimum values for the parameters. The resulting optimum parameters show a large variation from case to case. Using these different sets of optimum parameters in the calculation of blade vibrations, give rise to quite different predictions of aerodynamic damping which is discussed. (au)

  9. Multi-level emulation of a volcanic ash transport and dispersion model to quantify sensitivity to uncertain parameters

    Directory of Open Access Journals (Sweden)

    N. J. Harvey

    2018-01-01

    Full Text Available Following the disruption to European airspace caused by the eruption of Eyjafjallajökull in 2010 there has been a move towards producing quantitative predictions of volcanic ash concentration using volcanic ash transport and dispersion simulators. However, there is no formal framework for determining the uncertainties of these predictions and performing many simulations using these complex models is computationally expensive. In this paper a Bayesian linear emulation approach is applied to the Numerical Atmospheric-dispersion Modelling Environment (NAME to better understand the influence of source and internal model parameters on the simulator output. Emulation is a statistical method for predicting the output of a computer simulator at new parameter choices without actually running the simulator. A multi-level emulation approach is applied using two configurations of NAME with different numbers of model particles. Information from many evaluations of the computationally faster configuration is combined with results from relatively few evaluations of the slower, more accurate, configuration. This approach is effective when it is not possible to run the accurate simulator many times and when there is also little prior knowledge about the influence of parameters. The approach is applied to the mean ash column loading in 75 geographical regions on 14 May 2010. Through this analysis it has been found that the parameters that contribute the most to the output uncertainty are initial plume rise height, mass eruption rate, free tropospheric turbulence levels and precipitation threshold for wet deposition. This information can be used to inform future model development and observational campaigns and routine monitoring. The analysis presented here suggests the need for further observational and theoretical research into parameterisation of atmospheric turbulence. Furthermore it can also be used to inform the most important parameter perturbations

  10. Modeling the Joint Choice Decisions on Urban Shopping Destination and Travel-to-Shop Mode: A Comparative Study of Different Structures

    Directory of Open Access Journals (Sweden)

    Chuan Ding

    2014-01-01

    Full Text Available The joint choice of shopping destination and travel-to-shop mode in downtown area is described by making use of the cross-nested logit (CNL model structure that allows for potential interalternative correlation along the both choice dimensions. Meanwhile, the traditional multinomial logit (MNL model and nested logit (NL model are also formulated, respectively. This study uses the data collected in the downtown areas of Maryland-Washington, D.C. region, for shopping trips, considering household, individual, land use, and travel related characteristics. The results of the model reveal the significant influencing factors on joint choice travel behavior between shopping destination and travel mode. A comparison of the different models shows that the proposed CNL model structure offers significant improvements in capturing unobserved correlations between alternatives over MNL model and NL model. Moreover, a Monte Carlo simulation for a group of scenarios assuming that there is an increase in parking fees in downtown area is undertaken to examine the impact of a change in car travel cost on the joint choice of shopping destination and travel mode switching. The results are expected to give a better understanding on the shopping travel behavior.

  11. Transport Choice Modeling for the Evaluation of New Transport Policies

    Directory of Open Access Journals (Sweden)

    Ander Pijoan

    2018-04-01

    Full Text Available Quantifying the impact of the application of sustainable transport policies is essential in order to mitigate effects of greenhouse gas emissions produced by the transport sector. One of the most common approaches used for this purpose is that of traffic modelling and simulation, which consists of emulating the operation of an entire road network. This article presents the results of fitting 8 well known data science methods for transport choice modelling, the area in which more research is needed. The models have been trained with information from Biscay province in Spain in order to match as many of its commuters as possible. Results show that the best models correctly forecast more than 51% of the trips recorded. Finally, the results have been validated with a second data set from the Silesian Voivodeship in Poland, showing that all models indeed maintain their forecasting ability.

  12. Lumped-parameters equivalent circuit for condenser microphones modeling.

    Science.gov (United States)

    Esteves, Josué; Rufer, Libor; Ekeom, Didace; Basrour, Skandar

    2017-10-01

    This work presents a lumped parameters equivalent model of condenser microphone based on analogies between acoustic, mechanical, fluidic, and electrical domains. Parameters of the model were determined mainly through analytical relations and/or finite element method (FEM) simulations. Special attention was paid to the air gap modeling and to the use of proper boundary condition. Corresponding lumped-parameters were obtained as results of FEM simulations. Because of its simplicity, the model allows a fast simulation and is readily usable for microphone design. This work shows the validation of the equivalent circuit on three real cases of capacitive microphones, including both traditional and Micro-Electro-Mechanical Systems structures. In all cases, it has been demonstrated that the sensitivity and other related data obtained from the equivalent circuit are in very good agreement with available measurement data.

  13. Analysis of Modeling Parameters on Threaded Screws.

    Energy Technology Data Exchange (ETDEWEB)

    Vigil, Miquela S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brake, Matthew Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vangoethem, Douglas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-06-01

    Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation prop- erties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connec- tion. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.

  14. Parameter Estimates in Differential Equation Models for Chemical Kinetics

    Science.gov (United States)

    Winkel, Brian

    2011-01-01

    We discuss the need for devoting time in differential equations courses to modelling and the completion of the modelling process with efforts to estimate the parameters in the models using data. We estimate the parameters present in several differential equation models of chemical reactions of order n, where n = 0, 1, 2, and apply more general…

  15. Simultaneous inference for model averaging of derived parameters

    DEFF Research Database (Denmark)

    Jensen, Signe Marie; Ritz, Christian

    2015-01-01

    Model averaging is a useful approach for capturing uncertainty due to model selection. Currently, this uncertainty is often quantified by means of approximations that do not easily extend to simultaneous inference. Moreover, in practice there is a need for both model averaging and simultaneous...... inference for derived parameters calculated in an after-fitting step. We propose a method for obtaining asymptotically correct standard errors for one or several model-averaged estimates of derived parameters and for obtaining simultaneous confidence intervals that asymptotically control the family...

  16. Parameter identification in the logistic STAR model

    DEFF Research Database (Denmark)

    Ekner, Line Elvstrøm; Nejstgaard, Emil

    We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter is that th...

  17. Regionalization of SWAT Model Parameters for Use in Ungauged Watersheds

    Directory of Open Access Journals (Sweden)

    Indrajeet Chaubey

    2010-11-01

    Full Text Available There has been a steady shift towards modeling and model-based approaches as primary methods of assessing watershed response to hydrologic inputs and land management, and of quantifying watershed-wide best management practice (BMP effectiveness. Watershed models often require some degree of calibration and validation to achieve adequate watershed and therefore BMP representation. This is, however, only possible for gauged watersheds. There are many watersheds for which there are very little or no monitoring data available, thus the question as to whether it would be possible to extend and/or generalize model parameters obtained through calibration of gauged watersheds to ungauged watersheds within the same region. This study explored the possibility of developing regionalized model parameter sets for use in ungauged watersheds. The study evaluated two regionalization methods: global averaging, and regression-based parameters, on the SWAT model using data from priority watersheds in Arkansas. Resulting parameters were tested and model performance determined on three gauged watersheds. Nash-Sutcliffe efficiencies (NS for stream flow obtained using regression-based parameters (0.53–0.83 compared well with corresponding values obtained through model calibration (0.45–0.90. Model performance obtained using global averaged parameter values was also generally acceptable (0.4 ≤ NS ≤ 0.75. Results from this study indicate that regionalized parameter sets for the SWAT model can be obtained and used for making satisfactory hydrologic response predictions in ungauged watersheds.

  18. Portfolio Optimization and Mortgage Choice

    Directory of Open Access Journals (Sweden)

    Maj-Britt Nordfang

    2017-01-01

    Full Text Available This paper studies the optimal mortgage choice of an investor in a simple bond market with a stochastic interest rate and access to term life insurance. The study is based on advances in stochastic control theory, which provides analytical solutions to portfolio problems with a stochastic interest rate. We derive the optimal portfolio of a mortgagor in a simple framework and formulate stylized versions of mortgage products offered in the market today. This allows us to analyze the optimal investment strategy in terms of optimal mortgage choice. We conclude that certain extreme investors optimally choose either a traditional fixed rate mortgage or an adjustable rate mortgage, while investors with moderate risk aversion and income prefer a mix of the two. By matching specific investor characteristics to existing mortgage products, our study provides a better understanding of the complex and yet restricted mortgage choice faced by many household investors. In addition, the simple analytical framework enables a detailed analysis of how changes to market, income and preference parameters affect the optimal mortgage choice.

  19. Soil-related Input Parameters for the Biosphere Model

    International Nuclear Information System (INIS)

    A. J. Smith

    2003-01-01

    This analysis is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the geologic repository at Yucca Mountain. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN biosphere model is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003 [163602]). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. ''The Biosphere Model Report'' (BSC 2003 [160699]) describes in detail the conceptual model as well as the mathematical model and its input parameters. The purpose of this analysis was to develop the biosphere model parameters needed to evaluate doses from pathways associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation and ash

  20. Inhalation Exposure Input Parameters for the Biosphere Model

    Energy Technology Data Exchange (ETDEWEB)

    K. Rautenstrauch

    2004-09-10

    This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception.

  1. Inhalation Exposure Input Parameters for the Biosphere Model

    International Nuclear Information System (INIS)

    K. Rautenstrauch

    2004-01-01

    This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception

  2. WHETHER OPEN INNOVATION IS A BETTER CHOICE AS A MODEL OF INNOVATION FOR ORGANIZATIONS?

    OpenAIRE

    KANBUR, AYSUN; A. H. MOHAMED, Ibrahim

    2018-01-01

    This studypresents a review of innovation models and by taking consideration andexamining these models it is aimed to understand whether the model based onopen innovation is a better choice among all the other models. Fororganizations, innovation models generally demonstrate how to work in aninnovative point of view. Companies of today’s business life are striving todevelop their capabilities and their activities to become innovative companies.Many of the organizations try to find the most su...

  3. Building a bridge into the future: dynamic connectionist modeling as an integrative tool for research on intertemporal choice.

    Science.gov (United States)

    Scherbaum, Stefan; Dshemuchadse, Maja; Goschke, Thomas

    2012-01-01

    Temporal discounting denotes the fact that individuals prefer smaller rewards delivered sooner over larger rewards delivered later, often to a higher extent than suggested by normative economical theories. In this article, we identify three lines of research studying this phenomenon which aim (i) to describe temporal discounting mathematically, (ii) to explain observed choice behavior psychologically, and (iii) to predict the influence of specific factors on intertemporal decisions. We then opt for an approach integrating postulated mechanisms and empirical findings from these three lines of research. Our approach focuses on the dynamical properties of decision processes and is based on computational modeling. We present a dynamic connectionist model of intertemporal choice focusing on the role of self-control and time framing as two central factors determining choice behavior. Results of our simulations indicate that the two influences interact with each other, and we present experimental data supporting this prediction. We conclude that computational modeling of the decision process dynamics can advance the integration of different strands of research in intertemporal choice.

  4. Building a bridge into the future: Dynamic connectionist modeling as an integrative tool for research on intertemporal choice

    Directory of Open Access Journals (Sweden)

    Stefan eScherbaum

    2012-11-01

    Full Text Available Temporal discounting denotes the fact that individuals prefer smaller rewards delivered sooner over larger rewards delivered later, often to a higher extent than suggested by normative economical theories. In this article, we identify three lines of research studying this phenomenon which aim (i to describe temporal discounting mathematically, (ii to explain observed choice behavior psychologically, and (iii to predict the influence of specific factors on intertemporal decisions. We then opt for an approach integrating postulated mechanisms and empirical findings from these three lines of research. Our approach focuses on the dynamical properties of decision processes and is based on computational modeling. We present a dynamic connectionist model of intertemporal choice focusing on the role of self-control and time framing as two central factors determining choice behavior. Results of our simulations indicate that the two influences interact with each other, and we present experimental data supporting this prediction. We conclude that computational modeling of the decision process dynamics can advance the integration of different strands of research in intertemporal choice.

  5. Modeling and Parameter Estimation of a Small Wind Generation System

    Directory of Open Access Journals (Sweden)

    Carlos A. Ramírez Gómez

    2013-11-01

    Full Text Available The modeling and parameter estimation of a small wind generation system is presented in this paper. The system consists of a wind turbine, a permanent magnet synchronous generator, a three phase rectifier, and a direct current load. In order to estimate the parameters wind speed data are registered in a weather station located in the Fraternidad Campus at ITM. Wind speed data were applied to a reference model programed with PSIM software. From that simulation, variables were registered to estimate the parameters. The wind generation system model together with the estimated parameters is an excellent representation of the detailed model, but the estimated model offers a higher flexibility than the programed model in PSIM software.

  6. Latent variables and route choice behavior

    DEFF Research Database (Denmark)

    Prato, Carlo Giacomo; Bekhor, Shlomo; Pronello, Cristina

    2012-01-01

    In the last decade, a broad array of disciplines has shown a general interest in enhancing discrete choice models by considering the incorporation of psychological factors affecting decision making. This paper provides insight into the comprehension of the determinants of route choice behavior...... and bound algorithm. A hybrid model consists of measurement equations, which relate latent variables to measurement indicators and utilities to choice indicators, and structural equations, which link travelers’ observable characteristics to latent variables and explanatory variables to utilities. Estimation...

  7. Improving weather predictability by including land-surface model parameter uncertainty

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Pappenberger, Florian

    2016-04-01

    The land surface forms an important component of Earth system models and interacts nonlinearly with other parts such as ocean and atmosphere. To capture the complex and heterogenous hydrology of the land surface, land surface models include a large number of parameters impacting the coupling to other components of the Earth system model. Focusing on ECMWF's land-surface model HTESSEL we present in this study a comprehensive parameter sensitivity evaluation using multiple observational datasets in Europe. We select 6 poorly constrained effective parameters (surface runoff effective depth, skin conductivity, minimum stomatal resistance, maximum interception, soil moisture stress function shape, total soil depth) and explore their sensitivity to model outputs such as soil moisture, evapotranspiration and runoff using uncoupled simulations and coupled seasonal forecasts. Additionally we investigate the possibility to construct ensembles from the multiple land surface parameters. In the uncoupled runs we find that minimum stomatal resistance and total soil depth have the most influence on model performance. Forecast skill scores are moreover sensitive to the same parameters as HTESSEL performance in the uncoupled analysis. We demonstrate the robustness of our findings by comparing multiple best performing parameter sets and multiple randomly chosen parameter sets. We find better temperature and precipitation forecast skill with the best-performing parameter perturbations demonstrating representativeness of model performance across uncoupled (and hence less computationally demanding) and coupled settings. Finally, we construct ensemble forecasts from ensemble members derived with different best-performing parameterizations of HTESSEL. This incorporation of parameter uncertainty in the ensemble generation yields an increase in forecast skill, even beyond the skill of the default system. Orth, R., E. Dutra, and F. Pappenberger, 2016: Improving weather predictability by

  8. Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model

    Science.gov (United States)

    Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Ruget, F.; Gabrielle, B.

    2012-12-01

    Agro-Land Surface Models (agro-LSM) have been developed from the coupling of specific crop models and large-scale generic vegetation models. They aim at accounting for the spatial distribution and variability of energy, water and carbon fluxes within soil-vegetation-atmosphere continuum with a particular emphasis on how crop phenology and agricultural management practice influence the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty in these models is related to the many parameters included in the models' equations. In this study, we quantify the parameter-based uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS on a multi-regional approach with data from sites in Australia, La Reunion and Brazil. First, the main source of uncertainty for the output variables NPP, GPP, and sensible heat flux (SH) is determined through a screening of the main parameters of the model on a multi-site basis leading to the selection of a subset of most sensitive parameters causing most of the uncertainty. In a second step, a sensitivity analysis is carried out on the parameters selected from the screening analysis at a regional scale. For this, a Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used. First, we quantify the sensitivity of the output variables to individual input parameters on a regional scale for two regions of intensive sugar cane cultivation in Australia and Brazil. Then, we quantify the overall uncertainty in the simulation's outputs propagated from the uncertainty in the input parameters. Seven parameters are identified by the screening procedure as driving most of the uncertainty in the agro-LSM ORCHIDEE-STICS model output at all sites. These parameters control photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), root

  9. Methods of equipment choice in shotcreting

    Science.gov (United States)

    Sharapov, R. R.; Yadykina, V. V.; Stepanov, M. A.; Kitukov, B. A.

    2018-03-01

    Shotcrete is widely used in architecture, hydraulic engineering structures, finishing works in tunnels, arc covers and ceilings. The problem of the equipment choice in shotcreting is very important. The main issues influencing the equipment choice are quality improvement and intensification of shotcreting. Main parameters and rational limits of technological characteristic of machines used in solving different problems in shotcreting are described. It is suggested to take into account peculiarities of shotcrete mixing processes and peculiarities of applying these mixtures with compressed air kinetic energy. The described method suggests choosing a mixer with the account of energy capacity, Reynolds number and rotational frequency of the mixing drum. The suggested choice procedure of the equipment nomenclature allows decreasing exploitation costs, increasing the quality of shotcrete and shotcreting in general.

  10. Statistics of Parameter Estimates: A Concrete Example

    KAUST Repository

    Aguilar, Oscar

    2015-01-01

    © 2015 Society for Industrial and Applied Mathematics. Most mathematical models include parameters that need to be determined from measurements. The estimated values of these parameters and their uncertainties depend on assumptions made about noise levels, models, or prior knowledge. But what can we say about the validity of such estimates, and the influence of these assumptions? This paper is concerned with methods to address these questions, and for didactic purposes it is written in the context of a concrete nonlinear parameter estimation problem. We will use the results of a physical experiment conducted by Allmaras et al. at Texas A&M University [M. Allmaras et al., SIAM Rev., 55 (2013), pp. 149-167] to illustrate the importance of validation procedures for statistical parameter estimation. We describe statistical methods and data analysis tools to check the choices of likelihood and prior distributions, and provide examples of how to compare Bayesian results with those obtained by non-Bayesian methods based on different types of assumptions. We explain how different statistical methods can be used in complementary ways to improve the understanding of parameter estimates and their uncertainties.

  11. Spatial scale effects on model parameter estimation and predictive uncertainty in ungauged basins

    CSIR Research Space (South Africa)

    Hughes, DA

    2013-06-01

    Full Text Available . The choice of model structure has been a major topic of discussion throughout the history of hydrological modelling and it is quite rare to find consensus amongst the broad community of model developers and users. With respect to conceptual type models...

  12. Analysis test of understanding of vectors with the three-parameter logistic model of item response theory and item response curves technique

    Directory of Open Access Journals (Sweden)

    Suttida Rakkapao

    2016-10-01

    Full Text Available This study investigated the multiple-choice test of understanding of vectors (TUV, by applying item response theory (IRT. The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming unidimensionality and local independence. Moreover, all distractors of the TUV were analyzed from item response curves (IRC that represent simplified IRT. Data were gathered on 2392 science and engineering freshmen, from three universities in Thailand. The results revealed IRT analysis to be useful in assessing the test since its item parameters are independent of the ability parameters. The IRT framework reveals item-level information, and indicates appropriate ability ranges for the test. Moreover, the IRC analysis can be used to assess the effectiveness of the test’s distractors. Both IRT and IRC approaches reveal test characteristics beyond those revealed by the classical analysis methods of tests. Test developers can apply these methods to diagnose and evaluate the features of items at various ability levels of test takers.

  13. Analysis test of understanding of vectors with the three-parameter logistic model of item response theory and item response curves technique

    Science.gov (United States)

    Rakkapao, Suttida; Prasitpong, Singha; Arayathanitkul, Kwan

    2016-12-01

    This study investigated the multiple-choice test of understanding of vectors (TUV), by applying item response theory (IRT). The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming unidimensionality and local independence. Moreover, all distractors of the TUV were analyzed from item response curves (IRC) that represent simplified IRT. Data were gathered on 2392 science and engineering freshmen, from three universities in Thailand. The results revealed IRT analysis to be useful in assessing the test since its item parameters are independent of the ability parameters. The IRT framework reveals item-level information, and indicates appropriate ability ranges for the test. Moreover, the IRC analysis can be used to assess the effectiveness of the test's distractors. Both IRT and IRC approaches reveal test characteristics beyond those revealed by the classical analysis methods of tests. Test developers can apply these methods to diagnose and evaluate the features of items at various ability levels of test takers.

  14. Hybrid artificial bee colony algorithm for parameter optimization of five-parameter bidirectional reflectance distribution function model.

    Science.gov (United States)

    Wang, Qianqian; Zhao, Jing; Gong, Yong; Hao, Qun; Peng, Zhong

    2017-11-20

    A hybrid artificial bee colony (ABC) algorithm inspired by the best-so-far solution and bacterial chemotaxis was introduced to optimize the parameters of the five-parameter bidirectional reflectance distribution function (BRDF) model. To verify the performance of the hybrid ABC algorithm, we measured BRDF of three kinds of samples and simulated the undetermined parameters of the five-parameter BRDF model using the hybrid ABC algorithm and the genetic algorithm, respectively. The experimental results demonstrate that the hybrid ABC algorithm outperforms the genetic algorithm in convergence speed, accuracy, and time efficiency under the same conditions.

  15. Component Reification in Systems Modelling

    DEFF Research Database (Denmark)

    Bendisposto, Jens; Hallerstede, Stefan

    When modelling concurrent or distributed systems in Event-B, we often obtain models where the structure of the connected components is specified by constants. Their behaviour is specified by the non-deterministic choice of event parameters for events that operate on shared variables. From a certain......? These components may still refer to shared variables. Events of these components should not refer to the constants specifying the structure. The non-deterministic choice between these components should not be via parameters. We say the components are reified. We need to address how the reified components get...... reflected into the original model. This reflection should indicate the constraints on how to connect the components....

  16. Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

    Science.gov (United States)

    Pande, S.; Arkesteijn, L.; Savenije, H.; Bastidas, L. A.

    2015-04-01

    This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting) and its simplified version SIXPAR (Six Parameter Model), are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters) does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.

  17. Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

    Directory of Open Access Journals (Sweden)

    Xiao-meng Song

    2013-01-01

    Full Text Available Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on (1 a screening method (Morris for qualitative ranking of parameters, and (2 a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model (RSMSobol. First, the Morris screening method was used to qualitatively identify the parameters' sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model (RSM were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.

  18. Updating parameters of the chicken processing line model

    DEFF Research Database (Denmark)

    Kurowicka, Dorota; Nauta, Maarten; Jozwiak, Katarzyna

    2010-01-01

    A mathematical model of chicken processing that quantitatively describes the transmission of Campylobacter on chicken carcasses from slaughter to chicken meat product has been developed in Nauta et al. (2005). This model was quantified with expert judgment. Recent availability of data allows...... updating parameters of the model to better describe processes observed in slaughterhouses. We propose Bayesian updating as a suitable technique to update expert judgment with microbiological data. Berrang and Dickens’s data are used to demonstrate performance of this method in updating parameters...... of the chicken processing line model....

  19. Seasonal and spatial variation in broadleaf forest model parameters

    Science.gov (United States)

    Groenendijk, M.; van der Molen, M. K.; Dolman, A. J.

    2009-04-01

    Process based, coupled ecosystem carbon, energy and water cycle models are used with the ultimate goal to project the effect of future climate change on the terrestrial carbon cycle. A typical dilemma in such exercises is how much detail the model must be given to describe the observations reasonably realistic while also be general. We use a simple vegetation model (5PM) with five model parameters to study the variability of the parameters. These parameters are derived from the observed carbon and water fluxes from the FLUXNET database. For 15 broadleaf forests the model parameters were derived for different time resolutions. It appears that in general for all forests, the correlation coefficient between observed and simulated carbon and water fluxes improves with a higher parameter time resolution. The quality of the simulations is thus always better when a higher time resolution is used. These results show that annual parameters are not capable of properly describing weather effects on ecosystem fluxes, and that two day time resolution yields the best results. A first indication of the climate constraints can be found by the seasonal variation of the covariance between Jm, which describes the maximum electron transport for photosynthesis, and climate variables. A general seasonality we found is that during winter the covariance with all climate variables is zero. Jm increases rapidly after initial spring warming, resulting in a large covariance with air temperature and global radiation. During summer Jm is less variable, but co-varies negatively with air temperature and vapour pressure deficit and positively with soil water content. A temperature response appears during spring and autumn for broadleaf forests. This shows that an annual model parameter cannot be representative for the entire year. And relations with mean annual temperature are not possible. During summer the photosynthesis parameters are constrained by water availability, soil water content and

  20. Agent-based modelling of consumer energy choices

    Science.gov (United States)

    Rai, Varun; Henry, Adam Douglas

    2016-06-01

    Strategies to mitigate global climate change should be grounded in a rigorous understanding of energy systems, particularly the factors that drive energy demand. Agent-based modelling (ABM) is a powerful tool for representing the complexities of energy demand, such as social interactions and spatial constraints. Unlike other approaches for modelling energy demand, ABM is not limited to studying perfectly rational agents or to abstracting micro details into system-level equations. Instead, ABM provides the ability to represent behaviours of energy consumers -- such as individual households -- using a range of theories, and to examine how the interaction of heterogeneous agents at the micro-level produces macro outcomes of importance to the global climate, such as the adoption of low-carbon behaviours and technologies over space and time. We provide an overview of ABM work in the area of consumer energy choices, with a focus on identifying specific ways in which ABM can improve understanding of both fundamental scientific and applied aspects of the demand side of energy to aid the design of better policies and programmes. Future research needs for improving the practice of ABM to better understand energy demand are also discussed.

  1. Tough and easy choices

    DEFF Research Database (Denmark)

    Olsen, Søren Bøye; Lundhede, Thomas; Jacobsen, Jette Bredahl

    2011-01-01

    and the best alternative to that. We test this hypothesis using data from two independent Choice Experiments both focusing on nature values. In modelling respondents’ self-reported certainty in choice, we find evidence that the stated level of certainty increases significantly as utility difference in choice......Respondents in Stated Preference studies may be uncertain about their preferences for the good presented to them. Inspired by Wang (J Environ Econ Manag 32:219–232, 1997) we hypothesize that respondents’ stated certainty in choice increases with the utility difference between the alternative chosen...... sets increases. In addition, stated certainty increases with income. Furthermore, there is some evidence that male respondents are inherently more certain in their choices than females, and a learning effect may increase stated certainty. We find evidence of this in the first study where the good...

  2. Temporal variation and scaling of parameters for a monthly hydrologic model

    Science.gov (United States)

    Deng, Chao; Liu, Pan; Wang, Dingbao; Wang, Weiguang

    2018-03-01

    The temporal variation of model parameters is affected by the catchment conditions and has a significant impact on hydrological simulation. This study aims to evaluate the seasonality and downscaling of model parameter across time scales based on monthly and mean annual water balance models with a common model framework. Two parameters of the monthly model, i.e., k and m, are assumed to be time-variant at different months. Based on the hydrological data set from 121 MOPEX catchments in the United States, we firstly analyzed the correlation between parameters (k and m) and catchment properties (NDVI and frequency of rainfall events, α). The results show that parameter k is positively correlated with NDVI or α, while the correlation is opposite for parameter m, indicating that precipitation and vegetation affect monthly water balance by controlling temporal variation of parameters k and m. The multiple linear regression is then used to fit the relationship between ε and the means and coefficient of variations of parameters k and m. Based on the empirical equation and the correlations between the time-variant parameters and NDVI, the mean annual parameter ε is downscaled to monthly k and m. The results show that it has lower NSEs than these from model with time-variant k and m being calibrated through SCE-UA, while for several study catchments, it has higher NSEs than that of the model with constant parameters. The proposed method is feasible and provides a useful tool for temporal scaling of model parameter.

  3. An improved state-parameter analysis of ecosystem models using data assimilation

    Science.gov (United States)

    Chen, M.; Liu, S.; Tieszen, L.L.; Hollinger, D.Y.

    2008-01-01

    Much of the effort spent in developing data assimilation methods for carbon dynamics analysis has focused on estimating optimal values for either model parameters or state variables. The main weakness of estimating parameter values alone (i.e., without considering state variables) is that all errors from input, output, and model structure are attributed to model parameter uncertainties. On the other hand, the accuracy of estimating state variables may be lowered if the temporal evolution of parameter values is not incorporated. This research develops a smoothed ensemble Kalman filter (SEnKF) by combining ensemble Kalman filter with kernel smoothing technique. SEnKF has following characteristics: (1) to estimate simultaneously the model states and parameters through concatenating unknown parameters and state variables into a joint state vector; (2) to mitigate dramatic, sudden changes of parameter values in parameter sampling and parameter evolution process, and control narrowing of parameter variance which results in filter divergence through adjusting smoothing factor in kernel smoothing algorithm; (3) to assimilate recursively data into the model and thus detect possible time variation of parameters; and (4) to address properly various sources of uncertainties stemming from input, output and parameter uncertainties. The SEnKF is tested by assimilating observed fluxes of carbon dioxide and environmental driving factor data from an AmeriFlux forest station located near Howland, Maine, USA, into a partition eddy flux model. Our analysis demonstrates that model parameters, such as light use efficiency, respiration coefficients, minimum and optimum temperatures for photosynthetic activity, and others, are highly constrained by eddy flux data at daily-to-seasonal time scales. The SEnKF stabilizes parameter values quickly regardless of the initial values of the parameters. Potential ecosystem light use efficiency demonstrates a strong seasonality. Results show that the

  4. Choice Model and Influencing Factor Analysis of Travel Mode for Migrant Workers: Case Study in Xi’an, China

    OpenAIRE

    Hong Chen; Zuo-xian Gan; Yu-ting He

    2015-01-01

    Based on the basic theory and methods of disaggregate choice model, the influencing factors in travel mode choice for migrant workers are analyzed, according to 1366 data samples of Xi’an migrant workers. Walking, bus, subway, and taxi are taken as the alternative parts of travel modes for migrant workers, and a multinomial logit (MNL) model of travel mode for migrant workers is set up. The validity of the model is verified by the hit rate, and the hit rates of four travel modes are all great...

  5. Setting Parameters for Biological Models With ANIMO

    NARCIS (Netherlands)

    Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Post, Janine Nicole; van de Pol, Jan Cornelis; Langerak, Romanus; André, Étienne; Frehse, Goran

    2014-01-01

    ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions

  6. Constant-parameter capture-recapture models

    Science.gov (United States)

    Brownie, C.; Hines, J.E.; Nichols, J.D.

    1986-01-01

    Jolly (1982, Biometrics 38, 301-321) presented modifications of the Jolly-Seber model for capture-recapture data, which assume constant survival and/or capture rates. Where appropriate, because of the reduced number of parameters, these models lead to more efficient estimators than the Jolly-Seber model. The tests to compare models given by Jolly do not make complete use of the data, and we present here the appropriate modifications, and also indicate how to carry out goodness-of-fit tests which utilize individual capture history information. We also describe analogous models for the case where young and adult animals are tagged. The availability of computer programs to perform the analysis is noted, and examples are given using output from these programs.

  7. Sensitivity Analysis of WEC Array Layout Parameters Effect on the Power Performance

    DEFF Research Database (Denmark)

    Ruiz, Pau Mercadé; Ferri, Francesco; Kofoed, Jens Peter

    2015-01-01

    This study assesses the effect that the array layout choice has on the power performance. To this end, a sensitivity analysis is carried out with six array layout parameters, as the simulation inputs, the array power performance (q-factor), as the simulation output, and a simulation model special...

  8. Factors that influence beverage choices at meal times

    DEFF Research Database (Denmark)

    Mueller Loose, Simone; Jaeger, S. R.

    2012-01-01

    Beverages are consumed at almost every meal occasion, but knowledge about the factors that influence beverage choice is less than for food choice. The aim of this research was to characterize and quantify factors that influence beverage choices at meal times. Insights into what beverages are chosen...... consumers. Participants (n=164) described 8356 meal occasions in terms of foods and beverages consumed, and the contextual characteristics of the occasion. Beverage choice was explored with random-parameter logit regressions to reveal influences linked to food items eaten, context factors and person factors....... Thereby this study contributed to the food choice kaleidoscope research approach by expressing the degree of context dependency in form of odds ratios and according significance levels. The exploration of co-occurrence of beverages with food items suggests that beverage-meal item combinations can be meal...

  9. Strategy-proof social choice

    OpenAIRE

    Barberà, Salvador, 1946-

    2010-01-01

    This paper surveys the literature on strategy-proofness from a historical perspective. While I discuss the connections with other works on incentives in mechanism design, the main emphasis is on social choice models. This article has been prepared for the Handbook of Social Choice and Welfare, Volume 2, Edited by K. Arrow, A. Sen and K. Suzumura

  10. Ground level enhancement (GLE) energy spectrum parameters model

    Science.gov (United States)

    Qin, G.; Wu, S.

    2017-12-01

    We study the ground level enhancement (GLE) events in solar cycle 23 with the four energy spectra parameters, the normalization parameter C, low-energy power-law slope γ 1, high-energy power-law slope γ 2, and break energy E0, obtained by Mewaldt et al. 2012 who fit the observations to the double power-law equation. we divide the GLEs into two groups, one with strong acceleration by interplanetary (IP) shocks and another one without strong acceleration according to the condition of solar eruptions. We next fit the four parameters with solar event conditions to get models of the parameters for the two groups of GLEs separately. So that we would establish a model of energy spectrum for GLEs for the future space weather prediction.

  11. A discrete-choice model with social interactions : With an application to high school teen behavior

    NARCIS (Netherlands)

    Soetevent, Adriaan R.; Kooreman, Peter

    2007-01-01

    We develop an empirical discrete-choice interaction model with a finite number of agents. We characterize its equilibrium properties-in particular the correspondence between interaction strength, number of agents, and the set of equilibria-and propose to estimate the model by means of simulation

  12. A discrete choice model with social interactions; with an application to high school teen behavior

    NARCIS (Netherlands)

    Soetevent, Adriaan R.; Kooreman, Peter

    2004-01-01

    We develop an empirical discrete choice interaction model with a finite number of agents. We characterize its equilibrium properties - in particular the correspondence between the interaction strength, the number of agents, and the set of equilibria - and propose to estimate the model by means of

  13. A discrete choice model with social interactions; with an application to high school teen behavior

    NARCIS (Netherlands)

    Soetevent, A.R.; Kooreman, P.

    2007-01-01

    We develop an empirical discrete-choice interaction model with a finite number of agents. We characterize its equilibrium properties - in particular the correspondence between interaction strength, number of agents, and the set of equilibria - and propose to estimate the model by means of simulation

  14. Parameter Estimation of Spacecraft Fuel Slosh Model

    Science.gov (United States)

    Gangadharan, Sathya; Sudermann, James; Marlowe, Andrea; Njengam Charles

    2004-01-01

    Fuel slosh in the upper stages of a spinning spacecraft during launch has been a long standing concern for the success of a space mission. Energy loss through the movement of the liquid fuel in the fuel tank affects the gyroscopic stability of the spacecraft and leads to nutation (wobble) which can cause devastating control issues. The rate at which nutation develops (defined by Nutation Time Constant (NTC can be tedious to calculate and largely inaccurate if done during the early stages of spacecraft design. Pure analytical means of predicting the influence of onboard liquids have generally failed. A strong need exists to identify and model the conditions of resonance between nutation motion and liquid modes and to understand the general characteristics of the liquid motion that causes the problem in spinning spacecraft. A 3-D computerized model of the fuel slosh that accounts for any resonant modes found in the experimental testing will allow for increased accuracy in the overall modeling process. Development of a more accurate model of the fuel slosh currently lies in a more generalized 3-D computerized model incorporating masses, springs and dampers. Parameters describing the model include the inertia tensor of the fuel, spring constants, and damper coefficients. Refinement and understanding the effects of these parameters allow for a more accurate simulation of fuel slosh. The current research will focus on developing models of different complexity and estimating the model parameters that will ultimately provide a more realistic prediction of Nutation Time Constant obtained through simulation.

  15. Soil-Related Input Parameters for the Biosphere Model

    International Nuclear Information System (INIS)

    Smith, A. J.

    2004-01-01

    This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure was defined as AP-SIII.9Q, ''Scientific Analyses''. This

  16. Railway and road discrete choice model for foreign trade freight between Antioquia and the Port of Cartagena

    Directory of Open Access Journals (Sweden)

    J. D. Pineda-Jaramillo

    2016-09-01

    Full Text Available Most Colombian freight is transported on roads with barely acceptable conditions, and although there is a speculation about the need for a railway for freight transportation, there is not a study in Colombia showing the variables that influence the modal choice by the companies that generate freight transportation. This article presents the calculation of demand for a hypothetical railway through a discrete choice model. It begins with a qualitative research through focus group techniques to identify the variables that influence the choice of persons responsible for the transportation of large commercial companies in Antioquia (Colombia. The influential variables in the election were the cost and service frequency, and these variables were used to apply a Stated Preference (SP and Revealed Preference (RP survey, then to calibrate a Multinomial Logit Model (MNL, and to estimate the influence of each of them. We show that the probability of railway choice by the studied companies varies between 67% and 93%, depending on differences in these variables.

  17. Honoring Choices Minnesota: preliminary data from a community-wide advance care planning model.

    Science.gov (United States)

    Wilson, Kent S; Kottke, Thomas E; Schettle, Sue

    2014-12-01

    Advance care planning (ACP) increases the likelihood that individuals who are dying receive the care that they prefer. It also reduces depression and anxiety in family members and increases family satisfaction with the process of care. Honoring Choices Minnesota is an ACP program based on the Respecting Choices model of La Crosse, Wisconsin. The objective of this report is to describe the process, which began in 2008, of implementing Honoring Choices Minnesota in a large, diverse metropolitan area. All eight large healthcare systems in the metropolitan area agreed to participate in the project, and as of April 30, 2013, the proportion of hospitalized individuals 65 and older with advance care directives in the electronic medical record was 12.1% to 65.6%. The proportion of outpatients aged 65 and older was 11.6% to 31.7%. Organizations that had sponsored recruitment initiatives had the highest proportions of records containing healthcare directives. It was concluded that it is possible to reduce redundancy by recruiting all healthcare systems in a metropolitan area to endorse the same ACP model, although significantly increasing the proportion of individuals with a healthcare directive in their medical record requires a campaign with recruitment of organizations and individuals. © 2014 The Authors.The Journal of the American Geriatrics Society published by Wiley Periodicals, Inc. on behalf of The American Geriatrics Society.

  18. The influence of low-fare airlines on vacation choices of students : results of a stated portfolio choice experiment

    NARCIS (Netherlands)

    Grigolon, A.B.; Kemperman, A.D.A.M.; Timmermans, H.J.P.

    2012-01-01

    This paper reports the results of a portfolio model of vacation choices of students. The portfolio model concerns the combined choice of destination type, transport mode, duration, accommodation, and travel party for vacations. In addition to usual transport modes such as airline, train, bus and

  19. Worldwide Diversity in Funded Pension Plans : Four Role Models on Choice and Participation

    NARCIS (Netherlands)

    Garcia Huitron, Manuel; Ponds, Eduard

    2015-01-01

    This paper provides an in-depth comparison of funded pension savings plans around the world. The large variety in plan designs is a reflection of historical, cultural and institutional diversity. We postulate a new classification of four role models of funded pension plans, primarily based on choice

  20. On the choice of the driving temperature for eddy-covariance carbon dioxide flux partitioning

    DEFF Research Database (Denmark)

    Lasslop, G.; Migliavacca, M.; Bohrer, G.

    2012-01-01

    be used. This choice is a source of uncertainty and potential biases.In this study, we analysed the correlation between different temperature observations and nighttime NEE (which equals nighttime respiration) across FLUXNET sites to understand the potential of the different temperature observations...... as input for the flux partitioning model. We found that the differences in the correlation between different temperature data streams and nighttime NEE are small and depend on the selection of sites. We investigated the effects of the choice of the temperature data by running two flux partitioning...... parameters was estimated, and the strongest impact was found for the temperature sensitivity. Overall, this study suggests that the choice between soil or air temperature must be made on site-by-site basis by analysing the correlation between temperature and nighttime NEE. We recommend using an ensemble...

  1. Assessment of thermodynamic parameters of plasma shock wave

    International Nuclear Information System (INIS)

    Vasileva, O V; Isaev, Yu N; Budko, A A; Filkov, A I

    2014-01-01

    The work is devoted to the solution of the one-dimensional equation of hydraulic gas dynamics for the coaxial magneto plasma accelerator by means of Lax-Wendroff modified algorithm with optimum choice of the regularization parameter artificial viscosity. Replacement of the differential equations containing private derivatives is made by finite difference method. Optimum parameter of regularization artificial viscosity is added using the exact known decision of Soda problem. The developed algorithm of thermodynamic parameter calculation in a braking point is proved. Thermodynamic parameters of a shock wave in front of the plasma piston of the coaxial magneto plasma accelerator are calculated on the basis of the offered algorithm. Unstable high-frequency fluctuations are smoothed using modeling and that allows narrowing the ambiguity area. Results of calculation of gas dynamic parameters in a point of braking coincide with literary data. The chart 3 shows the dynamics of change of speed and thermodynamic parameters of a shock wave such as pressure, density and temperature just before the plasma piston

  2. Labeled experimental choice design for estimating attribute and availability cross effects with N attributes and specific brand attribute levels

    DEFF Research Database (Denmark)

    Nguyen, Thong Tien

    2011-01-01

    Experimental designs are required in widely used techniques in marketing research, especially for preference-based conjoint analysis and discrete-choice studies. Ideally, marketing researchers prefer orthogonal designs because this technique could give uncorrelated parameter estimates. However, o...... for implementing designs that is efficient enough to estimate model with N brands, each brand have K attributes, and brand attribute has specific levels. The paper also illustrates an example in food consumption study.......Experimental designs are required in widely used techniques in marketing research, especially for preference-based conjoint analysis and discrete-choice studies. Ideally, marketing researchers prefer orthogonal designs because this technique could give uncorrelated parameter estimates. However......, orthogonal design is not available for every situation. Instead, efficient design based on computerized design algorithm is always available. This paper presents the method of efficient design for estimating brand models having attribute and availability cross effects. The paper gives a framework...

  3. Finding viable models in SUSY parameter spaces with signal specific discovery potential

    Science.gov (United States)

    Burgess, Thomas; Lindroos, Jan Øye; Lipniacka, Anna; Sandaker, Heidi

    2013-08-01

    Recent results from ATLAS giving a Higgs mass of 125.5 GeV, further constrain already highly constrained supersymmetric models such as pMSSM or CMSSM/mSUGRA. As a consequence, finding potentially discoverable and non-excluded regions of model parameter space is becoming increasingly difficult. Several groups have invested large effort in studying the consequences of Higgs mass bounds, upper limits on rare B-meson decays, and limits on relic dark matter density on constrained models, aiming at predicting superpartner masses, and establishing likelihood of SUSY models compared to that of the Standard Model vis-á-vis experimental data. In this paper a framework for efficient search for discoverable, non-excluded regions of different SUSY spaces giving specific experimental signature of interest is presented. The method employs an improved Markov Chain Monte Carlo (MCMC) scheme exploiting an iteratively updated likelihood function to guide search for viable models. Existing experimental and theoretical bounds as well as the LHC discovery potential are taken into account. This includes recent bounds on relic dark matter density, the Higgs sector and rare B-mesons decays. A clustering algorithm is applied to classify selected models according to expected phenomenology enabling automated choice of experimental benchmarks and regions to be used for optimizing searches. The aim is to provide experimentalist with a viable tool helping to target experimental signatures to search for, once a class of models of interest is established. As an example a search for viable CMSSM models with τ-lepton signatures observable with the 2012 LHC data set is presented. In the search 105209 unique models were probed. From these, ten reference benchmark points covering different ranges of phenomenological observables at the LHC were selected.

  4. Specialty choice preference of medical students according to personality traits by Five-Factor Model.

    Science.gov (United States)

    Kwon, Oh Young; Park, So Youn

    2016-03-01

    The purpose of this study was to determine the relationship between personality traits, using the Five-Factor Model, and characteristics and motivational factors affecting specialty choice in Korean medical students. A questionnaire survey of Year 4 medical students (n=110) in July 2015 was administered. We evaluated the personality traits of Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness by using the Korean version of Big Five Inventory. Questions about general characteristics, medical specialties most preferred as a career, motivational factors in determining specialty choice were included. Data between five personality traits and general characteristics and motivational factors affecting specialty choice were analyzed using Student t-test, Mann-Whitney test and analysis of variance. Of the 110 eligible medical students, 105 (95.4% response rate) completed the questionnaire. More Agreeableness students preferred clinical medicine to basic medicine (p=0.010) and more Openness students preferred medical departments to others (p=0.031). Personal interest was the significant motivational factors in more Openness students (p=0.003) and Conscientiousness students (p=0.003). Medical students with more Agreeableness were more likely to prefer clinical medicine and those with more Openness preferred medical departments. Personal interest was a significant influential factor determining specialty choice in more Openness and Conscientiousness students. These findings may be helpful to medical educators or career counselors in the specialty choice process.

  5. Specialty choice preference of medical students according to personality traits by Five-Factor Model

    Directory of Open Access Journals (Sweden)

    Oh Young Kwon

    2016-03-01

    Full Text Available Purpose: The purpose of this study was to determine the relationship between personality traits, using the Five-Factor Model, and characteristics and motivational factors affecting specialty choice in Korean medical students. Methods: A questionnaire survey of Year 4 medical students (n=110 in July 2015 was administered. We evaluated the personality traits of Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness by using the Korean version of Big Five Inventory. Questions about general characteristics, medical specialties most preferred as a career, motivational factors in determining specialty choice were included. Data between five personality traits and general characteristics and motivational factors affecting specialty choice were analyzed using Student t-test, Mann-Whitney test and analysis of variance. Results: Of the 110 eligible medical students, 105 (95.4% response rate completed the questionnaire. More Agreeableness students preferred clinical medicine to basic medicine (p=0.010 and more Openness students preferred medical departments to others (p=0.031. Personal interest was the significant motivational factors in more Openness students (p=0.003 and Conscientiousness students (p=0.003. Conclusion: Medical students with more Agreeableness were more likely to prefer clinical medicine and those with more Openness preferred medical departments. Personal interest was a significant influential factor determining specialty choice in more Openness and Conscientiousness students. These findings may be helpful to medical educators or career counselors in the specialty choice process.

  6. Improving the representation of modal choice into bottom-up optimization energy system models - The MoCho-TIMES model

    DEFF Research Database (Denmark)

    Tattini, Jacopo; Ramea, Kalai; Gargiulo, Maurizio

    2018-01-01

    and mathematical expressions required to develop the approach. This study develops MoCho-TIMES in the standalone transportation sector of TIMES-DK, the integrated energy system model for Denmark. The model is tested for the Business as Usual scenario and for four alternative scenarios that imply diverse......This study presents MoCho-TIMES, an original methodology for incorporating modal choice into energy-economy-environment-engineering (E4) system models. MoCho-TIMES addresses the scarce ability of E4 models to realistically depict behaviour in transport and allows for modal shift towards transit...

  7. Parameter estimation in nonlinear models for pesticide degradation

    International Nuclear Information System (INIS)

    Richter, O.; Pestemer, W.; Bunte, D.; Diekkrueger, B.

    1991-01-01

    A wide class of environmental transfer models is formulated as ordinary or partial differential equations. With the availability of fast computers, the numerical solution of large systems became feasible. The main difficulty in performing a realistic and convincing simulation of the fate of a substance in the biosphere is not the implementation of numerical techniques but rather the incomplete data basis for parameter estimation. Parameter estimation is a synonym for statistical and numerical procedures to derive reasonable numerical values for model parameters from data. The classical method is the familiar linear regression technique which dates back to the 18th century. Because it is easy to handle, linear regression has long been established as a convenient tool for analysing relationships. However, the wide use of linear regression has led to an overemphasis of linear relationships. In nature, most relationships are nonlinear and linearization often gives a poor approximation of reality. Furthermore, pure regression models are not capable to map the dynamics of a process. Therefore, realistic models involve the evolution in time (and space). This leads in a natural way to the formulation of differential equations. To establish the link between data and dynamical models, numerical advanced parameter identification methods have been developed in recent years. This paper demonstrates the application of these techniques to estimation problems in the field of pesticide dynamics. (7 refs., 5 figs., 2 tabs.)

  8. Biological parameters for lung cancer in mathematical models of carcinogenesis

    International Nuclear Information System (INIS)

    Jacob, P.; Jacob, V.

    2003-01-01

    Applications of the two-step model of carcinogenesis with clonal expansion (TSCE) to lung cancer data are reviewed, including those on atomic bomb survivors from Hiroshima and Nagasaki, British doctors, Colorado Plateau miners, and Chinese tin miners. Different sets of identifiable model parameters are used in the literature. The parameter set which could be determined with the lowest uncertainty consists of the net proliferation rate gamma of intermediate cells, the hazard h 55 at an intermediate age, and the hazard H? at an asymptotically large age. Also, the values of these three parameters obtained in the various studies are more consistent than other identifiable combinations of the biological parameters. Based on representative results for these three parameters, implications for the biological parameters in the TSCE model are derived. (author)

  9. Human Nonindependent Mate Choice: Is Model Female Attractiveness Everything?

    Directory of Open Access Journals (Sweden)

    Antonios Vakirtzis

    2012-04-01

    Full Text Available Following two decades of research on non-human animals, there has recently been increased interest in human nonindependent mate choice, namely the ways in which choosing women incorporate information about a man's past or present romantic partners (‘model females’ into their own assessment of the male. Experimental studies using static facial images have generally found that men receive higher desirability ratings from female raters when presented with attractive (compared to unattractive model females. This phenomenon has a straightforward evolutionary explanation: the fact that female mate value is more dependent on physical attractiveness compared to male mate value. Furthermore, due to assortative mating for attractiveness, men who are paired with attractive women are more likely to be of high mate value themselves. Here, we also examine the possible relevance of model female cues other than attractiveness (personality and behavioral traits by presenting video recordings of model females to a set of female raters. The results confirm that the model female's attractiveness is the primary cue. Contrary to some earlier findings in the human and nonhuman literature, we found no evidence that female raters prefer partners of slightly older model females. We conclude by suggesting some promising variations on the present experimental design.

  10. Parameter sensitivity and uncertainty analysis for a storm surge and wave model

    Directory of Open Access Journals (Sweden)

    L. A. Bastidas

    2016-09-01

    Full Text Available Development and simulation of synthetic hurricane tracks is a common methodology used to estimate hurricane hazards in the absence of empirical coastal surge and wave observations. Such methods typically rely on numerical models to translate stochastically generated hurricane wind and pressure forcing into coastal surge and wave estimates. The model output uncertainty associated with selection of appropriate model parameters must therefore be addressed. The computational overburden of probabilistic surge hazard estimates is exacerbated by the high dimensionality of numerical surge and wave models. We present a model parameter sensitivity analysis of the Delft3D model for the simulation of hazards posed by Hurricane Bob (1991 utilizing three theoretical wind distributions (NWS23, modified Rankine, and Holland. The sensitive model parameters (of 11 total considered include wind drag, the depth-induced breaking γB, and the bottom roughness. Several parameters show no sensitivity (threshold depth, eddy viscosity, wave triad parameters, and depth-induced breaking αB and can therefore be excluded to reduce the computational overburden of probabilistic surge hazard estimates. The sensitive model parameters also demonstrate a large number of interactions between parameters and a nonlinear model response. While model outputs showed sensitivity to several parameters, the ability of these parameters to act as tuning parameters for calibration is somewhat limited as proper model calibration is strongly reliant on accurate wind and pressure forcing data. A comparison of the model performance with forcings from the different wind models is also presented.

  11. Merging Psychophysical and Psychometric Theory to Estimate Global Visual State Measures from Forced-Choices

    International Nuclear Information System (INIS)

    Massof, Robert W; Schmidt, Karen M; Laby, Daniel M; Kirschen, David; Meadows, David

    2013-01-01

    Visual acuity, a forced-choice psychophysical measure of visual spatial resolution, is the sine qua non of clinical visual impairment testing in ophthalmology and optometry patients with visual system disorders ranging from refractive error to retinal, optic nerve, or central visual system pathology. Visual acuity measures are standardized against a norm, but it is well known that visual acuity depends on a variety of stimulus parameters, including contrast and exposure duration. This paper asks if it is possible to estimate a single global visual state measure from visual acuity measures as a function of stimulus parameters that can represent the patient's overall visual health state with a single variable. Psychophysical theory (at the sensory level) and psychometric theory (at the decision level) are merged to identify the conditions that must be satisfied to derive a global visual state measure from parameterised visual acuity measures. A global visual state measurement model is developed and tested with forced-choice visual acuity measures from 116 subjects with no visual impairments and 560 subjects with uncorrected refractive error. The results are in agreement with the expectations of the model

  12. Calibration of discrete element model parameters: soybeans

    Science.gov (United States)

    Ghodki, Bhupendra M.; Patel, Manish; Namdeo, Rohit; Carpenter, Gopal

    2018-05-01

    Discrete element method (DEM) simulations are broadly used to get an insight of flow characteristics of granular materials in complex particulate systems. DEM input parameters for a model are the critical prerequisite for an efficient simulation. Thus, the present investigation aims to determine DEM input parameters for Hertz-Mindlin model using soybeans as a granular material. To achieve this aim, widely acceptable calibration approach was used having standard box-type apparatus. Further, qualitative and quantitative findings such as particle profile, height of kernels retaining the acrylic wall, and angle of repose of experiments and numerical simulations were compared to get the parameters. The calibrated set of DEM input parameters includes the following (a) material properties: particle geometric mean diameter (6.24 mm); spherical shape; particle density (1220 kg m^{-3} ), and (b) interaction parameters such as particle-particle: coefficient of restitution (0.17); coefficient of static friction (0.26); coefficient of rolling friction (0.08), and particle-wall: coefficient of restitution (0.35); coefficient of static friction (0.30); coefficient of rolling friction (0.08). The results may adequately be used to simulate particle scale mechanics (grain commingling, flow/motion, forces, etc) of soybeans in post-harvest machinery and devices.

  13. Local structural properties and attribute characteristisc in 2-mode networks: p* models to map choices of theater events

    NARCIS (Netherlands)

    Agneessens, F.; Roose, H.

    2008-01-01

    Choices of plays made by theatergoers can be considered as a 2-mode or affiliation network. In this article we illustrate how p* models (an exponential family of distributions for random graphs) can be used to uncover patterns of choices. Based on audience research in three theater institutions in

  14. Regularization parameter selection methods for ill-posed Poisson maximum likelihood estimation

    International Nuclear Information System (INIS)

    Bardsley, Johnathan M; Goldes, John

    2009-01-01

    In image processing applications, image intensity is often measured via the counting of incident photons emitted by the object of interest. In such cases, image data noise is accurately modeled by a Poisson distribution. This motivates the use of Poisson maximum likelihood estimation for image reconstruction. However, when the underlying model equation is ill-posed, regularization is needed. Regularized Poisson likelihood estimation has been studied extensively by the authors, though a problem of high importance remains: the choice of the regularization parameter. We will present three statistically motivated methods for choosing the regularization parameter, and numerical examples will be presented to illustrate their effectiveness

  15. A three-dimensional cohesive sediment transport model with data assimilation: Model development, sensitivity analysis and parameter estimation

    Science.gov (United States)

    Wang, Daosheng; Cao, Anzhou; Zhang, Jicai; Fan, Daidu; Liu, Yongzhi; Zhang, Yue

    2018-06-01

    Based on the theory of inverse problems, a three-dimensional sigma-coordinate cohesive sediment transport model with the adjoint data assimilation is developed. In this model, the physical processes of cohesive sediment transport, including deposition, erosion and advection-diffusion, are parameterized by corresponding model parameters. These parameters are usually poorly known and have traditionally been assigned empirically. By assimilating observations into the model, the model parameters can be estimated using the adjoint method; meanwhile, the data misfit between model results and observations can be decreased. The model developed in this work contains numerous parameters; therefore, it is necessary to investigate the parameter sensitivity of the model, which is assessed by calculating a relative sensitivity function and the gradient of the cost function with respect to each parameter. The results of parameter sensitivity analysis indicate that the model is sensitive to the initial conditions, inflow open boundary conditions, suspended sediment settling velocity and resuspension rate, while the model is insensitive to horizontal and vertical diffusivity coefficients. A detailed explanation of the pattern of sensitivity analysis is also given. In ideal twin experiments, constant parameters are estimated by assimilating 'pseudo' observations. The results show that the sensitive parameters are estimated more easily than the insensitive parameters. The conclusions of this work can provide guidance for the practical applications of this model to simulate sediment transport in the study area.

  16. Age-based differences in strategy use in choice tasks

    Directory of Open Access Journals (Sweden)

    Darrell A. Worthy

    2012-01-01

    Full Text Available We incorporated behavioral and computational modeling techniques to examine age-based differences in strategy use in two four-choice decision-making tasks. Healthy older (aged 60-82 years and younger adults (aged 18-23 years performed one of two decision-making tasks that differed in the degree to which rewards for each option depended on the choices made on previous trials. In the choice-independent task rewards for each choice were not affected by the sequence of previous choices that had been made. In contrast, in the choice-dependent task rewards for each option were based on how often each option had been chosen in the past. We compared the fits of a model that assumes the use of a win-stay-lose-shift (WSLS heuristic to make decisions, to the fits of a reinforcement-learning (RL model that compared expected reward values for each option to make decisions. Younger adults were best fit by the RL model, while older adults showed significantly more evidence of being best fit by the WSLS heuristic model. This led older adults to perform worse than younger adults in the choice-independent task, but better in the choice-dependent task. These results coincide with previous work in our labs that also found better performance for older adults in choice-dependent tasks (Worthy et al., 2011, and the present results suggest that qualitative age-based differences in the strategies used in choice tasks may underlie older adults’ advantage in choice-dependent tasks. We discuss possible factors behind these differences such as neurobiological changes associated with aging, and increased use of heuristics by older adults.

  17. Uncertainty of Modal Parameters Estimated by ARMA Models

    DEFF Research Database (Denmark)

    Jensen, Jacob Laigaard; Brincker, Rune; Rytter, Anders

    1990-01-01

    In this paper the uncertainties of identified modal parameters such as eidenfrequencies and damping ratios are assed. From the measured response of dynamic excited structures the modal parameters may be identified and provide important structural knowledge. However the uncertainty of the parameters...... by simulation study of a lightly damped single degree of freedom system. Identification by ARMA models has been choosen as system identification method. It is concluded that both the sampling interval and number of sampled points may play a significant role with respect to the statistical errors. Furthermore......, it is shown that the model errors may also contribute significantly to the uncertainty....

  18. Effect of model choice and sample size on statistical tolerance limits

    International Nuclear Information System (INIS)

    Duran, B.S.; Campbell, K.

    1980-03-01

    Statistical tolerance limits are estimates of large (or small) quantiles of a distribution, quantities which are very sensitive to the shape of the tail of the distribution. The exact nature of this tail behavior cannot be ascertained brom small samples, so statistical tolerance limits are frequently computed using a statistical model chosen on the basis of theoretical considerations or prior experience with similar populations. This report illustrates the effects of such choices on the computations

  19. Momentous Choices: Testing nonstandard decision models in health and housing markets

    OpenAIRE

    Filko, Martin

    2013-01-01

    markdownabstract__Abstract__ During more than half a century, several strands of research contributed to the development of decision theory. The standard normative model for choice under uncertainty – expected utility – was given a foundation by von Neumann and Morgenstern (1944) and Savage (1954). It advised – and expected – reasonable actors to evaluate the consequences of their actions by the weighted sum of their utility, using probabilities of these consequences as weights. Utilities wer...

  20. Consistent Stochastic Modelling of Meteocean Design Parameters

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Sterndorff, M. J.

    2000-01-01

    Consistent stochastic models of metocean design parameters and their directional dependencies are essential for reliability assessment of offshore structures. In this paper a stochastic model for the annual maximum values of the significant wave height, and the associated wind velocity, current...

  1. Soil-Related Input Parameters for the Biosphere Model

    Energy Technology Data Exchange (ETDEWEB)

    A. J. Smith

    2004-09-09

    This report presents one of the analyses that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN). The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes the details of the conceptual model as well as the mathematical model and the required input parameters. The biosphere model is one of a series of process models supporting the postclosure Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A schematic representation of the documentation flow for the Biosphere input to TSPA is presented in Figure 1-1. This figure shows the evolutionary relationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan for Biosphere Modeling and Expert Support'' (TWP) (BSC 2004 [DIRS 169573]). This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this report. This report, ''Soil-Related Input Parameters for the Biosphere Model'', is one of the five analysis reports that develop input parameters for use in the ERMYN model. This report is the source documentation for the six biosphere parameters identified in Table 1-1. The purpose of this analysis was to develop the biosphere model parameters associated with the accumulation and depletion of radionuclides in the soil. These parameters support the calculation of radionuclide concentrations in soil from on-going irrigation or ash deposition and, as a direct consequence, radionuclide concentration in other environmental media that are affected by radionuclide concentrations in soil. The analysis was performed in accordance with the TWP (BSC 2004 [DIRS 169573]) where the governing procedure

  2. Health Care Facility Choice and User Fee Abolition: Regression Discontinuity in a Multinomial Choice Setting

    OpenAIRE

    Steven F. Koch; Jeffrey S. Racine

    2013-01-01

    We apply parametric and nonparametric regression discontinuity methodology within a multinomial choice setting to examine the impact of public health care user fee abolition on health facility choice using data from South Africa. The nonparametric model is found to outperform the parametric model both in- and out-of-sample, while also delivering more plausible estimates of the impact of user fee abolition (i.e. the 'treatment effect'). In the parametric framework, treatment effects were relat...

  3. Inhalation Exposure Input Parameters for the Biosphere Model

    Energy Technology Data Exchange (ETDEWEB)

    M. Wasiolek

    2006-06-05

    This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This

  4. Inhalation Exposure Input Parameters for the Biosphere Model

    International Nuclear Information System (INIS)

    M. Wasiolek

    2006-01-01

    This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This report is concerned primarily with the

  5. Parameter optimization for surface flux transport models

    Science.gov (United States)

    Whitbread, T.; Yeates, A. R.; Muñoz-Jaramillo, A.; Petrie, G. J. D.

    2017-11-01

    Accurate prediction of solar activity calls for precise calibration of solar cycle models. Consequently we aim to find optimal parameters for models which describe the physical processes on the solar surface, which in turn act as proxies for what occurs in the interior and provide source terms for coronal models. We use a genetic algorithm to optimize surface flux transport models using National Solar Observatory (NSO) magnetogram data for Solar Cycle 23. This is applied to both a 1D model that inserts new magnetic flux in the form of idealized bipolar magnetic regions, and also to a 2D model that assimilates specific shapes of real active regions. The genetic algorithm searches for parameter sets (meridional flow speed and profile, supergranular diffusivity, initial magnetic field, and radial decay time) that produce the best fit between observed and simulated butterfly diagrams, weighted by a latitude-dependent error structure which reflects uncertainty in observations. Due to the easily adaptable nature of the 2D model, the optimization process is repeated for Cycles 21, 22, and 24 in order to analyse cycle-to-cycle variation of the optimal solution. We find that the ranges and optimal solutions for the various regimes are in reasonable agreement with results from the literature, both theoretical and observational. The optimal meridional flow profiles for each regime are almost entirely within observational bounds determined by magnetic feature tracking, with the 2D model being able to accommodate the mean observed profile more successfully. Differences between models appear to be important in deciding values for the diffusive and decay terms. In like fashion, differences in the behaviours of different solar cycles lead to contrasts in parameters defining the meridional flow and initial field strength.

  6. Validating the PVL-Delta model for the Iowa gambling task

    Directory of Open Access Journals (Sweden)

    Helen eSteingroever

    2013-12-01

    Full Text Available Decision-making deficits in clinical populations are often assessed with the Iowa gambling task (IGT. Performance on this task is driven by latent psychological processes, the assessment of which requires an analysis using cognitive models. Two popular examples of such models are the Expectancy Valence (EV and Prospect Valence Learning (PVL models. These models have recently been subjected to sophisticated procedures of model checking, spawning a hybrid version of the EV and PVL models—the PVL-Delta model. In order to test the validity of the PVL-Delta model we present a parameter space partitioning (PSP study and a test of selective influence. The PSP study allows one to assess the choice patterns that the PVL-Delta model generates across its entire parameter space. The PSP study revealed that the model accounts for empirical choice patterns featuring a preference for the good decks or the decks with infrequent losses; however, the model fails to account for empirical choice patterns featuring a preference for the bad decks. The test of selective influence investigates the effectiveness of experimental manipulations designed to target only a single model parameter. This test showed that the manipulations were successful for all but one parameter. To conclude, despite a few shortcomings, the PVL-Delta model seems to be a better IGT model than the popular EV and PVL models.

  7. Task-based assessment of breast tomosynthesis: Effect of acquisition parameters and quantum noise1

    OpenAIRE

    Reiser, I.; Nishikawa, R. M.

    2010-01-01

    Purpose: Tomosynthesis is a promising modality for breast imaging. The appearance of the tomosynthesis reconstructed image is greatly affected by the choice of acquisition and reconstruction parameters. The purpose of this study was to investigate the limitations of tomosynthesis breast imaging due to scan parameters and quantum noise. Tomosynthesis image quality was assessed based on performance of a mathematical observer model in a signal-known exactly (SKE) detection task.

  8. [Mathematical models of decision making and learning].

    Science.gov (United States)

    Ito, Makoto; Doya, Kenji

    2008-07-01

    Computational models of reinforcement learning have recently been applied to analysis of brain imaging and neural recording data to identity neural correlates of specific processes of decision making, such as valuation of action candidates and parameters of value learning. However, for such model-based analysis paradigms, selecting an appropriate model is crucial. In this study we analyze the process of choice learning in rats using stochastic rewards. We show that "Q-learning," which is a standard reinforcement learning algorithm, does not adequately reflect the features of choice behaviors. Thus, we propose a generalized reinforcement learning (GRL) algorithm that incorporates the negative reward effect of reward loss and forgetting of values of actions not chosen. Using the Bayesian estimation method for time-varying parameters, we demonstrated that the GRL algorithm can predict an animal's choice behaviors as efficiently as the best Markov model. The results suggest the usefulness of the GRL for the model-based analysis of neural processes involved in decision making.

  9. The choices, choosing model of quality of life: linkages to a science base.

    Science.gov (United States)

    Gurland, Barry J; Gurland, Roni V

    2009-01-01

    A previous paper began with a critical review of current models and measures of quality of life and then proposed criteria for judging the relative merits of alternative models: preference was given to finding a model with explicit mechanisms, linkages to a science base, a means of identifying deficits amenable to rational restorative interventions, and with embedded values of the whole person. A conjectured model, based on the processes of accessing choices and choosing among them, matched the proposed criteria. The choices and choosing (c-c) process is an evolved adaptive mechanism dedicated to the pursuit of quality of life, driven by specific biological and psychological systems, and influenced also by social and environmental forces. In this paper the c-c model is examined for its potential to strengthen the science base for the field of quality of life and thus to unify many approaches to concept and measurement. A third paper in this set will lay out a guide to applying the c-c model in evaluating impairments of quality of life and will tie this evaluation to corresponding interventions aimed at relieving restrictions or distortions of the c-c process; thus helping people to preserve and improve their quality of life. The fourth paper will demonstrate empirical analyses of the relationship between health imposed restrictions of options for living and conventional indicators of diminished quality of life. (c) 2008 John Wiley & Sons, Ltd.

  10. Joint modeling of constrained path enumeration and path choice behavior: a semi-compensatory approach

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    2010-01-01

    A behavioural and a modelling framework are proposed for representing route choice from a path set that satisfies travellers’ spatiotemporal constraints. Within the proposed framework, travellers’ master sets are constructed by path generation, consideration sets are delimited according to spatio...

  11. A distributed approach for parameters estimation in System Biology models

    International Nuclear Information System (INIS)

    Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.

    2009-01-01

    Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.

  12. Meal patterns, satiety, and food choice in a rat model of Roux-en-Y gastric bypass surgery.

    Science.gov (United States)

    Zheng, Huiyuan; Shin, Andrew C; Lenard, Natalie R; Townsend, R Leigh; Patterson, Laurel M; Sigalet, David L; Berthoud, Hans-Rudolf

    2009-11-01

    Gastric bypass surgery efficiently and lastingly reduces excess body weight and reverses type 2 diabetes in obese patients. Although increased energy expenditure may also play a role, decreased energy intake is thought to be the main reason for weight loss, but the mechanisms involved are poorly understood. Therefore, the aim of this study was to characterize the changes in ingestive behavior in a rat model of Roux-en-Y gastric bypass surgery (RYGB). Obese (24% body fat compared with 18% in chow-fed controls), male Sprague-Dawley rats maintained for 15 wk before and 4 mo after RYGB or sham-surgery on a two-choice low-fat/high-fat diet, were subjected to a series of tests assessing energy intake, meal patterning, and food choice. Although sham-operated rats gained an additional 100 g body wt during the postoperative period, RYGB rats lost approximately 100 g. Intake of a nutritionally complete and palatable liquid diet (Ensure) was significantly reduced by approximately 50% during the first 2 wk after RYGB compared with sham surgery. Decreased intake was the result of greatly reduced meal size with only partial compensation by meal frequency, and a corresponding increase in the satiety ratio. Similar results were obtained with solid food (regular or high-fat chow) 6 wk after surgery. In 12- to 24-h two-choice liquid or solid diet paradigms with nutritionally complete low- and high-fat diets, RYGB rats preferred the low-fat choice (solid) or showed decreased acceptance for the high-fat choice (liquid), whereas sham-operated rats preferred the high-fat choices. A separate group of rats offered chow only before surgery completely avoided the solid high-fat diet in a choice paradigm. The results confirm anecdotal reports of "nibbling" behavior and fat avoidance in RYGB patients and provide a basis for more mechanistic studies in this rat model.

  13. Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

    Science.gov (United States)

    Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami

    2017-06-01

    A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.

  14. Reflector modelization for neutronic diffusion and parameters identification

    International Nuclear Information System (INIS)

    Argaud, J.P.

    1993-04-01

    Physical parameters of neutronic diffusion equations can be adjusted to decrease calculations-measurements errors. The reflector being always difficult to modelize, we choose to elaborate a new reflector model and to use the parameters of this model as adjustment coefficients in the identification procedure. Using theoretical results, and also the physical behaviour of neutronic flux solutions, the reflector model consists then in its replacement by boundary conditions for the diffusion equations on the core only. This theoretical result of non-local operator relations leads then to some discrete approximations by taking into account the multiscaled behaviour, on the core-reflector interface, of neutronic diffusion solutions. The resulting model of this approach is then compared with previous reflector modelizations, and first results indicate that this new model gives the same representation of reflector for the core than previous. (author). 12 refs

  15. Transient dynamic and modeling parameter sensitivity analysis of 1D solid oxide fuel cell model

    International Nuclear Information System (INIS)

    Huangfu, Yigeng; Gao, Fei; Abbas-Turki, Abdeljalil; Bouquain, David; Miraoui, Abdellatif

    2013-01-01

    Highlights: • A multiphysics, 1D, dynamic SOFC model is developed. • The presented model is validated experimentally in eight different operating conditions. • Electrochemical and thermal dynamic transient time expressions are given in explicit forms. • Parameter sensitivity is discussed for different semi-empirical parameters in the model. - Abstract: In this paper, a multiphysics solid oxide fuel cell (SOFC) dynamic model is developed by using a one dimensional (1D) modeling approach. The dynamic effects of double layer capacitance on the electrochemical domain and the dynamic effect of thermal capacity on thermal domain are thoroughly considered. The 1D approach allows the model to predict the non-uniform distributions of current density, gas pressure and temperature in SOFC during its operation. The developed model has been experimentally validated, under different conditions of temperature and gas pressure. Based on the proposed model, the explicit time constant expressions for different dynamic phenomena in SOFC have been given and discussed in detail. A parameters sensitivity study has also been performed and discussed by using statistical Multi Parameter Sensitivity Analysis (MPSA) method, in order to investigate the impact of parameters on the modeling accuracy

  16. Effects of chronic administration of drugs of abuse on impulsive choice (delay discounting) in animal models.

    Science.gov (United States)

    Setlow, Barry; Mendez, Ian A; Mitchell, Marci R; Simon, Nicholas W

    2009-09-01

    Drug-addicted individuals show high levels of impulsive choice, characterized by preference for small immediate over larger but delayed rewards. Although the causal relationship between chronic drug use and elevated impulsive choice in humans has been unclear, a small but growing body of literature over the past decade has shown that chronic drug administration in animal models can cause increases in impulsive choice, suggesting that a similar causal relationship may exist in human drug users. This article reviews this literature, with a particular focus on the effects of chronic cocaine administration, which have been most thoroughly characterized. The potential mechanisms of these effects are described in terms of drug-induced neural alterations in ventral striatal and prefrontal cortical brain systems. Some implications of this research for pharmacological treatment of drug-induced increases in impulsive choice are discussed, along with suggestions for future research in this area.

  17. Coupled 1D-2D hydrodynamic inundation model for sewer overflow: Influence of modeling parameters

    Directory of Open Access Journals (Sweden)

    Adeniyi Ganiyu Adeogun

    2015-10-01

    Full Text Available This paper presents outcome of our investigation on the influence of modeling parameters on 1D-2D hydrodynamic inundation model for sewer overflow, developed through coupling of an existing 1D sewer network model (SWMM and 2D inundation model (BREZO. The 1D-2D hydrodynamic model was developed for the purpose of examining flood incidence due to surcharged water on overland surface. The investigation was carried out by performing sensitivity analysis on the developed model. For the sensitivity analysis, modeling parameters, such as mesh resolution Digital Elevation Model (DEM resolution and roughness were considered. The outcome of the study shows the model is sensitive to changes in these parameters. The performance of the model is significantly influenced, by the Manning's friction value, the DEM resolution and the area of the triangular mesh. Also, changes in the aforementioned modeling parameters influence the Flood characteristics, such as the inundation extent, the flow depth and the velocity across the model domain. Keywords: Inundation, DEM, Sensitivity analysis, Model coupling, Flooding

  18. The symmetry energy {\\boldsymbol{\\gamma }} parameter of relativistic mean-field models

    Science.gov (United States)

    Dutra, Mariana; Lourenço, Odilon; Hen, Or; Piasetzky, Eliezer; Menezes, Débora P.

    2018-05-01

    The relativistic mean-field models tested in previous works against nuclear matter experimental values, critical parameters and macroscopic stellar properties are revisited and used in the evaluation of the symmetry energy γ parameter obtained in three different ways. We have checked that, independent of the choice made to calculate the γ values, a trend of linear correlation is observed between γ and the symmetry energy ({{\\mathscr{S}}}0) and a more clear linear relationship is established between γ and the slope of the symmetry energy (L 0). These results directly contribute to the arising of other linear correlations between γ and the neutron star radii of {R}1.0 and {R}1.4, in agreement with recent findings. Finally, we have found that short-range correlations induce two specific parametrizations, namely, IU-FSU and DD-MEδ, simultaneously compatible with the neutron star mass constraint of 1.93≤slant {M}{{\\max }}/{M}ȯ ≤slant 2.05 and with the overlap band for the {L}0× {{\\mathscr{S}}}0 region, to present γ in the range of γ =0.25+/- 0.05. This work is a part of the project INCT-FNA Proc. No. 464898/2014-5 and was partially supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil under grants 300602/2009-0 and 306786/2014-1. E. P. acknowledges support from the Israel Science Foundation. O. H. acknowledges the U.S. Department of Energy Office of Science, Office of Nuclear Physics program under award number DE-FG02-94ER40818

  19. Modeling Impulse and Non-Impulse Store Choice Processes in a Multi-Agent Simulation of Pedestrian Activity in Shopping Environments

    NARCIS (Netherlands)

    Dijkstra, J.; Timmermans, H.J.P.; Vries, de B.; Timmermans, H.J.P.

    2009-01-01

    This chapter presents a multi-agent approach for modeling impulse and non-impulse store choice processes of pedestrian activity in shopping environments. The pedestrian simulation context will be discussed as well as the behavioral principles underlying the store choice processes. For these

  20. On the validity of evolutionary models with site-specific parameters.

    Directory of Open Access Journals (Sweden)

    Konrad Scheffler

    Full Text Available Evolutionary models that make use of site-specific parameters have recently been criticized on the grounds that parameter estimates obtained under such models can be unreliable and lack theoretical guarantees of convergence. We present a simulation study providing empirical evidence that a simple version of the models in question does exhibit sensible convergence behavior and that additional taxa, despite not being independent of each other, lead to improved parameter estimates. Although it would be desirable to have theoretical guarantees of this, we argue that such guarantees would not be sufficient to justify the use of these models in practice. Instead, we emphasize the importance of taking the variance of parameter estimates into account rather than blindly trusting point estimates - this is standardly done by using the models to construct statistical hypothesis tests, which are then validated empirically via simulation studies.

  1. Sensitivity of simulated regional Arctic climate to the choice of coupled model domain

    Directory of Open Access Journals (Sweden)

    Dmitry V. Sein

    2014-07-01

    Full Text Available The climate over the Arctic has undergone changes in recent decades. In order to evaluate the coupled response of the Arctic system to external and internal forcing, our study focuses on the estimation of regional climate variability and its dependence on large-scale atmospheric and regional ocean circulations. A global ocean–sea ice model with regionally high horizontal resolution is coupled to an atmospheric regional model and global terrestrial hydrology model. This way of coupling divides the global ocean model setup into two different domains: one coupled, where the ocean and the atmosphere are interacting, and one uncoupled, where the ocean model is driven by prescribed atmospheric forcing and runs in a so-called stand-alone mode. Therefore, selecting a specific area for the regional atmosphere implies that the ocean–atmosphere system can develop ‘freely’ in that area, whereas for the rest of the global ocean, the circulation is driven by prescribed atmospheric forcing without any feedbacks. Five different coupled setups are chosen for ensemble simulations. The choice of the coupled domains was done to estimate the influences of the Subtropical Atlantic, Eurasian and North Pacific regions on northern North Atlantic and Arctic climate. Our simulations show that the regional coupled ocean–atmosphere model is sensitive to the choice of the modelled area. The different model configurations reproduce differently both the mean climate and its variability. Only two out of five model setups were able to reproduce the Arctic climate as observed under recent climate conditions (ERA-40 Reanalysis. Evidence is found that the main source of uncertainty for Arctic climate variability and its predictability is the North Pacific. The prescription of North Pacific conditions in the regional model leads to significant correlation with observations, even if the whole North Atlantic is within the coupled model domain. However, the inclusion of the

  2. Error propagation of partial least squares for parameters optimization in NIR modeling

    Science.gov (United States)

    Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

    2018-03-01

    A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models.

  3. Error propagation of partial least squares for parameters optimization in NIR modeling.

    Science.gov (United States)

    Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng

    2018-03-05

    A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models. Copyright © 2017. Published by Elsevier B.V.

  4. Inhalation Exposure Input Parameters for the Biosphere Model

    International Nuclear Information System (INIS)

    M. A. Wasiolek

    2003-01-01

    This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air inhaled by a receptor. Concentrations in air to which the

  5. Parameter Optimisation for the Behaviour of Elastic Models over Time

    DEFF Research Database (Denmark)

    Mosegaard, Jesper

    2004-01-01

    Optimisation of parameters for elastic models is essential for comparison or finding equivalent behaviour of elastic models when parameters cannot simply be transferred or converted. This is the case with a large range of commonly used elastic models. In this paper we present a general method tha...

  6. Choice Shift in Opinion Network Dynamics

    Science.gov (United States)

    Gabbay, Michael

    Choice shift is a phenomenon associated with small group dynamics whereby group discussion causes group members to shift their opinions in a more extreme direction so that the mean post-discussion opinion exceeds the mean pre-discussion opinion. Also known as group polarization, choice shift is a robust experimental phenomenon and has been well-studied within social psychology. In opinion network models, shifts toward extremism are typically produced by the presence of stubborn agents at the extremes of the opinion axis, whose opinions are much more resistant to change than moderate agents. However, we present a model in which choice shift can arise without the assumption of stubborn agents; the model evolves member opinions and uncertainties using coupled nonlinear differential equations. In addition, we briefly describe the results of a recent experiment conducted involving online group discussion concerning the outcome of National Football League games are described. The model predictions concerning the effects of network structure, disagreement level, and team choice (favorite or underdog) are in accord with the experimental results. This research was funded by the Office of Naval Research and the Defense Threat Reduction Agency.

  7. Neural Activity Reveals Preferences Without Choices

    Science.gov (United States)

    Smith, Alec; Bernheim, B. Douglas; Camerer, Colin

    2014-01-01

    We investigate the feasibility of inferring the choices people would make (if given the opportunity) based on their neural responses to the pertinent prospects when they are not engaged in actual decision making. The ability to make such inferences is of potential value when choice data are unavailable, or limited in ways that render standard methods of estimating choice mappings problematic. We formulate prediction models relating choices to “non-choice” neural responses and use them to predict out-of-sample choices for new items and for new groups of individuals. The predictions are sufficiently accurate to establish the feasibility of our approach. PMID:25729468

  8. Bayesian road safety analysis: incorporation of past evidence and effect of hyper-prior choice.

    Science.gov (United States)

    Miranda-Moreno, Luis F; Heydari, Shahram; Lord, Dominique; Fu, Liping

    2013-09-01

    This paper aims to address two related issues when applying hierarchical Bayesian models for road safety analysis, namely: (a) how to incorporate available information from previous studies or past experiences in the (hyper) prior distributions for model parameters and (b) what are the potential benefits of incorporating past evidence on the results of a road safety analysis when working with scarce accident data (i.e., when calibrating models with crash datasets characterized by a very low average number of accidents and a small number of sites). A simulation framework was developed to evaluate the performance of alternative hyper-priors including informative and non-informative Gamma, Pareto, as well as Uniform distributions. Based on this simulation framework, different data scenarios (i.e., number of observations and years of data) were defined and tested using crash data collected at 3-legged rural intersections in California and crash data collected for rural 4-lane highway segments in Texas. This study shows how the accuracy of model parameter estimates (inverse dispersion parameter) is considerably improved when incorporating past evidence, in particular when working with the small number of observations and crash data with low mean. The results also illustrates that when the sample size (more than 100 sites) and the number of years of crash data is relatively large, neither the incorporation of past experience nor the choice of the hyper-prior distribution may affect the final results of a traffic safety analysis. As a potential solution to the problem of low sample mean and small sample size, this paper suggests some practical guidance on how to incorporate past evidence into informative hyper-priors. By combining evidence from past studies and data available, the model parameter estimates can significantly be improved. The effect of prior choice seems to be less important on the hotspot identification. The results show the benefits of incorporating prior

  9. Steam condenser optimization using Real-parameter Genetic Algorithm for Prototype Fast Breeder Reactor

    Energy Technology Data Exchange (ETDEWEB)

    Jayalal, M.L., E-mail: jayalal@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Kumar, L. Satish, E-mail: satish@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Jehadeesan, R., E-mail: jeha@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Rajeswari, S., E-mail: raj@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Satya Murty, S.A.V., E-mail: satya@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Balasubramaniyan, V.; Chetal, S.C. [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India)

    2011-10-15

    Highlights: > We model design optimization of a vital reactor component using Genetic Algorithm. > Real-parameter Genetic Algorithm is used for steam condenser optimization study. > Comparison analysis done with various Genetic Algorithm related mechanisms. > The results obtained are validated with the reference study results. - Abstract: This work explores the use of Real-parameter Genetic Algorithm and analyses its performance in the steam condenser (or Circulating Water System) optimization study of a 500 MW fast breeder nuclear reactor. Choice of optimum design parameters for condenser for a power plant from among a large number of technically viable combination is a complex task. This is primarily due to the conflicting nature of the economic implications of the different system parameters for maximizing the capitalized profit. In order to find the optimum design parameters a Real-parameter Genetic Algorithm model is developed and applied. The results obtained are validated with the reference study results.

  10. Forced-Choice Assessment of Work-Related Maladaptive Personality Traits: Preliminary Evidence From an Application of Thurstonian Item Response Modeling.

    Science.gov (United States)

    Guenole, Nigel; Brown, Anna A; Cooper, Andrew J

    2018-06-01

    This article describes an investigation of whether Thurstonian item response modeling is a viable method for assessment of maladaptive traits. Forced-choice responses from 420 working adults to a broad-range personality inventory assessing six maladaptive traits were considered. The Thurstonian item response model's fit to the forced-choice data was adequate, while the fit of a counterpart item response model to responses to the same items but arranged in a single-stimulus design was poor. Monotrait heteromethod correlations indicated corresponding traits in the two formats overlapped substantially, although they did not measure equivalent constructs. A better goodness of fit and higher factor loadings for the Thurstonian item response model, coupled with a clearer conceptual alignment to the theoretical trait definitions, suggested that the single-stimulus item responses were influenced by biases that the independent clusters measurement model did not account for. Researchers may wish to consider forced-choice designs and appropriate item response modeling techniques such as Thurstonian item response modeling for personality questionnaire applications in industrial psychology, especially when assessing maladaptive traits. We recommend further investigation of this approach in actual selection situations and with different assessment instruments.

  11. Recommended direct simulation Monte Carlo collision model parameters for modeling ionized air transport processes

    Energy Technology Data Exchange (ETDEWEB)

    Swaminathan-Gopalan, Krishnan; Stephani, Kelly A., E-mail: ksteph@illinois.edu [Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States)

    2016-02-15

    A systematic approach for calibrating the direct simulation Monte Carlo (DSMC) collision model parameters to achieve consistency in the transport processes is presented. The DSMC collision cross section model parameters are calibrated for high temperature atmospheric conditions by matching the collision integrals from DSMC against ab initio based collision integrals that are currently employed in the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) and Data Parallel Line Relaxation (DPLR) high temperature computational fluid dynamics solvers. The DSMC parameter values are computed for the widely used Variable Hard Sphere (VHS) and the Variable Soft Sphere (VSS) models using the collision-specific pairing approach. The recommended best-fit VHS/VSS parameter values are provided over a temperature range of 1000-20 000 K for a thirteen-species ionized air mixture. Use of the VSS model is necessary to achieve consistency in transport processes of ionized gases. The agreement of the VSS model transport properties with the transport properties as determined by the ab initio collision integral fits was found to be within 6% in the entire temperature range, regardless of the composition of the mixture. The recommended model parameter values can be readily applied to any gas mixture involving binary collisional interactions between the chemical species presented for the specified temperature range.

  12. DYNAMIC MATHEMATICAL MODEL OF URBAN SPATIAL PATTERN (RESIDENTIAL CHOICE OF LOCATION: MOBILITY VS EXTERNALITY

    Directory of Open Access Journals (Sweden)

    Rahma Fitriani

    2015-01-01

    Full Text Available Household’s residential choice of location determines urban spatial pattern (e.g sprawl. The static model which assumes that the choice has been affected by distance to the CBD and location specific externality, fails to capture the evoution of the pattern over time. Therefore this study proposes a dynamic version of the model. It analyses the effects of externalities on the optimal solution of development decision as function of time. It also derives the effect of mobility and externality on the rate of change of development pattern through time. When the increasing rate of utility is not as significant as the increasing rate of income, the externalities will delay the change of urban spatial pattern over time. If the mobility costs increase by large amount relative to the increase of income and inflation rate, then the mobility effect dominates the effects of externalities in delaying the urban expansion.

  13. Assessment of structural model and parameter uncertainty with a multi-model system for soil water balance models

    Science.gov (United States)

    Michalik, Thomas; Multsch, Sebastian; Frede, Hans-Georg; Breuer, Lutz

    2016-04-01

    Water for agriculture is strongly limited in arid and semi-arid regions and often of low quality in terms of salinity. The application of saline waters for irrigation increases the salt load in the rooting zone and has to be managed by leaching to maintain a healthy soil, i.e. to wash out salts by additional irrigation. Dynamic simulation models are helpful tools to calculate the root zone water fluxes and soil salinity content in order to investigate best management practices. However, there is little information on structural and parameter uncertainty for simulations regarding the water and salt balance of saline irrigation. Hence, we established a multi-model system with four different models (AquaCrop, RZWQM, SWAP, Hydrus1D/UNSATCHEM) to analyze the structural and parameter uncertainty by using the Global Likelihood and Uncertainty Estimation (GLUE) method. Hydrus1D/UNSATCHEM and SWAP were set up with multiple sets of different implemented functions (e.g. matric and osmotic stress for root water uptake) which results in a broad range of different model structures. The simulations were evaluated against soil water and salinity content observations. The posterior distribution of the GLUE analysis gives behavioral parameters sets and reveals uncertainty intervals for parameter uncertainty. Throughout all of the model sets, most parameters accounting for the soil water balance show a low uncertainty, only one or two out of five to six parameters in each model set displays a high uncertainty (e.g. pore-size distribution index in SWAP and Hydrus1D/UNSATCHEM). The differences between the models and model setups reveal the structural uncertainty. The highest structural uncertainty is observed for deep percolation fluxes between the model sets of Hydrus1D/UNSATCHEM (~200 mm) and RZWQM (~500 mm) that are more than twice as high for the latter. The model sets show a high variation in uncertainty intervals for deep percolation as well, with an interquartile range (IQR) of

  14. Testing Ecological Theories of Offender Spatial Decision Making Using a Discrete Choice Model

    Science.gov (United States)

    Summers, Lucia

    2015-01-01

    Research demonstrates that crime is spatially concentrated. However, most research relies on information about where crimes occur, without reference to where offenders reside. This study examines how the characteristics of neighborhoods and their proximity to offender home locations affect offender spatial decision making. Using a discrete choice model and data for detected incidents of theft from vehicles (TFV), we test predictions from two theoretical perspectives—crime pattern and social disorganization theories. We demonstrate that offenders favor areas that are low in social cohesion and closer to their home, or other age-related activity nodes. For adult offenders, choices also appear to be influenced by how accessible a neighborhood is via the street network. The implications for criminological theory and crime prevention are discussed. PMID:25866412

  15. Testing Ecological Theories of Offender Spatial Decision Making Using a Discrete Choice Model.

    Science.gov (United States)

    Johnson, Shane D; Summers, Lucia

    2015-04-01

    Research demonstrates that crime is spatially concentrated. However, most research relies on information about where crimes occur, without reference to where offenders reside. This study examines how the characteristics of neighborhoods and their proximity to offender home locations affect offender spatial decision making. Using a discrete choice model and data for detected incidents of theft from vehicles (TFV) , we test predictions from two theoretical perspectives-crime pattern and social disorganization theories. We demonstrate that offenders favor areas that are low in social cohesion and closer to their home, or other age-related activity nodes. For adult offenders, choices also appear to be influenced by how accessible a neighborhood is via the street network. The implications for criminological theory and crime prevention are discussed.

  16. Sensitivity of inferred climate model skill to evaluation decisions: a case study using CMIP5 evapotranspiration

    International Nuclear Information System (INIS)

    Schwalm, Christopher R; Huntinzger, Deborah N; Michalak, Anna M; Fisher, Joshua B; Kimball, John S; Mueller, Brigitte; Zhang, Ke; Zhang Yongqiang

    2013-01-01

    Confrontation of climate models with observationally-based reference datasets is widespread and integral to model development. These comparisons yield skill metrics quantifying the mismatch between simulated and reference values and also involve analyst choices, or meta-parameters, in structuring the analysis. Here, we systematically vary five such meta-parameters (reference dataset, spatial resolution, regridding approach, land mask, and time period) in evaluating evapotranspiration (ET) from eight CMIP5 models in a factorial design that yields 68 700 intercomparisons. The results show that while model–data comparisons can provide some feedback on overall model performance, model ranks are ambiguous and inferred model skill and rank are highly sensitive to the choice of meta-parameters for all models. This suggests that model skill and rank are best represented probabilistically rather than as scalar values. For this case study, the choice of reference dataset is found to have a dominant influence on inferred model skill, even larger than the choice of model itself. This is primarily due to large differences between reference datasets, indicating that further work in developing a community-accepted standard ET reference dataset is crucial in order to decrease ambiguity in model skill. (letter)

  17. College Students' Choice Modeling of Taking On-Line International Business Courses

    Science.gov (United States)

    Yeh, Robert S.

    2006-01-01

    To understand students' choice behavior of taking on-line international business courses, a survey study is conducted to collect information regarding students' actual choices of taking on-line courses and potential factors that may have impacts on students' choices of online learning. Potential factors such as enrollment status, demographic…

  18. Considerations about the correct evaluation of sorption thermodynamic parameters from equilibrium isotherms

    International Nuclear Information System (INIS)

    Salvestrini, Stefano; Leone, Vincenzo; Iovino, Pasquale; Canzano, Silvana; Capasso, Sante

    2014-01-01

    Highlights: • Different methods to derive sorption thermodynamic parameters have been discussed. • ΔG° and, ΔS° values depend on the selected standard states. • Isosteric heat values help in evaluating the applicability of the sorption models. -- Abstract: This is a comparative analysis of popular methods currently in use to derive sorption thermodynamic parameters from temperature dependence of sorption isotherms. It is emphasized that the standard and isosteric thermodynamic parameters have sharply different meanings. Moreover, it is shown with examples how the sorption model adopted conditions the standard state and consequently the value of ΔG° and ΔS°. These trivial but often neglected aspects should carefully be considered when comparing thermodynamic parameters from different literature sources. An effort by the scientific community is needed to define criteria for the choice of the standard state in sorption processes

  19. Modelling tourists arrival using time varying parameter

    Science.gov (United States)

    Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.

    2017-06-01

    The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.

  20. Evoked emotions predict food choice.

    Science.gov (United States)

    Dalenberg, Jelle R; Gutjar, Swetlana; Ter Horst, Gert J; de Graaf, Kees; Renken, Remco J; Jager, Gerry

    2014-01-01

    In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Therefore, the focus within recent studies shifted towards using emotion-profiling methods that successfully can discriminate between products that are equally liked. However, it is unclear how well scores from emotion-profiling methods predict actual food choice and/or consumption. To test this, we proposed to decompose emotion scores into valence and arousal scores using Principal Component Analysis (PCA) and apply Multinomial Logit Models (MLM) to estimate food choice using liking, valence, and arousal as possible predictors. For this analysis, we used an existing data set comprised of liking and food-evoked emotions scores from 123 participants, who rated 7 unlabeled breakfast drinks. Liking scores were measured using a 100-mm visual analogue scale, while food-evoked emotions were measured using 2 existing emotion-profiling methods: a verbal and a non-verbal method (EsSense Profile and PrEmo, respectively). After 7 days, participants were asked to choose 1 breakfast drink from the experiment to consume during breakfast in a simulated restaurant environment. Cross validation showed that we were able to correctly predict individualized food choice (1 out of 7 products) for over 50% of the participants. This number increased to nearly 80% when looking at the top 2 candidates. Model comparisons showed that evoked emotions better predict food choice than perceived liking alone. However, the strongest predictive strength was achieved by the combination of evoked emotions and liking. Furthermore we showed that non-verbal food-evoked emotion scores more accurately predict food choice than verbal food-evoked emotions scores.

  1. Model parameters estimation and sensitivity by genetic algorithms

    International Nuclear Information System (INIS)

    Marseguerra, Marzio; Zio, Enrico; Podofillini, Luca

    2003-01-01

    In this paper we illustrate the possibility of extracting qualitative information on the importance of the parameters of a model in the course of a Genetic Algorithms (GAs) optimization procedure for the estimation of such parameters. The Genetic Algorithms' search of the optimal solution is performed according to procedures that resemble those of natural selection and genetics: an initial population of alternative solutions evolves within the search space through the four fundamental operations of parent selection, crossover, replacement, and mutation. During the search, the algorithm examines a large amount of solution points which possibly carries relevant information on the underlying model characteristics. A possible utilization of this information amounts to create and update an archive with the set of best solutions found at each generation and then to analyze the evolution of the statistics of the archive along the successive generations. From this analysis one can retrieve information regarding the speed of convergence and stabilization of the different control (decision) variables of the optimization problem. In this work we analyze the evolution strategy followed by a GA in its search for the optimal solution with the aim of extracting information on the importance of the control (decision) variables of the optimization with respect to the sensitivity of the objective function. The study refers to a GA search for optimal estimates of the effective parameters in a lumped nuclear reactor model of literature. The supporting observation is that, as most optimization procedures do, the GA search evolves towards convergence in such a way to stabilize first the most important parameters of the model and later those which influence little the model outputs. In this sense, besides estimating efficiently the parameters values, the optimization approach also allows us to provide a qualitative ranking of their importance in contributing to the model output. The

  2. WATGIS: A GIS-Based Lumped Parameter Water Quality Model

    Science.gov (United States)

    Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

    2002-01-01

    A Geographic Information System (GIS)­based, lumped parameter water quality model was developed to estimate the spatial and temporal nitrogen­loading patterns for lower coastal plain watersheds in eastern North Carolina. The model uses a spatially distributed delivery ratio (DR) parameter to account for nitrogen retention or loss along a drainage network. Delivery...

  3. Money Earlier or Later? Simple Heuristics Explain Intertemporal Choices Better than Delay Discounting1

    Science.gov (United States)

    Marzilli Ericson, Keith M.; White, John Myles; Laibson, David; Cohen, Jonathan D.

    2015-01-01

    Heuristic models have been proposed for many domains of choice. We compare heuristic models of intertemporal choice, which can account for many of the known intertemporal choice anomalies, to discounting models. We conduct an out-of-sample, cross-validated comparison of intertemporal choice models. Heuristic models outperform traditional utility discounting models, including models of exponential and hyperbolic discounting. The best performing models predict choices by using a weighted average of absolute differences and relative (percentage) differences of the attributes of the goods in a choice set. We conclude that heuristic models explain time-money tradeoff choices in experiments better than utility discounting models. PMID:25911124

  4. The effects of nutrition labeling on consumer food choice: a psychological experiment and computational model.

    Science.gov (United States)

    Helfer, Peter; Shultz, Thomas R

    2014-12-01

    The widespread availability of calorie-dense food is believed to be a contributing cause of an epidemic of obesity and associated diseases throughout the world. One possible countermeasure is to empower consumers to make healthier food choices with useful nutrition labeling. An important part of this endeavor is to determine the usability of existing and proposed labeling schemes. Here, we report an experiment on how four different labeling schemes affect the speed and nutritional value of food choices. We then apply decision field theory, a leading computational model of human decision making, to simulate the experimental results. The psychology experiment shows that quantitative, single-attribute labeling schemes have greater usability than multiattribute and binary ones, and that they remain effective under moderate time pressure. The computational model simulates these psychological results and provides explanatory insights into them. This work shows how experimental psychology and computational modeling can contribute to the evaluation and improvement of nutrition-labeling schemes. © 2014 New York Academy of Sciences.

  5. A hybrid discrete choice model to assess the effect of awareness and attitude towards environmentally friendly travel modes

    DEFF Research Database (Denmark)

    Sottile, Eleonora; Meloni, Italo; Cherchi, Elisabetta

    2015-01-01

    The need to reduce private vehicle use has led to the development of soft measures aimed at re-educating car users through information processes that raise their awareness regarding the benefits of environmentally friendly modes, encouraging them to voluntarily change their mode choice behaviour......&R) instead of their car, we estimated a hybrid mode choice model....

  6. NONLINEAR PLANT PIECEWISE-CONTINUOUS MODEL MATRIX PARAMETERS ESTIMATION

    Directory of Open Access Journals (Sweden)

    Roman L. Leibov

    2017-09-01

    Full Text Available This paper presents a nonlinear plant piecewise-continuous model matrix parameters estimation technique using nonlinear model time responses and random search method. One of piecewise-continuous model application areas is defined. The results of proposed approach application for aircraft turbofan engine piecewisecontinuous model formation are presented

  7. Optimized bioregenerative space diet selection with crew choice

    Science.gov (United States)

    Vicens, Carrie; Wang, Carolyn; Olabi, Ammar; Jackson, Peter; Hunter, Jean

    2003-01-01

    Previous studies on optimization of crew diets have not accounted for choice. A diet selection model with crew choice was developed. Scenario analyses were conducted to assess the feasibility and cost of certain crew preferences, such as preferences for numerous-desserts, high-salt, and high-acceptability foods. For comparison purposes, a no-choice and a random-choice scenario were considered. The model was found to be feasible in terms of food variety and overall costs. The numerous-desserts, high-acceptability, and random-choice scenarios all resulted in feasible solutions costing between 13.2 and 17.3 kg ESM/person-day. Only the high-sodium scenario yielded an infeasible solution. This occurred when the foods highest in salt content were selected for the crew-choice portion of the diet. This infeasibility can be avoided by limiting the total sodium content in the crew-choice portion of the diet. Cost savings were found by reducing food variety in scenarios where the preference bias strongly affected nutritional content.

  8. A note on modeling of tumor regression for estimation of radiobiological parameters

    International Nuclear Information System (INIS)

    Zhong, Hualiang; Chetty, Indrin

    2014-01-01

    Purpose: Accurate calculation of radiobiological parameters is crucial to predicting radiation treatment response. Modeling differences may have a significant impact on derived parameters. In this study, the authors have integrated two existing models with kinetic differential equations to formulate a new tumor regression model for estimation of radiobiological parameters for individual patients. Methods: A system of differential equations that characterizes the birth-and-death process of tumor cells in radiation treatment was analytically solved. The solution of this system was used to construct an iterative model (Z-model). The model consists of three parameters: tumor doubling time T d , half-life of dead cells T r , and cell survival fraction SF D under dose D. The Jacobian determinant of this model was proposed as a constraint to optimize the three parameters for six head and neck cancer patients. The derived parameters were compared with those generated from the two existing models: Chvetsov's model (C-model) and Lim's model (L-model). The C-model and L-model were optimized with the parameter T d fixed. Results: With the Jacobian-constrained Z-model, the mean of the optimized cell survival fractions is 0.43 ± 0.08, and the half-life of dead cells averaged over the six patients is 17.5 ± 3.2 days. The parameters T r and SF D optimized with the Z-model differ by 1.2% and 20.3% from those optimized with the T d -fixed C-model, and by 32.1% and 112.3% from those optimized with the T d -fixed L-model, respectively. Conclusions: The Z-model was analytically constructed from the differential equations of cell populations that describe changes in the number of different tumor cells during the course of radiation treatment. The Jacobian constraints were proposed to optimize the three radiobiological parameters. The generated model and its optimization method may help develop high-quality treatment regimens for individual patients

  9. Location choice in the context of multi-day activity-travel patterns : model development and empirical results

    NARCIS (Netherlands)

    Arentze, T.A.; Ettema, D.F.; Timmermans, H.J.P.

    2013-01-01

    Multi-day activity-based models of travel demand are receiving increasing interest recently as successors of existing single-day activity-based models. In this article, we argue that predicting activity location choice-sets can no longer be ignored when multi-day time frames are adopted in these

  10. On the effect of model parameters on forecast objects

    Science.gov (United States)

    Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott

    2018-04-01

    Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.

  11. An automatic and effective parameter optimization method for model tuning

    Directory of Open Access Journals (Sweden)

    T. Zhang

    2015-11-01

    simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.

  12. Electricity investments and nuclear development: investment choice modeling based on value creation

    International Nuclear Information System (INIS)

    Tehrani, B.S.; Bocquer, J.C.; Tomoda, T.

    2014-01-01

    While nuclear power may experience a technological breakthrough in Europe with Generation IV nuclear reactors within 2040, several events could question this possibility such as the Fukushima accident, the climate issues and the electricity market liberalization. This paper aims at analyzing investment choices in power generation capacities in the European scope, using simple DSM-inspired approaches. The power company and interacting stake holders in the investment choice process are considered as a complex system, and dependencies between investment drivers associated with each stake holder are studied. Focusing on the value for the power company, the compatibility of each power company with each of considered technologies is assessed through a Domain Mapping Matrix, including not only technical drivers, but also associated policy and market drivers. Technology preferences are modeled for main European companies in a set of scenarios, these preferences being then used to explore trends in generation mix. (authors)

  13. PRO-ECOLOGICAL ACTIONS AND CONSUMER CHOICES IN THE MODEL OF RESPONSIBLE BUSINESS

    Directory of Open Access Journals (Sweden)

    Katarzyna Olejniczak

    2015-09-01

    Full Text Available The current farming conditions cause that recent social and environmental aspects of management play an important role for the functioning of modern enterprises. This results from the fact that on the one hand the activities of modern enterprises are determined by the surroundings’ increasing complexity, on the other hand the growing demands of various groups of stakeholders build company’s success based not only on a quest to maximize their profi t, but primarily on taking the responsibility for the consequences of their actions. Additionally, the growing awareness of consumers makes more and more enterprises implement the concept of corporate social responsibility (CSR in their actions. For this reason, it is important to discuss about the actions and choices of consumers in the model of CSR. The aim of this article is to present the results of the research on customers‘s environmentally conscious activities and choices.

  14. A Common Mechanism Underlying Food Choice and Social Decisions

    Science.gov (United States)

    Krajbich, Ian; Hare, Todd; Bartling, Björn; Morishima, Yosuke; Fehr, Ernst

    2015-01-01

    People make numerous decisions every day including perceptual decisions such as walking through a crowd, decisions over primary rewards such as what to eat, and social decisions that require balancing own and others’ benefits. The unifying principles behind choices in various domains are, however, still not well understood. Mathematical models that describe choice behavior in specific contexts have provided important insights into the computations that may underlie decision making in the brain. However, a critical and largely unanswered question is whether these models generalize from one choice context to another. Here we show that a model adapted from the perceptual decision-making domain and estimated on choices over food rewards accurately predicts choices and reaction times in four independent sets of subjects making social decisions. The robustness of the model across domains provides behavioral evidence for a common decision-making process in perceptual, primary reward, and social decision making. PMID:26460812

  15. A Common Mechanism Underlying Food Choice and Social Decisions.

    Science.gov (United States)

    Krajbich, Ian; Hare, Todd; Bartling, Björn; Morishima, Yosuke; Fehr, Ernst

    2015-10-01

    People make numerous decisions every day including perceptual decisions such as walking through a crowd, decisions over primary rewards such as what to eat, and social decisions that require balancing own and others' benefits. The unifying principles behind choices in various domains are, however, still not well understood. Mathematical models that describe choice behavior in specific contexts have provided important insights into the computations that may underlie decision making in the brain. However, a critical and largely unanswered question is whether these models generalize from one choice context to another. Here we show that a model adapted from the perceptual decision-making domain and estimated on choices over food rewards accurately predicts choices and reaction times in four independent sets of subjects making social decisions. The robustness of the model across domains provides behavioral evidence for a common decision-making process in perceptual, primary reward, and social decision making.

  16. Modeling a Multinomial Logit Model of Intercity Travel Mode Choice Behavior for All Trips in Libya

    OpenAIRE

    Manssour A. Abdulsalam Bin Miskeen; Ahmed Mohamed Alhodairi; Riza Atiq Abdullah Bin O. K. Rahmat

    2013-01-01

    In the planning point of view, it is essential to have mode choice, due to the massive amount of incurred in transportation systems. The intercity travellers in Libya have distinct features, as against travellers from other countries, which includes cultural and socioeconomic factors. Consequently, the goal of this study is to recognize the behavior of intercity travel using disaggregate models, for projecting the demand of nation-level intercity travel in Libya. Multinom...

  17. A compact cyclic plasticity model with parameter evolution

    DEFF Research Database (Denmark)

    Krenk, Steen; Tidemann, L.

    2017-01-01

    The paper presents a compact model for cyclic plasticity based on energy in terms of external and internal variables, and plastic yielding described by kinematic hardening and a flow potential with an additive term controlling the nonlinear cyclic hardening. The model is basically described by five...... parameters: external and internal stiffness, a yield stress and a limiting ultimate stress, and finally a parameter controlling the gradual development of plastic deformation. Calibration against numerous experimental results indicates that typically larger plastic strains develop than predicted...

  18. Luminescence model with quantum impact parameter for low energy ions

    CERN Document Server

    Cruz-Galindo, H S; Martínez-Davalos, A; Belmont-Moreno, E; Galindo, S

    2002-01-01

    We have modified an analytical model of induced light production by energetic ions interacting in scintillating materials. The original model is based on the distribution of energy deposited by secondary electrons produced along the ion's track. The range of scattered electrons, and thus the energy distribution, depends on a classical impact parameter between the electron and the ion's track. The only adjustable parameter of the model is the quenching density rho sub q. The modification here presented, consists in proposing a quantum impact parameter that leads to a better fit of the model to the experimental data at low incident ion energies. The light output response of CsI(Tl) detectors to low energy ions (<3 MeV/A) is fitted with the modified model and comparison is made to the original model.

  19. Occupational choice and values.

    OpenAIRE

    Kantas, A.

    1985-01-01

    It is suggested that psychological and sociological approaches to occupational choice can be linked together by employment of three concepts: work salience, values and motivation. Employing Vroom's (1964) cognitive model of motivation occupational choice was examined as a value attainment process. The subjects were 225 male pupils of two different school complexes in Athens, Greece. They were asked to respond to a work salience questionnaire and to rank order a set of ...

  20. What counts as a choice? U.S. Americans are more likely than Indians to construe actions as choices.

    Science.gov (United States)

    Savani, Krishna; Markus, Hazel Rose; Naidu, N V R; Kumar, Satishchandra; Berlia, Neha

    2010-03-01

    People everywhere select among multiple alternatives, but are they always making choices? In five studies, we found that people in U.S. American contexts, where the disjoint model of agency is prevalent, are more likely than those in Indian contexts to construe their own and other individuals' behaviors as choices, to construe ongoing behaviors and behaviors recalled from memory as choices, to construe naturally occurring and experimentally controlled behaviors as choices, to construe mundane and important actions as choices, and to construe personal and interpersonal actions as choices. Indians showed a greater tendency to construe actions as choices when these actions involved responding to other people than when they did not. These findings show that whether people construe actions as choices is significantly shaped by sociocultural systems of meanings and practices. Together, they suggest that the positive consequences associated with maximizing the availability of personal choice may not be universal and instead may be limited to North American contexts.

  1. Analyzing multiday route choice behavior of commuters using GPS data

    Directory of Open Access Journals (Sweden)

    Wenyun Tang

    2016-02-01

    Full Text Available In this study, accurate global position system and geographic information system data were employed to reveal multiday routes people used and to study multiday route choice behavior for the same origin–destination trips, from home to work. A new way of thinking about route choice modeling is provided in this study. Travelers are classified into three kinds based on the deviation between actual routes and the shortest travel time paths. Based on the classification, a two-stage route choice process is proposed, in which the first step is to classify the travelers and the second one is to model route choice behavior. After analyzing the characteristics of different types of travelers, an artificial neural network was adopted to classify travelers and model route choice behavior. An empirical study using global position systems data collected in Minneapolis–St Paul metropolitan area was carried out. It finds that most travelers follow the same route during commute trips on successive days. And different types of travelers have a significant difference in route choice property. The modeling results indicate that neural network framework can classify travelers and model route choice well.

  2. Inhalation Exposure Input Parameters for the Biosphere Model

    Energy Technology Data Exchange (ETDEWEB)

    M. A. Wasiolek

    2003-09-24

    This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air

  3. A model of the impact of reimbursement schemes on health plan choice.

    Science.gov (United States)

    Keeler, E B; Carter, G; Newhouse, J P

    1998-06-01

    Flat capitation (uniform prospective payments) makes enrolling healthy enrollees profitable to health plans. Plans with relatively generous benefits may attract the sick and fail through a premium spiral. We simulate a model of idealized managed competition to explore the effect on market performance of alternatives to flat capitation such as severity-adjusted capitation and reduced supply-side cost-sharing. In our model flat capitation causes severe market problems. Severity adjustment and to a lesser extent reduced supply-side cost-sharing improve market performance, but outcomes are efficient only in cases in which people bear the marginal costs of their choices.

  4. Repetitive Identification of Structural Systems Using a Nonlinear Model Parameter Refinement Approach

    Directory of Open Access Journals (Sweden)

    Jeng-Wen Lin

    2009-01-01

    Full Text Available This paper proposes a statistical confidence interval based nonlinear model parameter refinement approach for the health monitoring of structural systems subjected to seismic excitations. The developed model refinement approach uses the 95% confidence interval of the estimated structural parameters to determine their statistical significance in a least-squares regression setting. When the parameters' confidence interval covers the zero value, it is statistically sustainable to truncate such parameters. The remaining parameters will repetitively undergo such parameter sifting process for model refinement until all the parameters' statistical significance cannot be further improved. This newly developed model refinement approach is implemented for the series models of multivariable polynomial expansions: the linear, the Taylor series, and the power series model, leading to a more accurate identification as well as a more controllable design for system vibration control. Because the statistical regression based model refinement approach is intrinsically used to process a “batch” of data and obtain an ensemble average estimation such as the structural stiffness, the Kalman filter and one of its extended versions is introduced to the refined power series model for structural health monitoring.

  5. MODELING OF FUEL SPRAY CHARACTERISTICS AND DIESEL COMBUSTION CHAMBER PARAMETERS

    Directory of Open Access Journals (Sweden)

    G. M. Kukharonak

    2011-01-01

    Full Text Available The computer model for coordination of fuel spray characteristics with diesel combustion chamber parameters has been created in the paper.  The model allows to observe fuel sprays  develоpment in diesel cylinder at any moment of injection, to calculate characteristics of fuel sprays with due account of a shape and dimensions of a combustion chamber, timely to change fuel injection characteristics and supercharging parameters, shape and dimensions of a combustion chamber. Moreover the computer model permits to determine parameters of holes in an injector nozzle that provides the required fuel sprays characteristics at the stage of designing a diesel engine. Combustion chamber parameters for 4ЧН11/12.5 diesel engine have been determined in the paper.

  6. Four-parameter model for polarization-resolved rough-surface BRDF.

    Science.gov (United States)

    Renhorn, Ingmar G E; Hallberg, Tomas; Bergström, David; Boreman, Glenn D

    2011-01-17

    A modeling procedure is demonstrated, which allows representation of polarization-resolved BRDF data using only four parameters: the real and imaginary parts of an effective refractive index with an added parameter taking grazing incidence absorption into account and an angular-scattering parameter determined from the BRDF measurement of a chosen angle of incidence, preferably close to normal incidence. These parameters allow accurate predictions of s- and p-polarized BRDF for a painted rough surface, over three decades of variation in BRDF magnitude. To characterize any particular surface of interest, the measurements required to determine these four parameters are the directional hemispherical reflectance (DHR) for s- and p-polarized input radiation and the BRDF at a selected angle of incidence. The DHR data describes the angular and polarization dependence, as well as providing the overall normalization constraint. The resulting model conserves energy and fulfills the reciprocity criteria.

  7. Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments

    Science.gov (United States)

    Lane, Peter C. R.; Gobet, Fernand

    2013-03-01

    Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the `speciated non-dominated sorting genetic algorithm' for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.

  8. Choice certainty in Discrete Choice Experiments

    DEFF Research Database (Denmark)

    Uggeldahl, Kennet Christian; Jacobsen, Catrine; Lundhede, Thomas

    2016-01-01

    In this study, we conduct a Discrete Choice Experiment (DCE) using eye tracking technology to investigate if eye movements during the completion of choice sets reveal information about respondents’ choice certainty. We hypothesise that the number of times that respondents shift their visual...

  9. On the relationship between input parameters in two-mass vocal-fold model with acoustical coupling an signal parameters of the glottal flow

    NARCIS (Netherlands)

    van Hirtum, Annemie; Lopez, Ines; Hirschberg, Abraham; Pelorson, Xavier

    2003-01-01

    In this paper the sensitivity of the two-mass model with acoustical coupling to the model input-parameters is assessed. The model-output or the glottal volume air flow is characterised by signal-parameters in the time-domain. The influence of changing input-parameters on the signal-parameters is

  10. Lumped-Parameter Models for Windturbine Footings on Layered Ground

    DEFF Research Database (Denmark)

    Andersen, Lars

    The design of modern wind turbines is typically based on lifetime analyses using aeroelastic codes. In this regard, the impedance of the foundations must be described accurately without increasing the overall size of the computationalmodel significantly. This may be obtained by the fitting...... of a lumped-parameter model to the results of a rigorous model or experimental results. In this paper, guidelines are given for the formulation of such lumped-parameter models and examples are given in which the models are utilised for the analysis of a wind turbine supported by a surface footing on a layered...

  11. Steam condenser optimization using Real-parameter Genetic Algorithm for Prototype Fast Breeder Reactor

    International Nuclear Information System (INIS)

    Jayalal, M.L.; Kumar, L. Satish; Jehadeesan, R.; Rajeswari, S.; Satya Murty, S.A.V.; Balasubramaniyan, V.; Chetal, S.C.

    2011-01-01

    Highlights: → We model design optimization of a vital reactor component using Genetic Algorithm. → Real-parameter Genetic Algorithm is used for steam condenser optimization study. → Comparison analysis done with various Genetic Algorithm related mechanisms. → The results obtained are validated with the reference study results. - Abstract: This work explores the use of Real-parameter Genetic Algorithm and analyses its performance in the steam condenser (or Circulating Water System) optimization study of a 500 MW fast breeder nuclear reactor. Choice of optimum design parameters for condenser for a power plant from among a large number of technically viable combination is a complex task. This is primarily due to the conflicting nature of the economic implications of the different system parameters for maximizing the capitalized profit. In order to find the optimum design parameters a Real-parameter Genetic Algorithm model is developed and applied. The results obtained are validated with the reference study results.

  12. Oyster Creek cycle 10 nodal model parameter optimization study using PSMS

    International Nuclear Information System (INIS)

    Dougher, J.D.

    1987-01-01

    The power shape monitoring system (PSMS) is an on-line core monitoring system that uses a three-dimensional nodal code (NODE-B) to perform nodal power calculations and compute thermal margins. The PSMS contains a parameter optimization function that improves the ability of NODE-B to accurately monitor core power distributions. This functions iterates on the model normalization parameters (albedos and mixing factors) to obtain the best agreement between predicted and measured traversing in-core probe (TIP) reading on a statepoint-by-statepoint basis. Following several statepoint optimization runs, an average set of optimized normalization parameters can be determined and can be implemented into the current or subsequent cycle core model for on-line core monitoring. A statistical analysis of 19 high-power steady-state state-points throughout Oyster Creek cycle 10 operation has shown a consistently poor virgin model performance. The normalization parameters used in the cycle 10 NODE-B model were based on a cycle 8 study, which evaluated only Exxon fuel types. The introduction of General Electric (GE) fuel into cycle 10 (172 assemblies) was a significant fuel/core design change that could have altered the optimum set of normalization parameters. Based on the need to evaluate a potential change in the model normalization parameters for cycle 11 and in an attempt to account for the poor cycle 10 model performance, a parameter optimization study was performed

  13. Determining extreme parameter correlation in ground water models

    DEFF Research Database (Denmark)

    Hill, Mary Cole; Østerby, Ole

    2003-01-01

    can go undetected even by experienced modelers. Extreme parameter correlation can be detected using parameter correlation coefficients, but their utility depends on the presence of sufficient, but not excessive, numerical imprecision of the sensitivities, such as round-off error. This work...... investigates the information that can be obtained from parameter correlation coefficients in the presence of different levels of numerical imprecision, and compares it to the information provided by an alternative method called the singular value decomposition (SVD). Results suggest that (1) calculated...... correlation coefficients with absolute values that round to 1.00 were good indicators of extreme parameter correlation, but smaller values were not necessarily good indicators of lack of correlation and resulting unique parameter estimates; (2) the SVD may be more difficult to interpret than parameter...

  14. Time-varying parameter models for catchments with land use change: the importance of model structure

    Science.gov (United States)

    Pathiraja, Sahani; Anghileri, Daniela; Burlando, Paolo; Sharma, Ashish; Marshall, Lucy; Moradkhani, Hamid

    2018-05-01

    Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2) in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD) that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors) contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.

  15. Time-varying parameter models for catchments with land use change: the importance of model structure

    Directory of Open Access Journals (Sweden)

    S. Pathiraja

    2018-05-01

    Full Text Available Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2 in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.

  16. Calibration of a joint time assignment and mode choice model system

    OpenAIRE

    Greeven, Paulina; Jara-Diaz, Sergio R.; Munizaga, Marcela A.; Axhausen, Kay W.

    2005-01-01

    In this paper we report the results of applying a new microeconomic framework to model time assignment to activities, goods consumption and mode choice jointly (Jara-Díaz and Guevara, 2003; Jara-Díaz and Guerra, 2003) that identifies the links between these decisions and permits the calculation of all the components of the subjective value of time defined in the literature: the value of time as a resource, value of assigning time to a specific activity and the value of saving time in a specif...

  17. A Common Mechanism Underlying Food Choice and Social Decisions.

    Directory of Open Access Journals (Sweden)

    Ian Krajbich

    2015-10-01

    Full Text Available People make numerous decisions every day including perceptual decisions such as walking through a crowd, decisions over primary rewards such as what to eat, and social decisions that require balancing own and others' benefits. The unifying principles behind choices in various domains are, however, still not well understood. Mathematical models that describe choice behavior in specific contexts have provided important insights into the computations that may underlie decision making in the brain. However, a critical and largely unanswered question is whether these models generalize from one choice context to another. Here we show that a model adapted from the perceptual decision-making domain and estimated on choices over food rewards accurately predicts choices and reaction times in four independent sets of subjects making social decisions. The robustness of the model across domains provides behavioral evidence for a common decision-making process in perceptual, primary reward, and social decision making.

  18. Metamodel-based inverse method for parameter identification: elastic-plastic damage model

    Science.gov (United States)

    Huang, Changwu; El Hami, Abdelkhalak; Radi, Bouchaïb

    2017-04-01

    This article proposed a metamodel-based inverse method for material parameter identification and applies it to elastic-plastic damage model parameter identification. An elastic-plastic damage model is presented and implemented in numerical simulation. The metamodel-based inverse method is proposed in order to overcome the disadvantage in computational cost of the inverse method. In the metamodel-based inverse method, a Kriging metamodel is constructed based on the experimental design in order to model the relationship between material parameters and the objective function values in the inverse problem, and then the optimization procedure is executed by the use of a metamodel. The applications of the presented material model and proposed parameter identification method in the standard A 2017-T4 tensile test prove that the presented elastic-plastic damage model is adequate to describe the material's mechanical behaviour and that the proposed metamodel-based inverse method not only enhances the efficiency of parameter identification but also gives reliable results.

  19. Paradoxical choice in rats: Subjective valuation and mechanism of choice.

    Science.gov (United States)

    Ojeda, Andrés; Murphy, Robin A; Kacelnik, Alex

    2018-07-01

    Decision-makers benefit from information only when they can use it to guide behavior. However, recent experiments found that pigeons and starlings value information that they cannot use. Here we show that this paradox is also present in rats, and explore the underlying decision process. Subjects chose between two options that delivered food probabilistically after a fixed delay. In one option ("info"), outcomes (food/no-food) were signaled immediately after choice, whereas in the alternative ("non-info") the outcome was uncertain until the delay lapsed. Rats sacrificed up to 20% potential rewards by preferring the info option, but reversed preference when the cost was 60%. This reversal contrasts with the results found with pigeons and starlings and may reflect species' differences worth of further investigation. Results are consistent with predictions of the Sequential Choice Model (SCM), that proposes that choices are driven by the mechanisms that control action in sequential encounters. As expected from the SCM, latencies to respond in single-option trials predicted preferences in choice trials, and latencies in choice trials were the same or shorter than in single-option trials. We argue that the congruence of results in distant vertebrates probably reflects evolved adaptations to shared fundamental challenges in nature, and that the apparently paradoxical overvaluing of information is not sub-optimal as has been claimed, even though its functional significance is not yet understood. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. The application of the random regret minimization model to drivers’ choice of crash avoidance maneuvers

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    This study explores the plausibility of regret minimization as behavioral paradigm underlying the choice of crash avoidance maneuvers. Alternatively to previous studies that considered utility maximization, this study applies the random regret minimization (RRM) model while assuming that drivers ...