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Sample records for decision analysis model

  1. Comparative Analysis of Investment Decision Models

    Directory of Open Access Journals (Sweden)

    Ieva Kekytė

    2017-06-01

    Full Text Available Rapid development of financial markets resulted new challenges for both investors and investment issues. This increased demand for innovative, modern investment and portfolio management decisions adequate for market conditions. Financial market receives special attention, creating new models, includes financial risk management and investment decision support systems.Researchers recognize the need to deal with financial problems using models consistent with the reality and based on sophisticated quantitative analysis technique. Thus, role mathematical modeling in finance becomes important. This article deals with various investments decision-making models, which include forecasting, optimization, stochatic processes, artificial intelligence, etc., and become useful tools for investment decisions.

  2. Sensitivity Analysis in Sequential Decision Models.

    Science.gov (United States)

    Chen, Qiushi; Ayer, Turgay; Chhatwal, Jagpreet

    2017-02-01

    Sequential decision problems are frequently encountered in medical decision making, which are commonly solved using Markov decision processes (MDPs). Modeling guidelines recommend conducting sensitivity analyses in decision-analytic models to assess the robustness of the model results against the uncertainty in model parameters. However, standard methods of conducting sensitivity analyses cannot be directly applied to sequential decision problems because this would require evaluating all possible decision sequences, typically in the order of trillions, which is not practically feasible. As a result, most MDP-based modeling studies do not examine confidence in their recommended policies. In this study, we provide an approach to estimate uncertainty and confidence in the results of sequential decision models. First, we provide a probabilistic univariate method to identify the most sensitive parameters in MDPs. Second, we present a probabilistic multivariate approach to estimate the overall confidence in the recommended optimal policy considering joint uncertainty in the model parameters. We provide a graphical representation, which we call a policy acceptability curve, to summarize the confidence in the optimal policy by incorporating stakeholders' willingness to accept the base case policy. For a cost-effectiveness analysis, we provide an approach to construct a cost-effectiveness acceptability frontier, which shows the most cost-effective policy as well as the confidence in that for a given willingness to pay threshold. We demonstrate our approach using a simple MDP case study. We developed a method to conduct sensitivity analysis in sequential decision models, which could increase the credibility of these models among stakeholders.

  3. Social influence and perceptual decision making: a diffusion model analysis.

    Science.gov (United States)

    Germar, Markus; Schlemmer, Alexander; Krug, Kristine; Voss, Andreas; Mojzisch, Andreas

    2014-02-01

    Classic studies on social influence used simple perceptual decision-making tasks to examine how the opinions of others change individuals' judgments. Since then, one of the most fundamental questions in social psychology has been whether social influence can alter basic perceptual processes. To address this issue, we used a diffusion model analysis. Diffusion models provide a stochastic approach for separating the cognitive processes underlying speeded binary decisions. Following this approach, our study is the first to disentangle whether social influence on decision making is due to altering the uptake of available sensory information or due to shifting the decision criteria. In two experiments, we found consistent evidence for the idea that social influence alters the uptake of available sensory evidence. By contrast, participants did not adjust their decision criteria.

  4. Modelling elderly cardiac patients decision making using Cognitive Work Analysis: identifying requirements for patient decision aids.

    Science.gov (United States)

    Dhukaram, Anandhi Vivekanandan; Baber, Chris

    2015-06-01

    Patients make various healthcare decisions on a daily basis. Such day-to-day decision making can have significant consequences on their own health, treatment, care, and costs. While decision aids (DAs) provide effective support in enhancing patient's decision making, to date there have been few studies examining patient's decision making process or exploring how the understanding of such decision processes can aid in extracting requirements for the design of DAs. This paper applies Cognitive Work Analysis (CWA) to analyse patient's decision making in order to inform requirements for supporting self-care decision making. This study uses focus groups to elicit information from elderly cardiovascular disease (CVD) patients concerning a range of decision situations they face on a daily basis. Specifically, the focus groups addressed issues related to the decision making of CVD in terms of medication compliance, pain, diet and exercise. The results of these focus groups are used to develop high level views using CWA. CWA framework decomposes the complex decision making problem to inform three approaches to DA design: one design based on high level requirements; one based on a normative model of decision-making for patients; and the third based on a range of heuristics that patients seem to use. CWA helps in extracting and synthesising decision making from different perspectives: decision processes, work organisation, patient competencies and strategies used in decision making. As decision making can be influenced by human behaviour like skills, rules and knowledge, it is argued that patients require support to different types of decision making. This paper also provides insights for designers in using CWA framework for the design of effective DAs to support patients in self-management. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  5. Design of Graph Analysis Model to support Decision Making

    International Nuclear Information System (INIS)

    An, Sang Ha; Lee, Sung Jin; Chang, Soon Heung; Kim, Sung Ho; Kim, Tae Woon

    2005-01-01

    Korea is meeting the growing electric power needs by using nuclear, fissile, hydro energy and so on. But we can not use fissile energy forever, and the people's consideration about nature has been changed. So we have to prepare appropriate energy by the conditions before people need more energy. And we should prepare dynamic response because people's need would be changed as the time goes on. So we designed graphic analysis model (GAM) for the dynamic analysis of decision on the energy sources. It can support Analytic Hierarchy Process (AHP) analysis based on Graphic User Interface

  6. Hierarchical Modelling of Flood Risk for Engineering Decision Analysis

    DEFF Research Database (Denmark)

    Custer, Rocco

    protection structures in the hierarchical flood protection system - is identified. To optimise the design of protection structures, fragility and vulnerability models must allow for consideration of decision alternatives. While such vulnerability models are available for large protection structures (e...... systems, as well as the implementation of the flood risk analysis methodology and the vulnerability modelling approach are illustrated with an example application. In summary, the present thesis provides a characterisation of hierarchical flood protection systems as well as several methodologies to model...... and robust. Traditional risk management solutions, e.g. dike construction, are not particularly flexible, as they are difficult to adapt to changing risk. Conversely, the recent concept of integrated flood risk management, entailing a combination of several structural and non-structural risk management...

  7. A diffusion decision model analysis of evidence variability in the lexical decision task

    NARCIS (Netherlands)

    Tillman, Gabriel; Osth, Adam F.; van Ravenzwaaij, Don; Heathcote, Andrew

    2017-01-01

    The lexical-decision task is among the most commonly used paradigms in psycholinguistics. In both the signal-detection theory and Diffusion Decision Model (DDM; Ratcliff, Gomez, & McKoon, Psychological Review, 111, 159–182, 2004) frameworks, lexical-decisions are based on a continuous source of

  8. Selection of Representative Models for Decision Analysis Under Uncertainty

    Science.gov (United States)

    Meira, Luis A. A.; Coelho, Guilherme P.; Santos, Antonio Alberto S.; Schiozer, Denis J.

    2016-03-01

    The decision-making process in oil fields includes a step of risk analysis associated with the uncertainties present in the variables of the problem. Such uncertainties lead to hundreds, even thousands, of possible scenarios that are supposed to be analyzed so an effective production strategy can be selected. Given this high number of scenarios, a technique to reduce this set to a smaller, feasible subset of representative scenarios is imperative. The selected scenarios must be representative of the original set and also free of optimistic and pessimistic bias. This paper is devoted to propose an assisted methodology to identify representative models in oil fields. To do so, first a mathematical function was developed to model the representativeness of a subset of models with respect to the full set that characterizes the problem. Then, an optimization tool was implemented to identify the representative models of any problem, considering not only the cross-plots of the main output variables, but also the risk curves and the probability distribution of the attribute-levels of the problem. The proposed technique was applied to two benchmark cases and the results, evaluated by experts in the field, indicate that the obtained solutions are richer than those identified by previously adopted manual approaches. The program bytecode is available under request.

  9. Model for nuclear proliferation resistance analysis using decision making tools

    International Nuclear Information System (INIS)

    Ko, Won Il; Kim, Ho Dong; Yang, Myung Seung

    2003-06-01

    The nuclear proliferation risks of nuclear fuel cycles is being considered as one of the most important factors in assessing advanced and innovative nuclear systems in GEN IV and INPRO program. They have been trying to find out an appropriate and reasonable method to evaluate quantitatively several nuclear energy system alternatives. Any reasonable methodology for integrated analysis of the proliferation resistance, however, has not yet been come out at this time. In this study, several decision making methods, which have been used in the situation of multiple objectives, are described in order to see if those can be appropriately used for proliferation resistance evaluation. Especially, the AHP model for quantitatively evaluating proliferation resistance is dealt with in more detail. The theoretical principle of the method and some examples for the proliferation resistance problem are described. For more efficient applications, a simple computer program for the AHP model is developed, and the usage of the program is introduced here in detail. We hope that the program developed in this study could be useful for quantitative analysis of the proliferation resistance involving multiple conflict criteria

  10. Model for nuclear proliferation resistance analysis using decision making tools

    Energy Technology Data Exchange (ETDEWEB)

    Ko, Won Il; Kim, Ho Dong; Yang, Myung Seung

    2003-06-01

    The nuclear proliferation risks of nuclear fuel cycles is being considered as one of the most important factors in assessing advanced and innovative nuclear systems in GEN IV and INPRO program. They have been trying to find out an appropriate and reasonable method to evaluate quantitatively several nuclear energy system alternatives. Any reasonable methodology for integrated analysis of the proliferation resistance, however, has not yet been come out at this time. In this study, several decision making methods, which have been used in the situation of multiple objectives, are described in order to see if those can be appropriately used for proliferation resistance evaluation. Especially, the AHP model for quantitatively evaluating proliferation resistance is dealt with in more detail. The theoretical principle of the method and some examples for the proliferation resistance problem are described. For more efficient applications, a simple computer program for the AHP model is developed, and the usage of the program is introduced here in detail. We hope that the program developed in this study could be useful for quantitative analysis of the proliferation resistance involving multiple conflict criteria.

  11. A diffusion decision model analysis of evidence variability in the lexical decision task.

    Science.gov (United States)

    Tillman, Gabriel; Osth, Adam F; van Ravenzwaaij, Don; Heathcote, Andrew

    2017-12-01

    The lexical-decision task is among the most commonly used paradigms in psycholinguistics. In both the signal-detection theory and Diffusion Decision Model (DDM; Ratcliff, Gomez, & McKoon, Psychological Review, 111, 159-182, 2004) frameworks, lexical-decisions are based on a continuous source of word-likeness evidence for both words and non-words. The Retrieving Effectively from Memory model of Lexical-Decision (REM-LD; Wagenmakers et al., Cognitive Psychology, 48(3), 332-367, 2004) provides a comprehensive explanation of lexical-decision data and makes the prediction that word-likeness evidence is more variable for words than non-words and that higher frequency words are more variable than lower frequency words. To test these predictions, we analyzed five lexical-decision data sets with the DDM. For all data sets, drift-rate variability changed across word frequency and non-word conditions. For the most part, REM-LD's predictions about the ordering of evidence variability across stimuli in the lexical-decision task were confirmed.

  12. Verification and validation of the decision analysis model for assessment of TWRS waste treatment strategies

    International Nuclear Information System (INIS)

    Awadalla, N.G.; Eaton, S.C.F.

    1996-01-01

    This document is the verification and validation final report for the Decision Analysis Model for Assessment of Tank Waste Remediation System Waste Treatment Strategies. This model is also known as the INSIGHT Model

  13. A Costing Analysis for Decision Making Grid Model in Failure-Based Maintenance

    Directory of Open Access Journals (Sweden)

    Burhanuddin M. A.

    2011-01-01

    Full Text Available Background. In current economic downturn, industries have to set good control on production cost, to maintain their profit margin. Maintenance department as an imperative unit in industries should attain all maintenance data, process information instantaneously, and subsequently transform it into a useful decision. Then act on the alternative to reduce production cost. Decision Making Grid model is used to identify strategies for maintenance decision. However, the model has limitation as it consider two factors only, that is, downtime and frequency of failures. We consider third factor, cost, in this study for failure-based maintenance. The objective of this paper is to introduce the formulae to estimate maintenance cost. Methods. Fish bone analysis conducted with Ishikawa model and Decision Making Grid methods are used in this study to reveal some underlying risk factors that delay failure-based maintenance. The goal of the study is to estimate the risk factor that is, repair cost to fit in the Decision Making Grid model. Decision Making grid model consider two variables, frequency of failure and downtime in the analysis. This paper introduces third variable, repair cost for Decision Making Grid model. This approaches give better result to categorize the machines, reduce cost, and boost the earning for the manufacturing plant. Results. We collected data from one of the food processing factories in Malaysia. From our empirical result, Machine C, Machine D, Machine F, and Machine I must be in the Decision Making Grid model even though their frequency of failures and downtime are less than Machine B and Machine N, based on the costing analysis. The case study and experimental results show that the cost analysis in Decision Making Grid model gives more promising strategies in failure-based maintenance. Conclusions. The improvement of Decision Making Grid model for decision analysis with costing analysis is our contribution in this paper for

  14. Decision analysis multicriteria analysis

    International Nuclear Information System (INIS)

    Lombard, J.

    1986-09-01

    The ALARA procedure covers a wide range of decisions from the simplest to the most complex one. For the simplest one the engineering judgement is generally enough and the use of a decision aiding technique is therefore not necessary. For some decisions the comparison of the available protection option may be performed from two or a few criteria (or attributes) (protection cost, collective dose,...) and the use of rather simple decision aiding techniques, like the Cost Effectiveness Analysis or the Cost Benefit Analysis, is quite enough. For the more complex decisions, involving numerous criteria or for decisions involving large uncertainties or qualitative judgement the use of these techniques, even the extended cost benefit analysis, is not recommended and appropriate techniques like multi-attribute decision aiding techniques are more relevant. There is a lot of such particular techniques and it is not possible to present all of them. Therefore only two broad categories of multi-attribute decision aiding techniques will be presented here: decision analysis and the outranking analysis

  15. LANL Institutional Decision Support By Process Modeling and Analysis Group (AET-2)

    Energy Technology Data Exchange (ETDEWEB)

    Booth, Steven Richard [Los Alamos National Laboratory

    2016-04-04

    AET-2 has expertise in process modeling, economics, business case analysis, risk assessment, Lean/Six Sigma tools, and decision analysis to provide timely decision support to LANS leading to continuous improvement. This capability is critical during the current tight budgetary environment as LANS pushes to identify potential areas of cost savings and efficiencies. An important arena is business systems and operations, where processes can impact most or all laboratory employees. Lab-wide efforts are needed to identify and eliminate inefficiencies to accomplish Director McMillan’s charge of “doing more with less.” LANS faces many critical and potentially expensive choices that require sound decision support to ensure success. AET-2 is available to provide this analysis support to expedite the decisions at hand.

  16. Global analysis of dynamical decision-making models through local computation around the hidden saddle.

    Directory of Open Access Journals (Sweden)

    Laura Trotta

    Full Text Available Bistable dynamical switches are frequently encountered in mathematical modeling of biological systems because binary decisions are at the core of many cellular processes. Bistable switches present two stable steady-states, each of them corresponding to a distinct decision. In response to a transient signal, the system can flip back and forth between these two stable steady-states, switching between both decisions. Understanding which parameters and states affect this switch between stable states may shed light on the mechanisms underlying the decision-making process. Yet, answering such a question involves analyzing the global dynamical (i.e., transient behavior of a nonlinear, possibly high dimensional model. In this paper, we show how a local analysis at a particular equilibrium point of bistable systems is highly relevant to understand the global properties of the switching system. The local analysis is performed at the saddle point, an often disregarded equilibrium point of bistable models but which is shown to be a key ruler of the decision-making process. Results are illustrated on three previously published models of biological switches: two models of apoptosis, the programmed cell death and one model of long-term potentiation, a phenomenon underlying synaptic plasticity.

  17. Balancing Information Analysis and Decision Value: A Model to Exploit the Decision Process

    Science.gov (United States)

    2011-12-01

    technical intelli- gence e.g. signals and sensors (SIGINT and MASINT), imagery (!MINT), as well and human and open source intelligence (HUMINT and OSINT ...Clark 2006). The ability to capture large amounts of da- ta and the plenitude of modem intelligence information sources provides a rich cache of...many tech- niques for managing information collected and derived from these sources , the exploitation of intelligence assets for decision-making

  18. Uncertainty and sensitivity analysis of flood risk management decisions based on stationary and nonstationary model choices

    Directory of Open Access Journals (Sweden)

    Rehan Balqis M.

    2016-01-01

    Full Text Available Current practice in flood frequency analysis assumes that the stochastic properties of extreme floods follow that of stationary conditions. As human intervention and anthropogenic climate change influences in hydrometeorological variables are becoming evident in some places, there have been suggestions that nonstationary statistics would be better to represent the stochastic properties of the extreme floods. The probabilistic estimation of non-stationary models, however, is surrounded with uncertainty related to scarcity of observations and modelling complexities hence the difficulty to project the future condition. In the face of uncertain future and the subjectivity of model choices, this study attempts to demonstrate the practical implications of applying a nonstationary model and compares it with a stationary model in flood risk assessment. A fully integrated framework to simulate decision makers’ behaviour in flood frequency analysis is thereby developed. The framework is applied to hypothetical flood risk management decisions and the outcomes are compared with those of known underlying future conditions. Uncertainty of the economic performance of the risk-based decisions is assessed through Monte Carlo simulations. Sensitivity of the results is also tested by varying the possible magnitude of future changes. The application provides quantitative and qualitative comparative results that satisfy a preliminary analysis of whether the nonstationary model complexity should be applied to improve the economic performance of decisions. Results obtained from the case study shows that the relative differences of competing models for all considered possible future changes are small, suggesting that stationary assumptions are preferred to a shift to nonstationary statistics for practical application of flood risk management. Nevertheless, nonstationary assumption should also be considered during a planning stage in addition to stationary assumption

  19. Decision making model design for antivirus software selection using Factor Analysis and Analytical Hierarchy Process

    OpenAIRE

    Nurhayati Ai; Gautama Aditya; Naseer Muchammad

    2018-01-01

    Virus spread increase significantly through the internet in 2017. One of the protection method is using antivirus software. The wide variety of antivirus software in the market tends to creating confusion among consumer. Selecting the right antivirus according to their needs has become difficult. This is the reason we conduct our research. We formulate a decision making model for antivirus software consumer. The model is constructed by using factor analysis and AHP method. First we spread que...

  20. A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.

    Science.gov (United States)

    Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L; Postmus, Douwe

    2011-05-30

    Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi-criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi-criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi-criteria model for the therapeutic group of second-generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade-offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.

  1. Quantification of a decision-making failure probability of the accident management using cognitive analysis model

    International Nuclear Information System (INIS)

    Yoshida, Yoshitaka; Ohtani, Masanori; Fujita, Yushi

    2002-01-01

    In the nuclear power plant, much knowledge is acquired through probabilistic safety assessment (PSA) of a severe accident, and accident management (AM) is prepared. It is necessary to evaluate the effectiveness of AM using the decision-making failure probability of an emergency organization, operation failure probability of operators, success criteria of AM and reliability of AM equipments in PSA. However, there has been no suitable qualification method for PSA so far to obtain the decision-making failure probability, because the decision-making failure of an emergency organization treats the knowledge based error. In this work, we developed a new method for quantification of the decision-making failure probability of an emergency organization using cognitive analysis model, which decided an AM strategy, in a nuclear power plant at the severe accident, and tried to apply it to a typical pressurized water reactor (PWR) plant. As a result: (1) It could quantify the decision-making failure probability adjusted to PSA for general analysts, who do not necessarily possess professional human factors knowledge, by choosing the suitable value of a basic failure probability and an error-factor. (2) The decision-making failure probabilities of six AMs were in the range of 0.23 to 0.41 using the screening evaluation method and in the range of 0.10 to 0.19 using the detailed evaluation method as the result of trial evaluation based on severe accident analysis of a typical PWR plant, and a result of sensitivity analysis of the conservative assumption, failure probability decreased about 50%. (3) The failure probability using the screening evaluation method exceeded that using detailed evaluation method by 99% of probability theoretically, and the failure probability of AM in this study exceeded 100%. From this result, it was shown that the decision-making failure probability was more conservative than the detailed evaluation method, and the screening evaluation method satisfied

  2. Quantification of a decision-making failure probability of the accident management using cognitive analysis model

    Energy Technology Data Exchange (ETDEWEB)

    Yoshida, Yoshitaka; Ohtani, Masanori [Institute of Nuclear Safety System, Inc., Mihama, Fukui (Japan); Fujita, Yushi [TECNOVA Corp., Tokyo (Japan)

    2002-09-01

    In the nuclear power plant, much knowledge is acquired through probabilistic safety assessment (PSA) of a severe accident, and accident management (AM) is prepared. It is necessary to evaluate the effectiveness of AM using the decision-making failure probability of an emergency organization, operation failure probability of operators, success criteria of AM and reliability of AM equipments in PSA. However, there has been no suitable qualification method for PSA so far to obtain the decision-making failure probability, because the decision-making failure of an emergency organization treats the knowledge based error. In this work, we developed a new method for quantification of the decision-making failure probability of an emergency organization using cognitive analysis model, which decided an AM strategy, in a nuclear power plant at the severe accident, and tried to apply it to a typical pressurized water reactor (PWR) plant. As a result: (1) It could quantify the decision-making failure probability adjusted to PSA for general analysts, who do not necessarily possess professional human factors knowledge, by choosing the suitable value of a basic failure probability and an error-factor. (2) The decision-making failure probabilities of six AMs were in the range of 0.23 to 0.41 using the screening evaluation method and in the range of 0.10 to 0.19 using the detailed evaluation method as the result of trial evaluation based on severe accident analysis of a typical PWR plant, and a result of sensitivity analysis of the conservative assumption, failure probability decreased about 50%. (3) The failure probability using the screening evaluation method exceeded that using detailed evaluation method by 99% of probability theoretically, and the failure probability of AM in this study exceeded 100%. From this result, it was shown that the decision-making failure probability was more conservative than the detailed evaluation method, and the screening evaluation method satisfied

  3. Extended warranties, maintenance service and lease contracts modeling and analysis for decision-making

    CERN Document Server

    Murthy, D N Prabhakar

    2014-01-01

    Serving to unify the existing literature on extended warranties, maintenance service contracts and lease contracts, this book also presents a unique perspective on the topic focussed on cost analysis and decision-making from the perspectives of the parties involved. Using a game theoretic approach together with mathematical modelling, results are presented in an integrated manner with key topics that require further research highlighted in order to serve as a starting point for researchers (engineers and statisticians) who are interested in doing further work in these areas. Designed to assist practitioners (managers, engineers, applied statisticians) who are involved with extended warranties, maintenance service contracts and lease contracts, the book provides them with the models and techniques needed for proper cost analysis and effective decision-making. The book is also suitable for use as a reference text in industrial engineering, applied statistics, operations research and management.

  4. A new approach to hazardous materials transportation risk analysis: decision modeling to identify critical variables.

    Science.gov (United States)

    Clark, Renee M; Besterfield-Sacre, Mary E

    2009-03-01

    We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity, and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk.

  5. Analysis on Dynamic Decision-Making Model of the Enterprise Technological Innovation Investment under Uncertain Environment

    Directory of Open Access Journals (Sweden)

    Yong Long

    2012-01-01

    Full Text Available Under the environment of fuzzy factors including the return of market, performance of product, and the demanding level of market, we use the method of dynamic programming and establish the model of investment decision, in technology innovation project of enterprise, based on the dynamic programming. Analysis of the influence caused by the changes of fuzzy uncertainty factors to technological innovation project investment of enterprise.

  6. Applying Recursive Sensitivity Analysis to Multi-Criteria Decision Models to Reduce Bias in Defense Cyber Engineering Analysis

    Science.gov (United States)

    2015-10-28

    techniques such as regression analysis, correlation, and multicollinearity assessment to identify the change and error on the input to the model...between many of the independent or predictor variables, the issue of multicollinearity may arise [18]. VII. SUMMARY Accurate decisions concerning

  7. A model of pathways to artificial superintelligence catastrophe for risk and decision analysis

    Science.gov (United States)

    Barrett, Anthony M.; Baum, Seth D.

    2017-03-01

    An artificial superintelligence (ASI) is an artificial intelligence that is significantly more intelligent than humans in all respects. Whilst ASI does not currently exist, some scholars propose that it could be created sometime in the future, and furthermore that its creation could cause a severe global catastrophe, possibly even resulting in human extinction. Given the high stakes, it is important to analyze ASI risk and factor the risk into decisions related to ASI research and development. This paper presents a graphical model of major pathways to ASI catastrophe, focusing on ASI created via recursive self-improvement. The model uses the established risk and decision analysis modelling paradigms of fault trees and influence diagrams in order to depict combinations of events and conditions that could lead to AI catastrophe, as well as intervention options that could decrease risks. The events and conditions include select aspects of the ASI itself as well as the human process of ASI research, development and management. Model structure is derived from published literature on ASI risk. The model offers a foundation for rigorous quantitative evaluation and decision-making on the long-term risk of ASI catastrophe.

  8. AN ANALYSIS ON THE DECISION MODEL OF SMART PLUS INSURANCE PRODUCT PURCHASE

    Directory of Open Access Journals (Sweden)

    Fitry Primadona

    2016-09-01

    Full Text Available The purposes of this study were 1 to analyze the decision model of Smart Plus insurance product purchase and 2 to determine the criteria, sub-criteria, and alternative priorities in Smart Plus purchase decision model. The methods utilized in the study included a survey and interview (in-depth interview by using an AHP analysis (Analytical Hierarchy Process and processing software of "Expert Choice". The result of the first analysis indicated the four marketing mixes that had been performed (Price, Product, Process, and Place; while the second one showed that the purchase of Smart Plus product is based on the factors with the level of interest as follow: benefit (36.3%, premium (35.7%, membership process (14.6%, and provider (13.4%. The result of the second analysis revealed the important sub-criteria including premium offer, additional benefits, membership card, and temporary certificate from the medical specialist.Keywords: AHP, life insurance, marketing mix, purchase decision

  9. Differential impairments underlying decision making in anorexia nervosa and bulimia nervosa: a cognitive modeling analysis.

    Science.gov (United States)

    Chan, Trista Wai Sze; Ahn, Woo-Young; Bates, John E; Busemeyer, Jerome R; Guillaume, Sebastien; Redgrave, Graham W; Danner, Unna N; Courtet, Philippe

    2014-03-01

    This study examined the underlying processes of decision-making impairments in individuals with anorexia nervosa (AN) and bulimia nervosa (BN). We deconstructed their performance on the widely used decision task, the Iowa Gambling Task (IGT) into cognitive, motivational, and response processes using cognitive modeling analysis. We hypothesized that IGT performance would be characterized by impaired memory functions and heightened punishment sensitivity in AN, and by elevated sensitivity to reward as opposed to punishment in BN. We analyzed trial-by-trial data of IGT obtained from 224 individuals: 94 individuals with AN, 63 with BN, and 67 healthy comparison individuals (HC). The prospect valence learning model was used to assess cognitive, motivational, and response processes underlying IGT performance. Individuals with AN showed marginally impaired IGT performance compared to HC. Their performance was characterized by impairments in memory functions. Individuals with BN showed significantly impaired IGT performance compared to HC. They showed greater relative sensitivity to gains as opposed to losses than HC. Memory functions in AN were positively correlated with body mass index. This study identified differential impairments underlying IGT performance in AN and BN. Findings suggest that impaired decision making in AN might involve impaired memory functions. Impaired decision making in BN might involve altered reward and punishment sensitivity. Copyright © 2013 Wiley Periodicals, Inc.

  10. Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention.

    Directory of Open Access Journals (Sweden)

    Cécile Aenishaenslin

    Full Text Available Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or

  11. Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention.

    Science.gov (United States)

    Aenishaenslin, Cécile; Gern, Lise; Michel, Pascal; Ravel, André; Hongoh, Valérie; Waaub, Jean-Philippe; Milord, François; Bélanger, Denise

    2015-01-01

    Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD) can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA) model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or other vector

  12. Models for Rational Decision Making. Analysis of Literature and Selected Bibliography. Analysis and Bibliography Series, No. 6.

    Science.gov (United States)

    Hall, John S.

    This review analyzes the trend in educational decision making to replace hierarchical authority structures with more rational models for decision making drawn from management science. Emphasis is also placed on alternatives to a hierarchical decision-making model, including governing models, union models, and influence models. A 54-item…

  13. Cloud Geospatial Analysis Tools for Global-Scale Comparisons of Population Models for Decision Making

    Science.gov (United States)

    Hancher, M.; Lieber, A.; Scott, L.

    2017-12-01

    The volume of satellite and other Earth data is growing rapidly. Combined with information about where people are, these data can inform decisions in a range of areas including food and water security, disease and disaster risk management, biodiversity, and climate adaptation. Google's platform for planetary-scale geospatial data analysis, Earth Engine, grants access to petabytes of continually updating Earth data, programming interfaces for analyzing the data without the need to download and manage it, and mechanisms for sharing the analyses and publishing results for data-driven decision making. In addition to data about the planet, data about the human planet - population, settlement and urban models - are now available for global scale analysis. The Earth Engine APIs enable these data to be joined, combined or visualized with economic or environmental indicators such as nighttime lights trends, global surface water, or climate projections, in the browser without the need to download anything. We will present our newly developed application intended to serve as a resource for government agencies, disaster response and public health programs, or other consumers of these data to quickly visualize the different population models, and compare them to ground truth tabular data to determine which model suits their immediate needs. Users can further tap into the power of Earth Engine and other Google technologies to perform a range of analysis from simple statistics in custom regions to more complex machine learning models. We will highlight case studies in which organizations around the world have used Earth Engine to combine population data with multiple other sources of data, such as water resources and roads data, over deep stacks of temporal imagery to model disease risk and accessibility to inform decisions.

  14. Harnessing Ecosystem Models and Multi-Criteria Decision Analysis for the Support of Forest Management

    Science.gov (United States)

    Wolfslehner, Bernhard; Seidl, Rupert

    2010-12-01

    The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

  15. Markov Modeling with Soft Aggregation for Safety and Decision Analysis; TOPICAL

    International Nuclear Information System (INIS)

    COOPER, J. ARLIN

    1999-01-01

    The methodology in this report improves on some of the limitations of many conventional safety assessment and decision analysis methods. A top-down mathematical approach is developed for decomposing systems and for expressing imprecise individual metrics as possibilistic or fuzzy numbers. A ''Markov-like'' model is developed that facilitates combining (aggregating) inputs into overall metrics and decision aids, also portraying the inherent uncertainty. A major goal of Markov modeling is to help convey the top-down system perspective. One of the constituent methodologies allows metrics to be weighted according to significance of the attribute and aggregated nonlinearly as to contribution. This aggregation is performed using exponential combination of the metrics, since the accumulating effect of such factors responds less and less to additional factors. This is termed ''soft'' mathematical aggregation. Dependence among the contributing factors is accounted for by incorporating subjective metrics on ''overlap'' of the factors as well as by correspondingly reducing the overall contribution of these combinations to the overall aggregation. Decisions corresponding to the meaningfulness of the results are facilitated in several ways. First, the results are compared to a soft threshold provided by a sigmoid function. Second, information is provided on input ''Importance'' and ''Sensitivity,'' in order to know where to place emphasis on considering new controls that may be necessary. Third, trends in inputs and outputs are tracked in order to obtain significant information% including cyclic information for the decision process. A practical example from the air transportation industry is used to demonstrate application of the methodology. Illustrations are given for developing a structure (along with recommended inputs and weights) for air transportation oversight at three different levels, for developing and using cycle information, for developing Importance and

  16. From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions

    Science.gov (United States)

    Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent

    2016-02-01

    This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the

  17. Optimizing medical device buying. Value analysis models can help you improve decision-making process.

    Science.gov (United States)

    Feldstein, Josh; Brooks, Elizabeth

    2010-05-01

    Value Analysis Models (VAMs) are a burgeoning analytical tool that can help materials managers, operating room managers, CFOs and others to make comparative value assessments before reaching a critical purchasing decision. Although relatively new to the hospital field, more and more manufacturers are supporting these initiatives to bring critical information to their customers and the health care industry. VAMs aren't designed to conclude that one product is better than another but to be a tool that can help make the product acquisition process much easier.

  18. A Costing Analysis for Decision Making Grid Model in Failure-Based Maintenance

    OpenAIRE

    M. A., Burhanuddin; Halawani, Sami M.; Ahmad, A. R.

    2011-01-01

    Background. In current economic downturn, industries have to set good control on production cost, to maintain their profit margin. Maintenance department as an imperative unit in industries should attain all maintenance data, process information instantaneously, and subsequently transform it into a useful decision. Then act on the alternative to reduce production cost. Decision Making Grid model is used to identify strategies for maintenance decision. However, the model has limitation as it c...

  19. Decision analysis and risk models for land development affecting infrastructure systems.

    Science.gov (United States)

    Thekdi, Shital A; Lambert, James H

    2012-07-01

    Coordination and layering of models to identify risks in complex systems such as large-scale infrastructure of energy, water, and transportation is of current interest across application domains. Such infrastructures are increasingly vulnerable to adjacent commercial and residential land development. Land development can compromise the performance of essential infrastructure systems and increase the costs of maintaining or increasing performance. A risk-informed approach to this topic would be useful to avoid surprise, regret, and the need for costly remedies. This article develops a layering and coordination of models for risk management of land development affecting infrastructure systems. The layers are: system identification, expert elicitation, predictive modeling, comparison of investment alternatives, and implications of current decisions for future options. The modeling layers share a focus on observable factors that most contribute to volatility of land development and land use. The relevant data and expert evidence include current and forecasted growth in population and employment, conservation and preservation rules, land topography and geometries, real estate assessments, market and economic conditions, and other factors. The approach integrates to a decision framework of strategic considerations based on assessing risk, cost, and opportunity in order to prioritize needs and potential remedies that mitigate impacts of land development to the infrastructure systems. The approach is demonstrated for a 5,700-mile multimodal transportation system adjacent to 60,000 tracts of potential land development. © 2011 Society for Risk Analysis.

  20. Slower Perception Followed by Faster Lexical Decision in Longer Words: A Diffusion Model Analysis.

    Science.gov (United States)

    Oganian, Yulia; Froehlich, Eva; Schlickeiser, Ulrike; Hofmann, Markus J; Heekeren, Hauke R; Jacobs, Arthur M

    2015-01-01

    Effects of stimulus length on reaction times (RTs) in the lexical decision task are the topic of extensive research. While slower RTs are consistently found for longer pseudo-words, a finding coined the word length effect (WLE), some studies found no effects for words, and yet others reported faster RTs for longer words. Moreover, the WLE depends on the orthographic transparency of a language, with larger effects in more transparent orthographies. Here we investigate processes underlying the WLE in lexical decision in German-English bilinguals using a diffusion model (DM) analysis, which we compared to a linear regression approach. In the DM analysis, RT-accuracy distributions are characterized using parameters that reflect latent sub-processes, in particular evidence accumulation and decision-independent perceptual encoding, instead of typical parameters such as mean RT and accuracy. The regression approach showed a decrease in RTs with length for pseudo-words, but no length effect for words. However, DM analysis revealed that the null effect for words resulted from opposing effects of length on perceptual encoding and rate of evidence accumulation. Perceptual encoding times increased with length for words and pseudo-words, whereas the rate of evidence accumulation increased with length for real words but decreased for pseudo-words. A comparison between DM parameters in German and English suggested that orthographic transparency affects perceptual encoding, whereas effects of length on evidence accumulation are likely to reflect contextual information and the increase in available perceptual evidence with length. These opposing effects may account for the inconsistent findings on WLEs.

  1. Dynamics of Metabolism and Decision Making During Alcohol Consumption: Modeling and Analysis.

    Science.gov (United States)

    Giraldo, Luis Felipe; Passino, Kevin M; Clapp, John D; Ruderman, Danielle

    2017-11-01

    Heavy alcohol consumption is considered an important public health issue in the United States as over 88 000 people die every year from alcohol-related causes. Research is being conducted to understand the etiology of alcohol consumption and to develop strategies to decrease high-risk consumption and its consequences, but there are still important gaps in determining the main factors that influence the consumption behaviors throughout the drinking event. There is a need for methodologies that allow us not only to identify such factors but also to have a comprehensive understanding of how they are connected and how they affect the dynamical evolution of a drinking event. In this paper, we use previous empirical findings from laboratory and field studies to build a mathematical model of the blood alcohol concentration dynamics in individuals that are in drinking events. We characterize these dynamics as the result of the interaction between a decision-making system and the metabolic process for alcohol. We provide a model of the metabolic process for arbitrary alcohol intake patterns and a characterization of the mechanisms that drive the decision-making process of a drinker during the drinking event. We use computational simulations and Lyapunov stability theory to analyze the effects of the parameters of the model on the blood alcohol concentration dynamics that are characterized. Also, we propose a methodology to inform the model using data collected in situ and to make estimations that provide additional information to the analysis. We show how this model allows us to analyze and predict previously observed behaviors, to design new approaches for the collection of data that improves the construction of the model, and help with the design of interventions.

  2. Propagating Water Quality Analysis Uncertainty Into Resource Management Decisions Through Probabilistic Modeling

    Science.gov (United States)

    Gronewold, A. D.; Wolpert, R. L.; Reckhow, K. H.

    2007-12-01

    Most probable number (MPN) and colony-forming-unit (CFU) are two estimates of fecal coliform bacteria concentration commonly used as measures of water quality in United States shellfish harvesting waters. The MPN is the maximum likelihood estimate (or MLE) of the true fecal coliform concentration based on counts of non-sterile tubes in serial dilution of a sample aliquot, indicating bacterial metabolic activity. The CFU is the MLE of the true fecal coliform concentration based on the number of bacteria colonies emerging on a growth plate after inoculation from a sample aliquot. Each estimating procedure has intrinsic variability and is subject to additional uncertainty arising from minor variations in experimental protocol. Several versions of each procedure (using different sized aliquots or different numbers of tubes, for example) are in common use, each with its own levels of probabilistic and experimental error and uncertainty. It has been observed empirically that the MPN procedure is more variable than the CFU procedure, and that MPN estimates are somewhat higher on average than CFU estimates, on split samples from the same water bodies. We construct a probabilistic model that provides a clear theoretical explanation for the observed variability in, and discrepancy between, MPN and CFU measurements. We then explore how this variability and uncertainty might propagate into shellfish harvesting area management decisions through a two-phased modeling strategy. First, we apply our probabilistic model in a simulation-based analysis of future water quality standard violation frequencies under alternative land use scenarios, such as those evaluated under guidelines of the total maximum daily load (TMDL) program. Second, we apply our model to water quality data from shellfish harvesting areas which at present are closed (either conditionally or permanently) to shellfishing, to determine if alternative laboratory analysis procedures might have led to different

  3. [A prediction model for internet game addiction in adolescents: using a decision tree analysis].

    Science.gov (United States)

    Kim, Ki Sook; Kim, Kyung Hee

    2010-06-01

    This study was designed to build a theoretical frame to provide practical help to prevent and manage adolescent internet game addiction by developing a prediction model through a comprehensive analysis of related factors. The participants were 1,318 students studying in elementary, middle, and high schools in Seoul and Gyeonggi Province, Korea. Collected data were analyzed using the SPSS program. Decision Tree Analysis using the Clementine program was applied to build an optimum and significant prediction model to predict internet game addiction related to various factors, especially parent related factors. From the data analyses, the prediction model for factors related to internet game addiction presented with 5 pathways. Causative factors included gender, type of school, siblings, economic status, religion, time spent alone, gaming place, payment to Internet café, frequency, duration, parent's ability to use internet, occupation (mother), trust (father), expectations regarding adolescent's study (mother), supervising (both parents), rearing attitude (both parents). The results suggest preventive and managerial nursing programs for specific groups by path. Use of this predictive model can expand the role of school nurses, not only in counseling addicted adolescents but also, in developing and carrying out programs with parents and approaching adolescents individually through databases and computer programming.

  4. Analysis of a decision model in the context of equilibrium pricing and order book pricing

    Science.gov (United States)

    Wagner, D. C.; Schmitt, T. A.; Schäfer, R.; Guhr, T.; Wolf, D. E.

    2014-12-01

    An agent-based model for financial markets has to incorporate two aspects: decision making and price formation. We introduce a simple decision model and consider its implications in two different pricing schemes. First, we study its parameter dependence within a supply-demand balance setting. We find realistic behavior in a wide parameter range. Second, we embed our decision model in an order book setting. Here, we observe interesting features which are not present in the equilibrium pricing scheme. In particular, we find a nontrivial behavior of the order book volumes which reminds of a trend switching phenomenon. Thus, the decision making model alone does not realistically represent the trading and the stylized facts. The order book mechanism is crucial.

  5. Multicriteria decision analysis: Overview and implications for environmental decision making

    Science.gov (United States)

    Hermans, Caroline M.; Erickson, Jon D.; Erickson, Jon D.; Messner, Frank; Ring, Irene

    2007-01-01

    Environmental decision making involving multiple stakeholders can benefit from the use of a formal process to structure stakeholder interactions, leading to more successful outcomes than traditional discursive decision processes. There are many tools available to handle complex decision making. Here we illustrate the use of a multicriteria decision analysis (MCDA) outranking tool (PROMETHEE) to facilitate decision making at the watershed scale, involving multiple stakeholders, multiple criteria, and multiple objectives. We compare various MCDA methods and their theoretical underpinnings, examining methods that most realistically model complex decision problems in ways that are understandable and transparent to stakeholders.

  6. Plutonium-238 Decision Analysis

    International Nuclear Information System (INIS)

    Brown, Mike; Lechel, David J.; Leigh, C.D.

    1999-01-01

    Five transuranic (TRU) waste sites in the Department of Energy (DOE) complex, collectively, have more than 2,100 cubic meters of Plutonium-238 (Pu-238) TRU waste that exceed the wattage restrictions of the Transuranic Package Transporter-II (TRUPACT-11). The Waste Isolation Pilot Plant (WIPP) is being developed by the DOE as a repository for TRU waste. With the Waste Isolation Pilot Plant (WIPP) opening in 1999, these sites are faced with a need to develop waste management practices that will enable the transportation of Pu-238 TRU waste to WIPP for disposal. This paper describes a decision analysis that provided a logical framework for addressing the Pu-238 TRU waste issue. The insights that can be gained by performing a formalized decision analysis are multifold. First and foremost, the very process. of formulating a decision tree forces the decision maker into structured, logical thinking where alternatives can be evaluated one against the other using a uniform set of criteria. In the process of developing the decision tree for transportation of Pu-238 TRU waste, several alternatives were eliminated and the logical order for decision making was discovered. Moreover, the key areas of uncertainty for proposed alternatives were identified and quantified. The decision analysis showed that the DOE can employ a combination approach where they will (1) use headspace gas analyses to show that a fraction of the Pu-238 TRU waste drums are no longer generating hydrogen gas and can be shipped to WIPP ''as-is'', (2) use drums and bags with advanced filter systems to repackage Pu-238 TRU waste drums that are still generating hydrogen, and (3) add hydrogen getter materials to the inner containment vessel of the TRUPACT-11to relieve the build-up of hydrogen gas during transportation of the Pu-238 TRU waste drums

  7. Single- versus dual-process models of lexical decision performance: insights from response time distributional analysis.

    Science.gov (United States)

    Yap, Melvin J; Balota, David A; Cortese, Michael J; Watson, Jason M

    2006-12-01

    This article evaluates 2 competing models that address the decision-making processes mediating word recognition and lexical decision performance: a hybrid 2-stage model of lexical decision performance and a random-walk model. In 2 experiments, nonword type and word frequency were manipulated across 2 contrasts (pseudohomophone-legal nonword and legal-illegal nonword). When nonwords became more wordlike (i.e., BRNTA vs. BRANT vs. BRANE), response latencies to nonwords were slowed and the word frequency effect increased. More important, distributional analyses revealed that the Nonword Type = Word Frequency interaction was modulated by different components of the response time distribution, depending on the specific nonword contrast. A single-process random-walk model was able to account for this particular set of findings more successfully than the hybrid 2-stage model. (c) 2006 APA, all rights reserved.

  8. Cost utility analysis of endoscopic biliary stent in unresectable hilar cholangiocarcinoma: decision analytic modeling approach.

    Science.gov (United States)

    Sangchan, Apichat; Chaiyakunapruk, Nathorn; Supakankunti, Siripen; Pugkhem, Ake; Mairiang, Pisaln

    2014-01-01

    Endoscopic biliary drainage using metal and plastic stent in unresectable hilar cholangiocarcinoma (HCA) is widely used but little is known about their cost-effectiveness. This study evaluated the cost-utility of endoscopic metal and plastic stent drainage in unresectable complex, Bismuth type II-IV, HCA patients. Decision analytic model, Markov model, was used to evaluate cost and quality-adjusted life year (QALY) of endoscopic biliary drainage in unresectable HCA. Costs of treatment and utilities of each Markov state were retrieved from hospital charges and unresectable HCA patients from tertiary care hospital in Thailand, respectively. Transition probabilities were derived from international literature. Base case analyses and sensitivity analyses were performed. Under the base-case analysis, metal stent is more effective but more expensive than plastic stent. An incremental cost per additional QALY gained is 192,650 baht (US$ 6,318). From probabilistic sensitivity analysis, at the willingness to pay threshold of one and three times GDP per capita or 158,000 baht (US$ 5,182) and 474,000 baht (US$ 15,546), the probability of metal stent being cost-effective is 26.4% and 99.8%, respectively. Based on the WHO recommendation regarding the cost-effectiveness threshold criteria, endoscopic metal stent drainage is cost-effective compared to plastic stent in unresectable complex HCA.

  9. Decision making model design for antivirus software selection using Factor Analysis and Analytical Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Nurhayati Ai

    2018-01-01

    Full Text Available Virus spread increase significantly through the internet in 2017. One of the protection method is using antivirus software. The wide variety of antivirus software in the market tends to creating confusion among consumer. Selecting the right antivirus according to their needs has become difficult. This is the reason we conduct our research. We formulate a decision making model for antivirus software consumer. The model is constructed by using factor analysis and AHP method. First we spread questionnaires to consumer, then from those questionnaires we identified 16 variables that needs to be considered on selecting antivirus software. This 16 variables then divided into 5 factors by using factor analysis method in SPSS software. These five factors are security, performance, internal, time and capacity. To rank those factors we spread questionnaires to 6 IT expert then the data is analyzed using AHP method. The result is that performance factors gained the highest rank from all of the other factors. Thus, consumer can select antivirus software by judging the variables in the performance factors. Those variables are software loading speed, user friendly, no excessive memory use, thorough scanning, and scanning virus fast and accurately.

  10. Path analysis and multi-criteria decision making: an approach for multivariate model selection and analysis in health.

    Science.gov (United States)

    Vasconcelos, A G; Almeida, R M; Nobre, F F

    2001-08-01

    This paper introduces an approach that includes non-quantitative factors for the selection and assessment of multivariate complex models in health. A goodness-of-fit based methodology combined with fuzzy multi-criteria decision-making approach is proposed for model selection. Models were obtained using the Path Analysis (PA) methodology in order to explain the interrelationship between health determinants and the post-neonatal component of infant mortality in 59 municipalities of Brazil in the year 1991. Socioeconomic and demographic factors were used as exogenous variables, and environmental, health service and agglomeration as endogenous variables. Five PA models were developed and accepted by statistical criteria of goodness-of fit. These models were then submitted to a group of experts, seeking to characterize their preferences, according to predefined criteria that tried to evaluate model relevance and plausibility. Fuzzy set techniques were used to rank the alternative models according to the number of times a model was superior to ("dominated") the others. The best-ranked model explained above 90% of the endogenous variables variation, and showed the favorable influences of income and education levels on post-neonatal mortality. It also showed the unfavorable effect on mortality of fast population growth, through precarious dwelling conditions and decreased access to sanitation. It was possible to aggregate expert opinions in model evaluation. The proposed procedure for model selection allowed the inclusion of subjective information in a clear and systematic manner.

  11. Children's Lead Exposure: A Multimedia Modeling Analysis to Guide Public Health Decision-Making.

    Science.gov (United States)

    Zartarian, Valerie; Xue, Jianping; Tornero-Velez, Rogelio; Brown, James

    2017-09-12

    Drinking water and other sources for lead are the subject of public health concerns around the Flint, Michigan, drinking water and East Chicago, Indiana, lead in soil crises. In 2015, the U.S. Environmental Protection Agency (EPA)'s National Drinking Water Advisory Council (NDWAC) recommended establishment of a "health-based, household action level" for lead in drinking water based on children's exposure. The primary objective was to develop a coupled exposure-dose modeling approach that can be used to determine what drinking water lead concentrations keep children's blood lead levels (BLLs) below specified values, considering exposures from water, soil, dust, food, and air. Related objectives were to evaluate the coupled model estimates using real-world blood lead data, to quantify relative contributions by the various media, and to identify key model inputs. A modeling approach using the EPA's Stochastic Human Exposure and Dose Simulation (SHEDS)-Multimedia and Integrated Exposure Uptake and Biokinetic (IEUBK) models was developed using available data. This analysis for the U.S. population of young children probabilistically simulated multimedia exposures and estimated relative contributions of media to BLLs across all population percentiles for several age groups. Modeled BLLs compared well with nationally representative BLLs (0-23% relative error). Analyses revealed relative importance of soil and dust ingestion exposure pathways and associated Pb intake rates; water ingestion was also a main pathway, especially for infants. This methodology advances scientific understanding of the relationship between lead concentrations in drinking water and BLLs in children. It can guide national health-based benchmarks for lead and related community public health decisions. https://doi.org/10.1289/EHP1605.

  12. Change Analysis and Decision Tree Based Detection Model for Residential Objects across Multiple Scales

    Directory of Open Access Journals (Sweden)

    CHEN Liyan

    2018-03-01

    Full Text Available Change analysis and detection plays important role in the updating of multi-scale databases.When overlap an updated larger-scale dataset and a to-be-updated smaller-scale dataset,people usually focus on temporal changes caused by the evolution of spatial entities.Little attention is paid to the representation changes influenced by map generalization.Using polygonal building data as an example,this study examines the changes from different perspectives,such as the reasons for their occurrence,their performance format.Based on this knowledge,we employ decision tree in field of machine learning to establish a change detection model.The aim of the proposed model is to distinguish temporal changes that need to be applied as updates to the smaller-scale dataset from representation changes.The proposed method is validated through tests using real-world building data from Guangzhou city.The experimental results show the overall precision of change detection is more than 90%,which indicates our method is effective to identify changed objects.

  13. Multi-criteria Decision Analysis to Model Ixodes ricinus Habitat Suitability.

    Science.gov (United States)

    Rousseau, Raphaël; McGrath, Guy; McMahon, Barry J; Vanwambeke, Sophie O

    2017-09-01

    Tick-borne diseases present a major threat to both human and livestock health throughout Europe. The risk of infection is directly related to the presence of its vector. Thereby it is important to know their distribution, which is strongly associated with environmental factors: the presence and availability of a suitable habitat, of a suitable climate and of hosts. The present study models the habitat suitability for Ixodes ricinus in Ireland, where data on tick distribution are scarce. Tick habitat suitability was estimated at a coarse scale (10 km) with a multi-criteria decision analysis (MCDA) method according to four different scenarios (depending on the variables used and on the weights granted to each of them). The western part of Ireland and the Wicklow mountains in the East were estimated to be the most suitable areas for I. ricinus in the island. There was a good level of agreement between results from the MCDA and recorded tick presence. The different scenarios did not affect the spatial outputs substantially. The current study suggests that tick habitat suitability can be mapped accurately at a coarse scale in a data-scarce context using knowledge-based methods. It can serve as a guideline for future countrywide sampling that would help to determine local risk of tick presence and refining knowledge on tick habitat suitability in Ireland.

  14. Energy systems analysis modeling as a decision tool; Systemanalytisk energimodell som beslutsverktyg. Borlaenge och andra kommuner i Dalarna

    Energy Technology Data Exchange (ETDEWEB)

    Byman, Karin

    1999-10-01

    The hypothesis is that `a system optimisation model can be a powerful tool to produce basic data for strategic decision making in a local energy company`. Another question is: do the companies trust the results? The model used is MODEST, which is a model for energy-system optimisation, built on linear programming. The local energy system in the municipality of Borlaenge, has been analysed by means of MODEST and at the same time a traditional study has been carried out by an experienced energy-consultant. Both investigations were made under exactly the same conditions but totally independent of each other. Both studies came to same conclusions, and this was very important for the continued work. A more extensive investigation was made when five communities, including Borlaenge, joined to analyse the optimal energy supply in the region of Dalarna. The other communities are Hedemora, Saeter, Avesta and Falun. By following the decision-making process in Borlaenge and the other communities it has been possible to judge the usefulness of the MODEST model and the concept of energy system analyses that goes with it. The energy companies were interviewed about their experiences of the model. They all agree that they have confidence in the model, as the results correspond with their own calculations and knowledge of their energy systems. The process is easy to follow and the inputs to the model are data that always have to be processed in an investigation of a new investment or other changes of the energy supply. The result of the analysis is easy to comprehend. Regarding Borlaenge a decisive strategic decision has not yet been made. That depends on external insecurities on the energy market which are outside the modelling process. Not making a decision is also a strategic act. Based on the results of the analysis that have been made during the period of this work, 1997-1999, Borlaenge Energy has decided to postpone the final decision for two or three years. The president of

  15. Decision-making models in the analysis of portal films: a clinical pilot study

    International Nuclear Information System (INIS)

    See, A.; Johansen, J.; Hamilton, C.; Bydder, S.A.; Hawkins, J.; Roff, M.; Denham, J.; Kron, T.

    2000-01-01

    Portal films continue to play an important role in the verification of radiotherapy treatment. There is still some discussion, however, as to what action should be taken after a port film has shown a radiation field deviation from the prescribed volume. It was the aim of the present pilot study to investigate the performance of three decision-making models ('Amsterdam', 'Quebec' and 'Newcastle') and an expert panel basing their decision on intuition rather than formal rules after portal film acquisition in a clinical setting. Portal films were acquired on every day during the first week of treatment for five head and neck and five prostate cancer patients (diagnostic phase). If required, the field position was modified according to our normal practice following the recommendation of the expert panel. In order to analyse the results of the models, however, additional port films were taken in the following 3 treatment weeks with the patient moved as required by the different models (intervention phase). The portal films were taken over 4 consecutive days, positioning the patient according to each of the different models on one day each. None of the models diagnosed a field misplacement in the head and neck patients, while the 'Amsterdam' and 'Quebec' models predicted a move in one prostate patient. The 'Newcastle' model, which is based on Hotelling's T 2 statistic, proved to be more sensitive and diagnosed a systematic displacement for three prostate patients. The intervention phase confirmed the diagnosis of the model, even if the three portal films taken with the patient position adjusted as required by the model proved to be insufficient to demonstrate an improvement. The 'Newcastle' model does not rely on assumptions about the random movement of patients and requires five portal films before a decision can be reached. This approach lends itself well to incorporation into electronic portal imaging 'packages', where repeated image acquisitions present no logistical

  16. Risk-based systems analysis for emerging technologies: Applications of a technology risk assessment model to public decision making

    International Nuclear Information System (INIS)

    Quadrel, M.J.; Fowler, K.M.; Cameron, R.; Treat, R.J.; McCormack, W.D.; Cruse, J.

    1995-01-01

    The risk-based systems analysis model was designed to establish funding priorities among competing technologies for tank waste remediation. The model addresses a gap in the Department of Energy's (DOE's) ''toolkit'' for establishing funding priorities among emerging technologies by providing disciplined risk and cost assessments of candidate technologies within the context of a complete remediation system. The model is comprised of a risk and cost assessment and a decision interface. The former assesses the potential reductions in risk and cost offered by new technology relative to the baseline risk and cost of an entire system. The latter places this critical information in context of other values articulated by decision makers and stakeholders in the DOE system. The risk assessment portion of the model is demonstrated for two candidate technologies for tank waste retrieval (arm-based mechanical retrieval -- the ''long reach arm'') and subsurface barriers (close-coupled chemical barriers). Relative changes from the base case in cost and risk are presented for these two technologies to illustrate how the model works. The model and associated software build on previous work performed for DOE's Office of Technology Development and the former Underground Storage Tank Integrated Demonstration, and complement a decision making tool presented at Waste Management 1994 for integrating technical judgements and non-technical (stakeholder) values when making technology funding decisions

  17. Ranking environmental projects model based on multicriteria decision-making and the weight sensitivity analysis

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    With the fast growth of Chinese economic,more and more capital will be invested in environmental projects.How to select the environmental investment projects(alternatives)for obtaining the best environmental quality and economic benefits is an important problem for the decision makers.The purpose of this paper is to develop a decision-making model to rank a finite number of alternatives with several and sometimes conflicting criteria.A model for ranking the projects of municipal sewage treatment plants is proposed by using exports' information and the data of the real projects.And,the ranking result is given based on the PROMETHEE method. Furthermore,by means of the concept of the weight stability intervals(WSI),the sensitivity of the ranking results to the size of criteria values and the change of weights value of criteria are discussed.The result shows that some criteria,such as"proportion of benefit to projoct cost",will influence the ranking result of alternatives very strong while others not.The influence are not only from the value of criterion but also from the changing the weight of criterion.So,some criteria such as"proportion of benefit to projoct cost" are key critera for ranking the projects. Decision makers must be cautious to them.

  18. Multiscale modelling and analysis of collective decision making in swarm robotics.

    Science.gov (United States)

    Vigelius, Matthias; Meyer, Bernd; Pascoe, Geoffrey

    2014-01-01

    We present a unified approach to describing certain types of collective decision making in swarm robotics that bridges from a microscopic individual-based description to aggregate properties. Our approach encompasses robot swarm experiments, microscopic and probabilistic macroscopic-discrete simulations as well as an analytic mathematical model. Following up on previous work, we identify the symmetry parameter, a measure of the progress of the swarm towards a decision, as a fundamental integrated swarm property and formulate its time evolution as a continuous-time Markov process. Contrary to previous work, which justified this approach only empirically and a posteriori, we justify it from first principles and derive hard limits on the parameter regime in which it is applicable.

  19. Multiscale Modelling and Analysis of Collective Decision Making in Swarm Robotics

    Science.gov (United States)

    Vigelius, Matthias; Meyer, Bernd; Pascoe, Geoffrey

    2014-01-01

    We present a unified approach to describing certain types of collective decision making in swarm robotics that bridges from a microscopic individual-based description to aggregate properties. Our approach encompasses robot swarm experiments, microscopic and probabilistic macroscopic-discrete simulations as well as an analytic mathematical model. Following up on previous work, we identify the symmetry parameter, a measure of the progress of the swarm towards a decision, as a fundamental integrated swarm property and formulate its time evolution as a continuous-time Markov process. Contrary to previous work, which justified this approach only empirically and a posteriori, we justify it from first principles and derive hard limits on the parameter regime in which it is applicable. PMID:25369026

  20. Decision Analysis Technique

    Directory of Open Access Journals (Sweden)

    Hammad Dabo Baba

    2014-01-01

    Full Text Available One of the most significant step in building structure maintenance decision is the physical inspection of the facility to be maintained. The physical inspection involved cursory assessment of the structure and ratings of the identified defects based on expert evaluation. The objective of this paper is to describe present a novel approach to prioritizing the criticality of physical defects in a residential building system using multi criteria decision analysis approach. A residential building constructed in 1985 was considered in this study. Four criteria which includes; Physical Condition of the building system (PC, Effect on Asset (EA, effect on Occupants (EO and Maintenance Cost (MC are considered in the inspection. The building was divided in to nine systems regarded as alternatives. Expert's choice software was used in comparing the importance of the criteria against the main objective, whereas structured Proforma was used in quantifying the defects observed on all building systems against each criteria. The defects severity score of each building system was identified and later multiplied by the weight of the criteria and final hierarchy was derived. The final ranking indicates that, electrical system was considered the most critical system with a risk value of 0.134 while ceiling system scored the lowest risk value of 0.066. The technique is often used in prioritizing mechanical equipment for maintenance planning. However, result of this study indicates that the technique could be used in prioritizing building systems for maintenance planning

  1. Sensor fault analysis using decision theory and data-driven modeling of pressurized water reactor subsystems

    International Nuclear Information System (INIS)

    Upadhyaya, B.R.; Skorska, M.

    1984-01-01

    Instrument fault detection and estimation is important for process surveillance, control, and safety functions of a power plant. The method incorporates the dual-hypotheses decision procedure and system characterization using data-driven time-domain models of signals representing the system. The multivariate models can be developed on-line and can be adapted to changing system conditions. For the method to be effective, specific subsystems of pressurized water reactors were considered, and signal selection was made such that a strong causal relationship exists among the measured variables. The technique is applied to the reactor core subsystem of the loss-of-fluid test reactor using in-core neutron detector and core-exit thermocouple signals. Thermocouple anomalies such as bias error, noise error, and slow drift in the sensor are detected and estimated using appropriate measurement models

  2. An analysis of medical decision making

    International Nuclear Information System (INIS)

    Lusted, L.B.

    1977-01-01

    Medical decision-making studies continue to focus on two questions: How do physicians make decisions and how should physicians make decisions. Researchers pursuing the first question emphasize human cognitive processes and the programming of symbol systems to model the observed human behaviour. Those researchers concentrating on the second question assume that there is a standard of performance against which physicians' decisions can be judged, and to help the physician improve his performance an array of tools is proposed. These tools include decision trees, Bayesian analysis, decision matrices, receiver operating characteristic (ROC) analysis, and cost-benefit considerations including utility measures. Both questions must be answered in an ethical context where ethics and decision analysis are intertwined. (author)

  3. Improved TOPSIS decision model for NPP emergencies

    International Nuclear Information System (INIS)

    Zhang Jin; Liu Feng; Huang Lian

    2011-01-01

    In this paper,an improved decision model is developed for its use as a tool to respond to emergencies at nuclear power plants. Given the complexity of multi-attribute emergency decision-making on nuclear accident, the improved TOPSIS method is used to build a decision-making model that integrates subjective weight and objective weight of each evaluation index. A comparison between the results of this new model and two traditional methods of fuzzy hierarchy analysis method and weighted analysis method demonstrates that the improved TOPSIS model has a better evaluation effect. (authors)

  4. Optimising Transport Decision Making using Customised Decision Models and Decision Conferences

    DEFF Research Database (Denmark)

    Barfod, Michael Bruhn

    The subject of this Ph.D. thesis entitled “Optimising Transport Decision Making using Customised Decision Models and Decision Conferences” is multi-criteria decision analysis (MCDA) and decision support in the context of transport infrastructure assessments. Despite the fact that large amounts...... is concerned with the insufficiency of conventional cost-benefit analysis (CBA), and proposes the use of MCDA as a supplementing tool in order to also capture impacts of a more strategic character in the appraisals and hence make more use of the often large efforts put in the preliminary examinations. MCDA...... and rail to bike transport projects. Two major concerns have been to propose an examination process that can be used in situations where complex decision problems need to be addressed by experts as well as non-experts in decision making, and to identify appropriate assessment techniques to be used...

  5. A History of Sandia’s Water Decision Modeling and Analysis Program

    Energy Technology Data Exchange (ETDEWEB)

    Lowry, Thomas Stephen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Earth Systems Analysis; Pate, Ronald C. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Earth Systems Analysis

    2016-10-01

    This document provides a brief narrative, and selected project descriptions, that represent Sandia’s history involving data, modeling, and analysis related to water, energy-water nexus, and energy-water-agriculture nexus within the context of climate change. Sandia National Laboratories has been engaged since the early-1990s with program development involving data, modeling, and analysis projects that address the interdependent issues, risks, and technology-based mitigations associated with increasing demands and stresses being placed on energy, water, and agricultural/food resources, and the related impacts on their security and sustainability in the face of both domestic and global population growth, expanding economic development, and climate change.

  6. An integrated approach to human reliability analysis -- decision analytic dynamic reliability model

    International Nuclear Information System (INIS)

    Holmberg, J.; Hukki, K.; Norros, L.; Pulkkinen, U.; Pyy, P.

    1999-01-01

    The reliability of human operators in process control is sensitive to the context. In many contemporary human reliability analysis (HRA) methods, this is not sufficiently taken into account. The aim of this article is that integration between probabilistic and psychological approaches in human reliability should be attempted. This is achieved first, by adopting such methods that adequately reflect the essential features of the process control activity, and secondly, by carrying out an interactive HRA process. Description of the activity context, probabilistic modeling, and psychological analysis form an iterative interdisciplinary sequence of analysis in which the results of one sub-task maybe input to another. The analysis of the context is carried out first with the help of a common set of conceptual tools. The resulting descriptions of the context promote the probabilistic modeling, through which new results regarding the probabilistic dynamics can be achieved. These can be incorporated in the context descriptions used as reference in the psychological analysis of actual performance. The results also provide new knowledge of the constraints of activity, by providing information of the premises of the operator's actions. Finally, the stochastic marked point process model gives a tool, by which psychological methodology may be interpreted and utilized for reliability analysis

  7. A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis

    NARCIS (Netherlands)

    Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L.; Postmus, Douwe

    2011-01-01

    Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multicriteria model that fully takes into account the evidence on efficacy and adverse drug

  8. Applying air pollution modelling within a multi-criteria decision analysis framework to evaluate UK air quality policies

    Science.gov (United States)

    Chalabi, Zaid; Milojevic, Ai; Doherty, Ruth M.; Stevenson, David S.; MacKenzie, Ian A.; Milner, James; Vieno, Massimo; Williams, Martin; Wilkinson, Paul

    2017-10-01

    A decision support system for evaluating UK air quality policies is presented. It combines the output from a chemistry transport model, a health impact model and other impact models within a multi-criteria decision analysis (MCDA) framework. As a proof-of-concept, the MCDA framework is used to evaluate and compare idealized emission reduction policies in four sectors (combustion in energy and transformation industries, non-industrial combustion plants, road transport and agriculture) and across six outcomes or criteria (mortality, health inequality, greenhouse gas emissions, biodiversity, crop yield and air quality legal compliance). To illustrate a realistic use of the MCDA framework, the relative importance of the criteria were elicited from a number of stakeholders acting as proxy policy makers. In the prototype decision problem, we show that reducing emissions from industrial combustion (followed very closely by road transport and agriculture) is more advantageous than equivalent reductions from the other sectors when all the criteria are taken into account. Extensions of the MCDA framework to support policy makers in practice are discussed.

  9. Assessing the economic impact of paternal involvement: a comparison of the generalized linear model versus decision analysis trees.

    Science.gov (United States)

    Salihu, Hamisu M; Salemi, Jason L; Nash, Michelle C; Chandler, Kristen; Mbah, Alfred K; Alio, Amina P

    2014-08-01

    Lack of paternal involvement has been shown to be associated with adverse pregnancy outcomes, including infant morbidity and mortality, but the impact on health care costs is unknown. Various methodological approaches have been used in cost minimization and cost effectiveness analyses and it remains unclear how cost estimates vary according to the analytic strategy adopted. We illustrate a methodological comparison of decision analysis modeling and generalized linear modeling (GLM) techniques using a case study that assesses the cost-effectiveness of potential father involvement interventions. We conducted a 12-year retrospective cohort study using a statewide enhanced maternal-infant database that contains both clinical and nonclinical information. A missing name for the father on the infant's birth certificate was used as a proxy for lack of paternal involvement, the main exposure of this study. Using decision analysis modeling and GLM, we compared all infant inpatient hospitalization costs over the first year of life. Costs were calculated from hospital charges using department-level cost-to-charge ratios and were adjusted for inflation. In our cohort of 2,243,891 infants, 9.2% had a father uninvolved during pregnancy. Lack of paternal involvement was associated with higher rates of preterm birth, small-for-gestational age, and infant morbidity and mortality. Both analytic approaches estimate significantly higher per-infant costs for father uninvolved pregnancies (decision analysis model: $1,827, GLM: $1,139). This paper provides sufficient evidence that healthcare costs could be significantly reduced through enhanced father involvement during pregnancy, and buttresses the call for a national program to involve fathers in antenatal care.

  10. Modeling as a Decision-Making Process

    Science.gov (United States)

    Bleiler-Baxter, Sarah K.; Stephens, D. Christopher; Baxter, Wesley A.; Barlow, Angela T.

    2017-01-01

    The goal in this article is to support teachers in better understanding what it means to model with mathematics by focusing on three key decision-making processes: Simplification, Relationship Mapping, and Situation Analysis. The authors use the Theme Park task to help teachers develop a vision of how students engage in these three decision-making…

  11. Decision strategy research: system analysis

    International Nuclear Information System (INIS)

    Carle, B.

    2000-01-01

    The objective of SCK-CEN's R and D programme on decision strategies is (1) to develop theories, methods and software tools which help decision makers shape, analyse and understand their decisions; (2) to study group processes in decision making; (3) to apply theories, methods and tools in a context related to nuclear emergency preparedness and more generally to support in a context dealing with ionising radiation; (4) to increase SCK-CEN's knowledge on general emergency preparedness and to introduce SCK-CEN staff to computer supported decision techniques. Ongoing R and D has two components: (1) the study of the use of information and knowledge transfer in group decision processes, and more specific studying important factors when computers are used as information source and communication tool; and (2) the study of preference modelling individually and during group decision processes. Principal achievements in 1999 are described

  12. Decision strategy research: system analysis

    Energy Technology Data Exchange (ETDEWEB)

    Carle, B

    2000-07-01

    The objective of SCK-CEN's R and D programme on decision strategies is (1) to develop theories, methods and software tools which help decision makers shape, analyse and understand their decisions; (2) to study group processes in decision making; (3) to apply theories, methods and tools in a context related to nuclear emergency preparedness and more generally to support in a context dealing with ionising radiation; (4) to increase SCK-CEN's knowledge on general emergency preparedness and to introduce SCK-CEN staff to computer supported decision techniques. Ongoing R and D has two components: (1) the study of the use of information and knowledge transfer in group decision processes, and more specific studying important factors when computers are used as information source and communication tool; and (2) the study of preference modelling individually and during group decision processes. Principal achievements in 1999 are described.

  13. Probabilistic sensitivity analysis on Markov models with uncertain transition probabilities: an application in evaluating treatment decisions for type 2 diabetes.

    Science.gov (United States)

    Zhang, Yuanhui; Wu, Haipeng; Denton, Brian T; Wilson, James R; Lobo, Jennifer M

    2017-10-27

    Markov models are commonly used for decision-making studies in many application domains; however, there are no widely adopted methods for performing sensitivity analysis on such models with uncertain transition probability matrices (TPMs). This article describes two simulation-based approaches for conducting probabilistic sensitivity analysis on a given discrete-time, finite-horizon, finite-state Markov model using TPMs that are sampled over a specified uncertainty set according to a relevant probability distribution. The first approach assumes no prior knowledge of the probability distribution, and each row of a TPM is independently sampled from the uniform distribution on the row's uncertainty set. The second approach involves random sampling from the (truncated) multivariate normal distribution of the TPM's maximum likelihood estimators for its rows subject to the condition that each row has nonnegative elements and sums to one. The two sampling methods are easily implemented and have reasonable computation times. A case study illustrates the application of these methods to a medical decision-making problem involving the evaluation of treatment guidelines for glycemic control of patients with type 2 diabetes, where natural variation in a patient's glycated hemoglobin (HbA1c) is modeled as a Markov chain, and the associated TPMs are subject to uncertainty.

  14. A Diffusion Model Analysis of Decision Biases Affecting Delayed Recognition of Emotional Stimuli

    Science.gov (United States)

    Bowen, Holly J.; Spaniol, Julia; Patel, Ronak; Voss, Andreas

    2016-01-01

    Previous empirical work suggests that emotion can influence accuracy and cognitive biases underlying recognition memory, depending on the experimental conditions. The current study examines the effects of arousal and valence on delayed recognition memory using the diffusion model, which allows the separation of two decision biases thought to underlie memory: response bias and memory bias. Memory bias has not been given much attention in the literature but can provide insight into the retrieval dynamics of emotion modulated memory. Participants viewed emotional pictorial stimuli; half were given a recognition test 1-day later and the other half 7-days later. Analyses revealed that emotional valence generally evokes liberal responding, whereas high arousal evokes liberal responding only at a short retention interval. The memory bias analyses indicated that participants experienced greater familiarity with high-arousal compared to low-arousal items and this pattern became more pronounced as study-test lag increased; positive items evoke greater familiarity compared to negative and this pattern remained stable across retention interval. The findings provide insight into the separate contributions of valence and arousal to the cognitive mechanisms underlying delayed emotion modulated memory. PMID:26784108

  15. 2018 Military Retirement Options: An Expected Net Present Value Decision Analysis Model

    Science.gov (United States)

    2017-03-23

    and the Operational Research Commons This Thesis is brought to you for free and open access by AFIT Scholar. It has been accepted for inclusion in...and build a representation of the model using Microsoft Excel 2016, Visual Basics for Applications ( VBA ), and Excel’s Data Analysis Toolkit. The...stream of future income. However, these DOD TSP contributions are not readily accessible to the member until they reach age 59.5 due to IRS

  16. Uncertainty Analysis of Coupled Socioeconomic-Cropping Models: Building Confidence in Climate Change Decision-Support Tools for Local Stakeholders

    Science.gov (United States)

    Malard, J. J.; Rojas, M.; Adamowski, J. F.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

    2015-12-01

    While cropping models represent the biophysical aspects of agricultural systems, system dynamics modelling offers the possibility of representing the socioeconomic (including social and cultural) aspects of these systems. The two types of models can then be coupled in order to include the socioeconomic dimensions of climate change adaptation in the predictions of cropping models.We develop a dynamically coupled socioeconomic-biophysical model of agricultural production and its repercussions on food security in two case studies from Guatemala (a market-based, intensive agricultural system and a low-input, subsistence crop-based system). Through the specification of the climate inputs to the cropping model, the impacts of climate change on the entire system can be analysed, and the participatory nature of the system dynamics model-building process, in which stakeholders from NGOs to local governmental extension workers were included, helps ensure local trust in and use of the model.However, the analysis of climate variability's impacts on agroecosystems includes uncertainty, especially in the case of joint physical-socioeconomic modelling, and the explicit representation of this uncertainty in the participatory development of the models is important to ensure appropriate use of the models by the end users. In addition, standard model calibration, validation, and uncertainty interval estimation techniques used for physically-based models are impractical in the case of socioeconomic modelling. We present a methodology for the calibration and uncertainty analysis of coupled biophysical (cropping) and system dynamics (socioeconomic) agricultural models, using survey data and expert input to calibrate and evaluate the uncertainty of the system dynamics as well as of the overall coupled model. This approach offers an important tool for local decision makers to evaluate the potential impacts of climate change and their feedbacks through the associated socioeconomic system.

  17. ​An Overview on the Principles of Decision Analysis and Economic Modeling in Healthcare and an Introduction to Advanced Software Treeage Pro 2011

    Directory of Open Access Journals (Sweden)

    Ali Imani

    2015-08-01

    Full Text Available Background and Objectives : Decision analysis models are conceptual framework for most of the cost - effectiveness (CEA and cost-utility (CUA analyses and this model increasingly plays an important role in decision making. The aim of this study was to improve the understanding and use of decision analysis and economic modeling techniques with a particular emphasis on decision trees and Markov modeling. Material and Methods : A review of the published literature was performed using the seven search engines and databases which include Web of Science, PubMed, Cochrane, Embase, EconLit, EBSCO and HEED with key words including: Decision Analysis, Health Economic Modeling and TreeAge and their combination to describe the structure, application, and limitations of the more popular decision analytic methods including decision trees, Markov models, and sensitivity analysis in healthcare. Results : We identified 19 relevant published articles. The results indicated that decision analytical models are widely used in economic evaluation of health care interventions with the objective of generating valuable information to assist health policy decision-makers to allocate scarce health care resources efficiently. Conclusion : Decision analytic modeling allows a rational, feasible, scientific, and timely approach to measure the efficiency of new medical technologies in health care by using the best available evidence of different sources to produce detailed estimates of the clinical and economic indicators. Despite TreeAge Pro software increasing use in developing countries as economic modeling studies of various health interventions, unfortunately its role and impact are not known in Iran yet. ​

  18. A Novel Clinical Prediction Model for Prognosis in Malignant Pleural Mesothelioma Using Decision Tree Analysis.

    Science.gov (United States)

    Brims, Fraser J H; Meniawy, Tarek M; Duffus, Ian; de Fonseka, Duneesha; Segal, Amanda; Creaney, Jenette; Maskell, Nicholas; Lake, Richard A; de Klerk, Nick; Nowak, Anna K

    2016-04-01

    Malignant pleural mesothelioma (MPM) is a rare cancer with a heterogeneous prognosis. Prognostic models are not widely utilized clinically. Classification and regression tree (CART) analysis examines the interaction of multiple variables with a given outcome. Between 2005 and 2014, all cases with pathologically confirmed MPM had routinely available histological, clinical, and laboratory characteristics recorded. Classification and regression tree analysis was performed using 29 variables with 18-month survival as the dependent variable. Risk groups were refined according to survival and clinical characteristics. The model was then tested on an external international cohort. A total of 482 cases were included in the derivation cohort; the median survival was 12.6 months, and the median age was 69 years. The model defined four risk groups with clear survival differences (p loss. The group with the best survival at 18 months (86.7% alive, median survival 34.0 months, termed risk group 1) had no weight loss, a hemoglobin level greater than 153 g/L, and a serum albumin level greater than 43 g/L. The group with the worst survival (0% alive, median survival 7.5 months, termed risk group 4d) had weight loss, a performance score of 0 or 1, and sarcomatoid histological characteristics. The C-statistic for the model was 0.761, and the sensitivity was 94.5%. Validation on 174 external cases confirmed the model's ability to discriminate between risk groups in an alternative data set with fair performance (C-statistic 0.68). We have developed and validated a simple, clinically relevant model to reliably discriminate patients at high and lower risk of death using routinely available variables from the time of diagnosis in unselected populations of patients with MPM. Copyright © 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

  19. Demonstration of a modelling-based multi-criteria decision analysis procedure for prioritisation of occupational risks from manufactured nanomaterials.

    Science.gov (United States)

    Hristozov, Danail; Zabeo, Alex; Alstrup Jensen, Keld; Gottardo, Stefania; Isigonis, Panagiotis; Maccalman, Laura; Critto, Andrea; Marcomini, Antonio

    2016-11-01

    Several tools to facilitate the risk assessment and management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed. This paper proposes such a quantitative risk prioritisation tool, based on a multi-criteria decision analysis algorithm, which combines advanced exposure and dose-response modelling to calculate margins of exposure (MoE) for a number of MN in order to rank their occupational risks. We demonstrated the tool in a number of workplace exposure scenarios (ES) involving the production and handling of nanoscale titanium dioxide, zinc oxide (ZnO), silver and multi-walled carbon nanotubes. The results of this application demonstrated that bag/bin filling, manual un/loading and dumping of large amounts of dry powders led to high emissions, which resulted in high risk associated with these ES. The ZnO MN revealed considerable hazard potential in vivo, which significantly influenced the risk prioritisation results. In order to study how variations in the input data affect our results, we performed probabilistic Monte Carlo sensitivity/uncertainty analysis, which demonstrated that the performance of the proposed model is stable against changes in the exposure and hazard input variables.

  20. Markov Decision Process Measurement Model.

    Science.gov (United States)

    LaMar, Michelle M

    2018-03-01

    Within-task actions can provide additional information on student competencies but are challenging to model. This paper explores the potential of using a cognitive model for decision making, the Markov decision process, to provide a mapping between within-task actions and latent traits of interest. Psychometric properties of the model are explored, and simulation studies report on parameter recovery within the context of a simple strategy game. The model is then applied to empirical data from an educational game. Estimates from the model are found to correlate more strongly with posttest results than a partial-credit IRT model based on outcome data alone.

  1. Lone ranger decision making versus consensus decision making: Descriptive analysis

    OpenAIRE

    Maite Sara Mashego

    2015-01-01

    Consensus decision making, concerns group members make decisions together with the requirement of reaching a consensus that is all members abiding by the decision outcome. Lone ranging worked for sometime in a autocratic environment. Researchers are now pointing to consensus decision-making in organizations bringing dividend to many organizations. This article used a descriptive analysis to compare the goodness of consensus decision making and making lone ranging decision management. This art...

  2. Uncertainty modeling and decision support

    International Nuclear Information System (INIS)

    Yager, Ronald R.

    2004-01-01

    We first formulate the problem of decision making under uncertainty. The importance of the representation of our knowledge about the uncertainty in formulating a decision process is pointed out. We begin with a brief discussion of the case of probabilistic uncertainty. Next, in considerable detail, we discuss the case of decision making under ignorance. For this case the fundamental role of the attitude of the decision maker is noted and its subjective nature is emphasized. Next the case in which a Dempster-Shafer belief structure is used to model our knowledge of the uncertainty is considered. Here we also emphasize the subjective choices the decision maker must make in formulating a decision function. The case in which the uncertainty is represented by a fuzzy measure (monotonic set function) is then investigated. We then return to the Dempster-Shafer belief structure and show its relationship to the fuzzy measure. This relationship allows us to get a deeper understanding of the formulation the decision function used Dempster- Shafer framework. We discuss how this deeper understanding allows a decision analyst to better make the subjective choices needed in the formulation of the decision function

  3. Root cause analysis of JCO accident based on decision-making model

    International Nuclear Information System (INIS)

    Kohda, Takehisa; Inoue, Koichi; Nojiri, Yoshihiko

    2000-01-01

    This paper discusses root causes of the JCO accident by considering the reasons why the workers made their decision to choose the illegal actions leading to a criticality accident. Analyzing their decision process compared with the normal decision process, the direct cause of their incorrect decision is estimated to be the lack of knowledge about the danger of nuclear materials and the criticality. Further, the lack of knowledge is considered to be due to organizational or environmental factors such as (a) the ignorance of safety by the overall JCO company which pursued low costs and high profit, (b) the JCO's custom and practice of modifying operational rules without permission, and (c) the JCO's inappropriate training or education where the criticality or its danger was not taught. All these background factors are related to the overconfidence of plant safety, a false trust that such a criticality accident will never occur at the plant. Since the recognition of the danger or risk of a system is considered to be the starting point for its safety management and operation, all information about the danger and safety should be correctly communicated to everyone related to the system. (author)

  4. Handbook of Marketing Decision Models

    NARCIS (Netherlands)

    B. Wierenga (Berend)

    2008-01-01

    textabstractThis book presents the state of the art in marketing decision models, dealing with new modeling areas such as customer relationship management, customer value and online marketing, but also describes recent developments in other areas. In the category of marketing mix models, the latest

  5. A regret theory approach to decision curve analysis: A novel method for eliciting decision makers' preferences and decision-making

    OpenAIRE

    Vickers Andrew; Hozo Iztok; Tsalatsanis Athanasios; Djulbegovic Benjamin

    2010-01-01

    Abstract Background Decision curve analysis (DCA) has been proposed as an alternative method for evaluation of diagnostic tests, prediction models, and molecular markers. However, DCA is based on expected utility theory, which has been routinely violated by decision makers. Decision-making is governed by intuition (system 1), and analytical, deliberative process (system 2), thus, rational decision-making should reflect both formal principles of rationality and intuition about good decisions. ...

  6. How decision analysis can further nanoinformatics.

    Science.gov (United States)

    Bates, Matthew E; Larkin, Sabrina; Keisler, Jeffrey M; Linkov, Igor

    2015-01-01

    The increase in nanomaterial research has resulted in increased nanomaterial data. The next challenge is to meaningfully integrate and interpret these data for better and more efficient decisions. Due to the complex nature of nanomaterials, rapid changes in technology, and disunified testing and data publishing strategies, information regarding material properties is often illusive, uncertain, and/or of varying quality, which limits the ability of researchers and regulatory agencies to process and use the data. The vision of nanoinformatics is to address this problem by identifying the information necessary to support specific decisions (a top-down approach) and collecting and visualizing these relevant data (a bottom-up approach). Current nanoinformatics efforts, however, have yet to efficiently focus data acquisition efforts on the research most relevant for bridging specific nanomaterial data gaps. Collecting unnecessary data and visualizing irrelevant information are expensive activities that overwhelm decision makers. We propose that the decision analytic techniques of multicriteria decision analysis (MCDA), value of information (VOI), weight of evidence (WOE), and portfolio decision analysis (PDA) can bridge the gap from current data collection and visualization efforts to present information relevant to specific decision needs. Decision analytic and Bayesian models could be a natural extension of mechanistic and statistical models for nanoinformatics practitioners to master in solving complex nanotechnology challenges.

  7. INCLUDING RISK IN ECONOMIC FEASIBILITY ANALYSIS:A STOCHASTIC SIMULATION MODEL FOR BLUEBERRY INVESTMENT DECISIONS IN CHILE

    Directory of Open Access Journals (Sweden)

    GERMÁN LOBOS

    2015-12-01

    Full Text Available ABSTRACT The traditional method of net present value (NPV to analyze the economic profitability of an investment (based on a deterministic approach does not adequately represent the implicit risk associated with different but correlated input variables. Using a stochastic simulation approach for evaluating the profitability of blueberry (Vaccinium corymbosum L. production in Chile, the objective of this study is to illustrate the complexity of including risk in economic feasibility analysis when the project is subject to several but correlated risks. The results of the simulation analysis suggest that the non-inclusion of the intratemporal correlation between input variables underestimate the risk associated with investment decisions. The methodological contribution of this study illustrates the complexity of the interrelationships between uncertain variables and their impact on the convenience of carrying out this type of business in Chile. The steps for the analysis of economic viability were: First, adjusted probability distributions for stochastic input variables (SIV were simulated and validated. Second, the random values of SIV were used to calculate random values of variables such as production, revenues, costs, depreciation, taxes and net cash flows. Third, the complete stochastic model was simulated with 10,000 iterations using random values for SIV. This result gave information to estimate the probability distributions of the stochastic output variables (SOV such as the net present value, internal rate of return, value at risk, average cost of production, contribution margin and return on capital. Fourth, the complete stochastic model simulation results were used to analyze alternative scenarios and provide the results to decision makers in the form of probabilities, probability distributions, and for the SOV probabilistic forecasts. The main conclusion shown that this project is a profitable alternative investment in fruit trees in

  8. Short term decisions for long term problems - The effect of foresight on model based energy systems analysis

    International Nuclear Information System (INIS)

    Keppo, Ilkka; Strubegger, Manfred

    2010-01-01

    This paper presents the development and demonstration of a limited foresight energy system model. The presented model is implemented as an extension to a large, linear optimization model, MESSAGE. The motivation behind changing the model is to provide an alternative decision framework, where information for the full time frame is not available immediately and sequential decision making under incomplete information is implied. While the traditional optimization framework provides the globally optimal decisions for the modeled problem, the framework presented here may offer a better description of the decision environment, under which decision makers must operate. We further modify the model to accommodate flexible dynamic constraints, which give an option to implement investments faster, albeit with a higher cost. Finally, the operation of the model is demonstrated using a moving window of foresight, with which decisions are taken for the next 30 years, but can be reconsidered later, when more information becomes available. We find that the results demonstrate some of the pitfalls of short term planning, e.g. lagging investments during earlier periods lead to higher requirements later during the century. Furthermore, the energy system remains more reliant on fossil based energy carriers, leading to higher greenhouse gas emissions.

  9. Variable precision rough set for multiple decision attribute analysis

    Institute of Scientific and Technical Information of China (English)

    Lai; Kin; Keung

    2008-01-01

    A variable precision rough set (VPRS) model is used to solve the multi-attribute decision analysis (MADA) problem with multiple conflicting decision attributes and multiple condition attributes. By introducing confidence measures and a β-reduct, the VPRS model can rationally solve the conflicting decision analysis problem with multiple decision attributes and multiple condition attributes. For illustration, a medical diagnosis example is utilized to show the feasibility of the VPRS model in solving the MADA...

  10. Introduction to Modeling of Buying Decisions

    Directory of Open Access Journals (Sweden)

    O. Gruenwald

    2011-01-01

    Full Text Available Buying decision models of customers to adjust the competitiveness of organizations have been a challenge for marketing disciplines for several generations. This topic has been explored by researchers and academics in past years, and quite an extensive theoretical base exists with a number of approaches for dealing with this challenge.This paper presents some approaches for creating a customer decision model, and provides experimental results from an electronic investigation intended to build the Kano Model; to prove an ability to understand the modeling principle; and to find out the interpretation of the examined demand in a specific market segment involving students of a technical university. The last section of the paper contains a brief introduction to Choice-Based Modeling with Choice-Based Conjoint Analysis (CBC, which was tailored for modeling purchasing decisions.

  11. Data Decision Analysis: Project Shoal

    Energy Technology Data Exchange (ETDEWEB)

    Forsgren, Frank; Pohll, Greg; Tracy, John

    1999-01-01

    The purpose of this study was to determine the most appropriate field activities in terms of reducing the uncertainty in the groundwater flow and transport model at the Project Shoal area. The data decision analysis relied on well-known tools of statistics and uncertainty analysis. This procedure identified nine parameters that were deemed uncertain. These included effective porosity, hydraulic head, surface recharge, hydraulic conductivity, fracture correlation scale, fracture orientation, dip angle, dissolution rate of radionuclides from the puddle glass, and the retardation coefficient, which describes the sorption characteristics. The parameter uncertainty was described by assigning prior distributions for each of these parameters. Next, the various field activities were identified that would provide additional information on these parameters. Each of the field activities was evaluated by an expert panel to estimate posterior distribution of the parameters assuming a field activity was performed. The posterior distributions describe the ability of the field activity to estimate the true value of the nine parameters. Monte Carlo techniques were used to determine the current uncertainty, the reduction of uncertainty if a single parameter was known with certainty, and the reduction of uncertainty expected from each field activity on the model predictions. The mean breakthrough time to the downgradient land withdrawal boundary and the peak concentration at the control boundary were used to evaluate the uncertainty reduction. The radionuclide 137Cs was used as the reference solute, as its migration is dependent on all of the parameters. The results indicate that the current uncertainty of the model yields a 95 percent confidence interval between 42 and 1,412 years for the mean breakthrough time and an 18 order-of-magnitude range in peak concentration. The uncertainty in effective porosity and recharge dominates the uncertainty in the model predictions, while the

  12. Modeling Common-Sense Decisions

    Science.gov (United States)

    Zak, Michail

    This paper presents a methodology for efficient synthesis of dynamical model simulating a common-sense decision making process. The approach is based upon the extension of the physics' First Principles that includes behavior of living systems. The new architecture consists of motor dynamics simulating actual behavior of the object, and mental dynamics representing evolution of the corresponding knowledge-base and incorporating it in the form of information flows into the motor dynamics. The autonomy of the decision making process is achieved by a feedback from mental to motor dynamics. This feedback replaces unavailable external information by an internal knowledgebase stored in the mental model in the form of probability distributions.

  13. THE CAUSAL ANALYSIS / DIAGNOSIS DECISION ...

    Science.gov (United States)

    CADDIS is an on-line decision support system that helps investigators in the regions, states and tribes find, access, organize, use and share information to produce causal evaluations in aquatic systems. It is based on the US EPA's Stressor Identification process which is a formal method for identifying causes of impairments in aquatic systems. CADDIS 2007 increases access to relevant information useful for causal analysis and provides methods and tools that practitioners can use to analyze their own data. The new Candidate Cause section provides overviews of commonly encountered causes of impairments to aquatic systems: metals, sediments, nutrients, flow alteration, temperature, ionic strength, and low dissolved oxygen. CADDIS includes new Conceptual Models that illustrate the relationships from sources to stressors to biological effects. An Interactive Conceptual Model for phosphorus links the diagram with supporting literature citations. The new Analyzing Data section helps practitioners analyze their data sets and interpret and use those results as evidence within the USEPA causal assessment process. Downloadable tools include a graphical user interface statistical package (CADStat), and programs for use with the freeware R statistical package, and a Microsoft Excel template. These tools can be used to quantify associations between causes and biological impairments using innovative methods such as species-sensitivity distributions, biological inferenc

  14. A multiple choice decision analysis: an integrated QFD – AHP model ...

    African Journals Online (AJOL)

    The aim of this work is to propose a new methodological approach to define customer specifications through the employment of an integrated Quality Function Deployment (QFD) – Analytic Hierarchy Process (AHP) model. The model, which is loosely based on QFD, incorporates the AHP approach to delineate and rank the ...

  15. Modelling the epidemiology of infectious diseases for decision analysis: a primer.

    Science.gov (United States)

    Jit, Mark; Brisson, Marc

    2011-05-01

    The number of economic evaluations related to infectious disease topics has increased over the last 2 decades. However, many such evaluations rely on models that do not take into account unique features of infectious diseases that can affect the estimated value of interventions against them. These include their transmissibility from infected to susceptible individuals, the possibility of acquiring natural immunity following recovery from infection and the uncertainties that arise as a result of their complex natural history and epidemiology. Modellers conducting economic evaluations of infectious disease interventions need to know the main features of different types of infectious disease models, the situations in which they should be applied and the effects of model choices on the cost effectiveness of interventions.

  16. Approximate reasoning in decision analysis

    Energy Technology Data Exchange (ETDEWEB)

    Gupta, M M; Sanchez, E

    1982-01-01

    The volume aims to incorporate the recent advances in both theory and applications. It contains 44 articles by 74 contributors from 17 different countries. The topics considered include: membership functions; composite fuzzy relations; fuzzy logic and inference; classifications and similarity measures; expert systems and medical diagnosis; psychological measurements and human behaviour; approximate reasoning and decision analysis; and fuzzy clustering algorithms.

  17. Decision Analysis Science Modeling for Application and Fielding Selection Applied to Concrete Decontamination Technologies

    International Nuclear Information System (INIS)

    Ebadian, M.A.; Ross, T.L.

    1998-01-01

    Concrete surfaces contaminated with radionuclides present a significant challenge during the decontamination and decommissioning (D and D) process. As structures undergo D and D, coating layers and/or surface layers of the concrete containing the contaminants must be removed for disposal in such a way as to present little to no risk to human health or the environment. The selection of a concrete decontamination technology that is safe, efficient, and cost-effective is critical to the successful D and D of contaminated sites. To support U.S. Department of Energy (DOE) Environmental Management objectives and to assist DOE site managers in the selection of the best-suited concrete floor decontamination technology(s) for a given site, two innovative and three baseline technologies have been assessed under standard, non-nuclear conditions at the Hemispheric Center for Environmental Technology (HCET) at Florida International University (FIU). The innovative technologies assessed include the Pegasus Coating Removal System and Textron's Electro-Hydraulic Scabbling System. The three baseline technologies assessed include: the Wheelabrator Blastrac model 1-15D, the NELCO Porta Shot Blast trademark model GPx-1O-18 HO Rider, and the NELCO Porta Shot Blasttrademark model EC-7-2. These decontamination technology assessments provide directly comparable performance data that have previously been available for only a limited number of technologies under restrictive site-specific constraints. Some of the performance data collected during these technology assessments include: removal capability, production rate, removal gap, primary and secondary waste volumes, and operation and maintenance requirements. The performance data generated by this project is intended to assist DOE site managers in the selection of the safest, most efficient, and cost-effective decontamination technologies to accomplish their remediation objectives

  18. Rule-based decision making model

    International Nuclear Information System (INIS)

    Sirola, Miki

    1998-01-01

    A rule-based decision making model is designed in G2 environment. A theoretical and methodological frame for the model is composed and motivated. The rule-based decision making model is based on object-oriented modelling, knowledge engineering and decision theory. The idea of safety objective tree is utilized. Advanced rule-based methodologies are applied. A general decision making model 'decision element' is constructed. The strategy planning of the decision element is based on e.g. value theory and utility theory. A hypothetical process model is built to give input data for the decision element. The basic principle of the object model in decision making is division in tasks. Probability models are used in characterizing component availabilities. Bayes' theorem is used to recalculate the probability figures when new information is got. The model includes simple learning features to save the solution path. A decision analytic interpretation is given to the decision making process. (author)

  19. Decision analysis with cumulative prospect theory.

    Science.gov (United States)

    Bayoumi, A M; Redelmeier, D A

    2000-01-01

    Individuals sometimes express preferences that do not follow expected utility theory. Cumulative prospect theory adjusts for some phenomena by using decision weights rather than probabilities when analyzing a decision tree. The authors examined how probability transformations from cumulative prospect theory might alter a decision analysis of a prophylactic therapy in AIDS, eliciting utilities from patients with HIV infection (n = 75) and calculating expected outcomes using an established Markov model. They next focused on transformations of three sets of probabilities: 1) the probabilities used in calculating standard-gamble utility scores; 2) the probabilities of being in discrete Markov states; 3) the probabilities of transitioning between Markov states. The same prophylaxis strategy yielded the highest quality-adjusted survival under all transformations. For the average patient, prophylaxis appeared relatively less advantageous when standard-gamble utilities were transformed. Prophylaxis appeared relatively more advantageous when state probabilities were transformed and relatively less advantageous when transition probabilities were transformed. Transforming standard-gamble and transition probabilities simultaneously decreased the gain from prophylaxis by almost half. Sensitivity analysis indicated that even near-linear probability weighting transformations could substantially alter quality-adjusted survival estimates. The magnitude of benefit estimated in a decision-analytic model can change significantly after using cumulative prospect theory. Incorporating cumulative prospect theory into decision analysis can provide a form of sensitivity analysis and may help describe when people deviate from expected utility theory.

  20. Cost-effectiveness analysis of diarrhoea management approaches in Nigeria: A decision analytical model.

    Directory of Open Access Journals (Sweden)

    Charles E Okafor

    2017-12-01

    Full Text Available Diarrhoea is a leading cause of death in Nigerian children under 5 years. Implementing the most cost-effective approach to diarrhoea management in Nigeria will help optimize health care resources allocation. This study evaluated the cost-effectiveness of various approaches to diarrhoea management namely: the 'no treatment' approach (NT; the preventive approach with rotavirus vaccine; the integrated management of childhood illness for diarrhoea approach (IMCI; and rotavirus vaccine plus integrated management of childhood illness for diarrhoea approach (rotavirus vaccine + IMCI.Markov cohort model conducted from the payer's perspective was used to calculate the cost-effectiveness of the four interventions. The markov model simulated a life cycle of 260 weeks for 33 million children under five years at risk of having diarrhoea (well state. Disability adjusted life years (DALYs averted was used to quantify clinical outcome. Incremental cost-effectiveness ratio (ICER served as measure of cost-effectiveness.Based on cost-effectiveness threshold of $2,177.99 (i.e. representing Nigerian GDP/capita, all the approaches were very cost-effective but rotavirus vaccine approach was dominated. While IMCI has the lowest ICER of $4.6/DALY averted, the addition of rotavirus vaccine was cost-effective with an ICER of $80.1/DALY averted. Rotavirus vaccine alone was less efficient in optimizing health care resource allocation.Rotavirus vaccine + IMCI approach was the most cost-effective approach to childhood diarrhoea management. Its awareness and practice should be promoted in Nigeria. Addition of rotavirus vaccine should be considered for inclusion in the national programme of immunization. Although our findings suggest that addition of rotavirus vaccine to IMCI for diarrhoea is cost-effective, there may be need for further vaccine demonstration studies or real life studies to establish the cost-effectiveness of the vaccine in Nigeria.

  1. A Selection Approach for Optimized Problem-Solving Process by Grey Relational Utility Model and Multicriteria Decision Analysis

    Directory of Open Access Journals (Sweden)

    Chih-Kun Ke

    2012-01-01

    Full Text Available In business enterprises, especially the manufacturing industry, various problem situations may occur during the production process. A situation denotes an evaluation point to determine the status of a production process. A problem may occur if there is a discrepancy between the actual situation and the desired one. Thus, a problem-solving process is often initiated to achieve the desired situation. In the process, how to determine an action need to be taken to resolve the situation becomes an important issue. Therefore, this work uses a selection approach for optimized problem-solving process to assist workers in taking a reasonable action. A grey relational utility model and a multicriteria decision analysis are used to determine the optimal selection order of candidate actions. The selection order is presented to the worker as an adaptive recommended solution. The worker chooses a reasonable problem-solving action based on the selection order. This work uses a high-tech company’s knowledge base log as the analysis data. Experimental results demonstrate that the proposed selection approach is effective.

  2. A hybrid multi-criteria decision modeling approach for the best biodiesel blend selection based on ANP-TOPSIS analysis

    Directory of Open Access Journals (Sweden)

    G. Sakthivel

    2015-03-01

    Full Text Available The ever increasing demand and depletion of fossil fuels had an adverse impact on environmental pollution. The selection of appropriate source of biodiesel and proper blending of biodiesel plays a major role in alternate energy production. This paper describes an application of hybrid Multi Criteria Decision Making (MCDM technique for the selection of optimum fuel blend in fish oil biodiesel for the IC engine. The proposed model, Analytical Network Process (ANP is integrated with Technique for Order Performance by Similarity to Ideal Solution (TOPSIS and VlseKriterijumska Optimizacija I Kompromisno Resenje (in Serbian (VIKOR to evaluate the optimum blend. Evaluation of suitable blend is based on the exploratory analysis of the performance, emission and combustion parameters of the single cylinder, constant speed direct injection diesel engine at different load conditions. Here the ANP is used to determine the relative weights of the criteria, whereas TOPSIS and VIKOR are used for obtaining the final ranking of alternative blends. An efficient pair-wise comparison process and ranking of alternatives can be achieved for optimum blend selection through the integration of ANP with TOPSIS and VIKOR. The obtained preference order of the blends for ANP-VIKOR and ANP-TOPSIS are B20 > Diesel > B40 > B60 > B80 > B100 and B20 > B40 > Diesel > B60 > B80 > B100 respectively. Hence by comparing both these methods, B20 is selected as the best blend to operate the internal combustion engines. This paper highlights a new insight into MCDM techniques to evaluate the best fuel blend for the decision makers such as engine manufactures and R& D engineers to meet the fuel economy and emission norms to empower the green revolution.

  3. A cost-effectiveness analysis of a proactive management strategy for the Sprint Fidelis recall: a probabilistic decision analysis model.

    Science.gov (United States)

    Bashir, Jamil; Cowan, Simone; Raymakers, Adam; Yamashita, Michael; Danter, Matthew; Krahn, Andrew; Lynd, Larry D

    2013-12-01

    The management of the recall is complicated by the competing risks of lead failure and complications that can occur with lead revision. Many of these patients are currently undergoing an elective generator change--an ideal time to consider lead revision. To determine the cost-effectiveness of a proactive management strategy for the Sprint Fidelis recall. We obtained detailed clinical outcomes and costing data from a retrospective analysis of 341 patients who received the Sprint Fidelis lead in British Columbia, where patients younger than 60 years were offered lead extraction when undergoing generator replacement. These population-based data were used to construct and populate a probabilistic Markov model in which a proactive management strategy was compared to a conservative strategy to determine the incremental cost per lead failure avoided. In our population, elective lead revisions were half the cost of emergent revisions and had a lower complication rate. In the model, the incremental cost-effectiveness ratio of proactive lead revision versus a recommended monitoring strategy was $12,779 per lead failure avoided. The proactive strategy resulted in 21 fewer failures per 100 patients treated and reduced the chance of an additional complication from an unexpected surgery. Cost-effectiveness analysis suggests that prospective lead revision should be considered when patients with a Sprint Fidelis lead present for pulse generator change. Elective revision of the lead is justified even when 25% of the population is operated on per year, and in some scenarios, it is both less costly and provides a better outcome. © 2013 Heart Rhythm Society Published by Heart Rhythm Society All rights reserved.

  4. Decision modeling and acceptance criteria

    DEFF Research Database (Denmark)

    Ditlevsen, Ove Dalager

    2003-01-01

    compensation value of a human life and a public money equivalent of a human life, where the last value usually is considerably larger than the first value, it is possible from the decision analysis to determine an upper limit that the public should impose on the ratio of the owner´s expected loss rate......) that combines wealth in terms of Gross Domestic Product per person, life expectancy at birth, and yearly work time into a single number. The philosophy behind the published evaluations is that the prevention of a loss of a life is counteracted by a cost such that the LQI remains unchanged (Skjong R, Ronold K......; Decision Analysis; Life quality index; Random interest rate; Risk aversion; Socio-economic value; Uncertainty aversion...

  5. Computational modelling and analysis of hippocampal-prefrontal information coding during a spatial decision-making task

    Directory of Open Access Journals (Sweden)

    Thomas eJahans-Price

    2014-03-01

    Full Text Available We introduce a computational model describing rat behaviour and the interactions of neural populations processing spatial and mnemonic information during a maze-based, decision-making task. The model integrates sensory input and implements a working memory to inform decisions at a choice point, reproducing rat behavioural data and predicting the occurrence of turn- and memory-dependent activity in neuronal networks supporting task performance. We tested these model predictions using a new software toolbox (Maze Query Language, MQL to analyse activity of medial prefrontal cortical (mPFC and dorsal hippocampal (dCA1 neurons recorded from 6 adult rats during task performance. The firing rates of dCA1 neurons discriminated context (i.e. the direction of the previous turn, whilst a subset of mPFC neurons was selective for current turn direction or context, with some conjunctively encoding both. mPFC turn-selective neurons displayed a ramping of activity on approach to the decision turn and turn-selectivity in mPFC was significantly reduced during error trials. These analyses complement data from neurophysiological recordings in non-human primates indicating that firing rates of cortical neurons correlate with integration of sensory evidence used to inform decision-making.

  6. Integrated agro-hydrological modelling and economic analysis of BMPs to support decision making and policy design

    Science.gov (United States)

    Maroy, E.; Rousseau, A. N.; Hallema, D. W.

    2012-12-01

    With recent efforts and increasing control over point source pollution of freshwater, agricultural non-point pollution sources have become responsible for most of sediment and nutrient loads in North American water systems. Environmental and agricultural agencies have recognised the need for reducing eutrophication and have developed various policies to compel or encourage producers to best management practices (BMPs). Addressing diffuse pollution is challenging considering the complex and cumulative nature of transport processes, high variability in space and time, and prohibitive costs of distributed water quality monitoring. Many policy options exist to push producers to adopt environmentally desirable behaviour while keeping their activity viable, and ensure equitable costs to consumers and tax payers. On the one hand, economic instruments (subsidies, taxes, water quality markets) are designed to maximize cost-effectiveness, so that farmers optimize their production for maximum profit while implementing BMPs. On the other hand, emission standards or regulation of inputs are often easier and less costly to implement. To study economic and environmental impacts of such policies, a distributed modelling approach is needed to deal with the complexity of the system and the large environmental and socio-economic data requirements. Our objective is to integrate agro-hydrological modelling and economic analysis to support decision and policy making processes of BMP implementation. The integrated modelling system GIBSI was developed in an earlier study within the Canadian WEBs project (Watershed Evaluation of BMPs) to evaluate the influence of BMPs on water quality. The case study involved 30 and 15 year records of discharge and water quality measurements respectively, in the Beaurivage River watershed (Quebec, Canada). GIBSI provided a risk-based overview of the impact of BMPs (including vegetated riparian buffer strips, precision slurry application, conversion to

  7. Strategic decision analysis applied to borehole seismology

    International Nuclear Information System (INIS)

    Menke, M.M.; Paulsson, B.N.P.

    1994-01-01

    Strategic Decision Analysis (SDA) is the evolving body of knowledge on how to achieve high quality in the decision that shapes an organization's future. SDA comprises philosophy, process concepts, methodology, and tools for making good decisions. It specifically incorporates many concepts and tools from economic evaluation and risk analysis. Chevron Petroleum Technology Company (CPTC) has applied SDA to evaluate and prioritize a number of its most important and most uncertain R and D projects, including borehole seismology. Before SDA, there were significant issues and concerns about the value to CPTC of continuing to work on borehole seismology. The SDA process created a cross-functional team of experts to structure and evaluate this project. A credible economic model was developed, discrete risks and continuous uncertainties were assessed, and an extensive sensitivity analysis was performed. The results, even applied to a very restricted drilling program for a few years, were good enough to demonstrate the value of continuing the project. This paper explains the SDA philosophy concepts, and process and demonstrates the methodology and tools using the borehole seismology project example. SDA is useful in the upstream industry not just in the R and D/technology decisions, but also in major exploration and production decisions. Since a major challenge for upstream companies today is to create and realize value, the SDA approach should have a very broad applicability

  8. A model to systematically employ professional judgment in the Bayesian Decision Analysis for a semiconductor industry exposure assessment.

    Science.gov (United States)

    Torres, Craig; Jones, Rachael; Boelter, Fred; Poole, James; Dell, Linda; Harper, Paul

    2014-01-01

    Bayesian Decision Analysis (BDA) uses Bayesian statistics to integrate multiple types of exposure information and classify exposures within the exposure rating categorization scheme promoted in American Industrial Hygiene Association (AIHA) publications. Prior distributions for BDA may be developed from existing monitoring data, mathematical models, or professional judgment. Professional judgments may misclassify exposures. We suggest that a structured qualitative risk assessment (QLRA) method can provide consistency and transparency in professional judgments. In this analysis, we use a structured QLRA method to define prior distributions (priors) for BDA. We applied this approach at three semiconductor facilities in South Korea, and present an evaluation of the performance of structured QLRA for determination of priors, and an evaluation of occupational exposures using BDA. Specifically, the structured QLRA was applied to chemical agents in similar exposure groups to identify provisional risk ratings. Standard priors were developed for each risk rating before review of historical monitoring data. Newly collected monitoring data were used to update priors informed by QLRA or historical monitoring data, and determine the posterior distribution. Exposure ratings were defined by the rating category with the highest probability--i.e., the most likely. We found the most likely exposure rating in the QLRA-informed priors to be consistent with historical and newly collected monitoring data, and the posterior exposure ratings developed with QLRA-informed priors to be equal to or greater than those developed with data-informed priors in 94% of comparisons. Overall, exposures at these facilities are consistent with well-controlled work environments. That is, the 95th percentile of exposure distributions are ≤50% of the occupational exposure limit (OEL) for all chemical-SEG combinations evaluated; and are ≤10% of the limit for 94% of chemical-SEG combinations evaluated.

  9. Effects of Methadone Maintenance Treatment on Decision-Making Processes in Heroin-Abusers: A Cognitive Modeling Analysis

    Directory of Open Access Journals (Sweden)

    Arash Khodadadi

    2010-05-01

    Full Text Available A B S T R A C TIntroduction: Although decision-making processes have become a principal target of study among addiction researchers, few researches are published according to effects of different treatment methods on the cognitive processes underlying decision making up to now. Utilizing cognitive modeling method, in this paper we examine the effects of Methadone maintenance treatment (MMT on cognitive processes underlying decision-making disorders in heroin-abusers. Methods: For this purpose, for the first time, we use the balloon analog risk task (BART to assess the decision-making ability of heroin-abusers before and after treatment and compare it to the non heroin-dependent subjects. Results: Results demonstrate that heroin-abusers show more risky behavior than other groups. But, there is no difference between the performance of heroin-abusers after 6 months of MMT and control group. Modeling subjects’ behavior in BART reveals that poor performance in heroin-abusers is due to reward-dependency and insensitivity to evaluation. Discussion: Results show that 6 months of MMT decreases reward-dependency and increases sensitivity to evaluation.

  10. Aggregated systems model for nuclear safeguards decisions

    International Nuclear Information System (INIS)

    1979-03-01

    This report summarizes a general analytical tool designed to assist nuclear safeguards decision-makers. The approach is based on decision analysis--a quantitative procedure for evaluating complex decision alternatives with uncertain outcomes. The report describes the general analytical approach in the context of safeguards decisions at a hypothetical nuclear fuel reprocessing plant

  11. Decision tree modeling using R.

    Science.gov (United States)

    Zhang, Zhongheng

    2016-08-01

    In machine learning field, decision tree learner is powerful and easy to interpret. It employs recursive binary partitioning algorithm that splits the sample in partitioning variable with the strongest association with the response variable. The process continues until some stopping criteria are met. In the example I focus on conditional inference tree, which incorporates tree-structured regression models into conditional inference procedures. While growing a single tree is subject to small changes in the training data, random forests procedure is introduced to address this problem. The sources of diversity for random forests come from the random sampling and restricted set of input variables to be selected. Finally, I introduce R functions to perform model based recursive partitioning. This method incorporates recursive partitioning into conventional parametric model building.

  12. The IDA cognitive model for the analysis of nuclear power plant operator response under accident conditions. Part I: problem solving and decision making model

    International Nuclear Information System (INIS)

    Smidts, C.; Shen, S.H.; Mosleh, A.

    1997-01-01

    This paper is the first of a series of papers describing IDA which is a cognitive model for analysing the behaviour of nuclear power plant operators under accident conditions. The domain of applicability of the model is a relatively constrained environment where behaviour is significantly influenced by high levels of training and explicit requirement to follow written procedures. IDA consists of a model for individual operator behaviour and a model for control room operating crew expanded from the individual model. The model and its derivatives such as an error taxonomy and data collection approach has been designed with ultimate objective of becoming a quantitative method for human reliability analysis (HRA) in probabilistic risk assessment (PRA). The present paper gives a description of the main components of IDA such as memory structure, goals, and problem solving and decision making strategies. It also identifies factors that are at the origin of transitions between goals or between strategies. These factors cover the effects of external conditions and psychological state of the operator. The description is generic at first and then made specific to the nuclear power plant environment and more precisely to abnormal conditions

  13. Modeling Human Elements of Decision-Making

    Science.gov (United States)

    2002-06-01

    include factors such as personality, emotion , and level of expertise, which vary from individual to individual. The process of decision - making during... rational choice theories such as utility theory, to more descriptive psychological models that focus more on the process of decision - making ...descriptive nature, they provide a more realistic representation of human decision - making than the rationally based models. However these models do

  14. Decision models in engineering and management

    CERN Document Server

    2015-01-01

    Providing a comprehensive overview of various methods  and applications in decision engineering, this book presents chapters written by a range experts in the field. It presents conceptual aspects of decision support applications in various areas including finance, vendor selection, construction, process management, water management and energy, agribusiness , production scheduling and control, and waste management. In addition to this, a special focus is given to methods of multi-criteria decision analysis. Decision making in organizations is a recurrent theme and is essential for business continuity.  Managers from various fields including public, private, industrial, trading or service sectors are required to make decisions. Consequently managers need the support of these structured methods in order to engage in effective decision making. This book provides a valuable resource for graduate students, professors and researchers of decision analysis, multi-criteria decision analysis and group decision analys...

  15. Applied decision analysis and risk evaluation

    International Nuclear Information System (INIS)

    Ferse, W.; Kruber, S.

    1995-01-01

    During 1994 the workgroup 'Applied Decision Analysis and Risk Evaluation; continued the work on the knowledge based decision support system XUMA-GEFA for the evaluation of the hazard potential of contaminated sites. Additionally a new research direction was started which aims at the support of a later stage of the treatment of contaminated sites: The clean-up decision. For the support of decisions arising at this stage, the methods of decision analysis will be used. Computational aids for evaluation and decision support were implemented and a case study at a waste disposal site in Saxony which turns out to be a danger for the surrounding groundwater ressource was initiated. (orig.)

  16. Combining morphological analysis and Bayesian Networks for strategic decision support

    CSIR Research Space (South Africa)

    De Waal, AJ

    2007-12-01

    Full Text Available Morphological analysis (MA) and Bayesian networks (BN) are two closely related modelling methods, each of which has its advantages and disadvantages for strategic decision support modelling. MA is a method for defining, linking and evaluating...

  17. Modelling decision-making by pilots

    Science.gov (United States)

    Patrick, Nicholas J. M.

    1993-01-01

    Our scientific goal is to understand the process of human decision-making. Specifically, a model of human decision-making in piloting modern commercial aircraft which prescribes optimal behavior, and against which we can measure human sub-optimality is sought. This model should help us understand such diverse aspects of piloting as strategic decision-making, and the implicit decisions involved in attention allocation. Our engineering goal is to provide design specifications for (1) better computer-based decision-aids, and (2) better training programs for the human pilot (or human decision-maker, DM).

  18. Multidimensional Balanced Efficiency Decision Model

    Directory of Open Access Journals (Sweden)

    Antonella Petrillo

    2015-10-01

    Full Text Available In this paper a multicriteria methodological approach, based on Balanced Scorecard (BSC and Analytic Network Process (ANP, is proposed to evaluate competitiveness performance in luxury sector. A set of specific key performance indicators (KPIs have been proposed. The contribution of our paper is to present the integration of two methodologies, BSC – a multiple perspective framework for performance assessment – and ANP – a decision-making tool to prioritize multiple performance perspectives and indicators and to generate a unified metric that incorporates diversified issues for conducting supply chain improvements. The BSC/ANP model is used to prioritize all performances within a luxury industry. A real case study is presented.

  19. Decision forests for computer vision and medical image analysis

    CERN Document Server

    Criminisi, A

    2013-01-01

    This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision forests; discusses the use of decision for

  20. [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.

  1. Groundwater potentiality mapping using geoelectrical-based aquifer hydraulic parameters: A GIS-based multi-criteria decision analysis modeling approach

    Directory of Open Access Journals (Sweden)

    Kehinde Anthony Mogaji Hwee San Lim

    2017-01-01

    Full Text Available This study conducted a robust analysis on acquired 2D resistivity imaging data and borehole pumping test records to optimize groundwater potentiality mapping in Perak province, Malaysia using derived aquifer hydraulic properties. The transverse resistance (TR parameter was determined from the interpreted 2D resistivity imaging data by applying the Dar-Zarrouk parameter equation. Linear regression and GIS techniques were used to regress the estimated values for TR parameters with the aquifer transmissivity values extracted from the geospatially produced BPT records-based aquifer transmissivity map to develop the aquifer transmissivity parameter predictive (ATPP model. The reliability evaluated ATPP model using the Theil inequality coefficient measurement approach was used to establish geoelectrical-based hydraulic parameters (GHP modeling equations for the modeling of transmissivity (Tr, hydraulic conductivity (K, storativity (St, and hydraulic diffusivity (D properties. The applied GHP modeling equation results to the delineated aquifer media was used to produce aquifer potential conditioning factor maps for Tr, K, St, and D. The maps were modeled to develop an aquifer potential mapping index (APMI model via applying the multi-criteria decision analysis-analytic hierarchy process principle. The area groundwater reservoir productivity potential model map produced based on the processed APMI model estimates in the GIS environment was found to be 71% accurate. This study establishes a good alternative approach to determine aquifer hydraulic parameters even in areas where pumping test information is unavailable using a cost effective geophysical data. The produced map can be explored for hydrological decision making.

  2. CRITICAL ANALYSIS OF THE RELIABILITY OF INTUITIVE MORAL DECISIONS

    Directory of Open Access Journals (Sweden)

    V. V. Nadurak

    2017-06-01

    Full Text Available Purpose of the research is a critical analysis of the reliability of intuitive moral decisions. Methodology. The work is based on the methodological attitude of empirical ethics, involving the use of findings from empirical research in ethical reflection and decision making. Originality. The main kinds of intuitive moral decisions are identified: 1 intuitively emotional decisions (i.e. decisions made under the influence of emotions that accompanies the process of moral decision making; 2 decisions made under the influence of moral risky psychological aptitudes (unconscious human tendencies that makes us think in a certain way and make decisions, unacceptable from the logical and ethical point of view; 3 intuitively normative decisions (decisions made under the influence of socially learned norms, that cause evaluative feeling «good-bad», without conscious reasoning. It was found that all of these kinds of intuitive moral decisions can lead to mistakes in the moral life. Conclusions. Considering the fact that intuition systematically leads to erroneous moral decisions, intuitive reaction cannot be the only source for making such decisions. The conscious rational reasoning can compensate for weaknesses of intuition. In this case, there is a necessity in theoretical model that would structure the knowledge about the interactions between intuitive and rational factors in moral decisions making and became the basis for making suggestions that would help us to make the right moral decision.

  3. A prediction rule for the development of delirium among patients in medical wards: Chi-Square Automatic Interaction Detector (CHAID) decision tree analysis model.

    Science.gov (United States)

    Kobayashi, Daiki; Takahashi, Osamu; Arioka, Hiroko; Koga, Shinichiro; Fukui, Tsuguya

    2013-10-01

    To predict development of delirium among patients in medical wards by a Chi-Square Automatic Interaction Detector (CHAID) decision tree model. This was a retrospective cohort study of all adult patients admitted to medical wards at a large community hospital. The subject patients were randomly assigned to either a derivation or validation group (2:1) by computed random number generation. Baseline data and clinically relevant factors were collected from the electronic chart. Primary outcome was the development of delirium during hospitalization. All potential predictors were included in a forward stepwise logistic regression model. CHAID decision tree analysis was also performed to make another prediction model with the same group of patients. Receiver operating characteristic curves were drawn, and the area under the curves (AUCs) were calculated for both models. In the validation group, these receiver operating characteristic curves and AUCs were calculated based on the rules from derivation. A total of 3,570 patients were admitted: 2,400 patients assigned to the derivation group and 1,170 to the validation group. A total of 91 and 51 patients, respectively, developed delirium. Statistically significant predictors were delirium history, age, underlying malignancy, and activities of daily living impairment in CHAID decision tree model, resulting in six distinctive groups by the level of risk. AUC was 0.82 in derivation and 0.82 in validation with CHAID model and 0.78 in derivation and 0.79 in validation with logistic model. We propose a validated CHAID decision tree prediction model to predict the development of delirium among medical patients. Copyright © 2013 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

  4. Decision theory, the context for risk and reliability analysis

    International Nuclear Information System (INIS)

    Kaplan, S.

    1985-01-01

    According to this model of the decision process then, the optimum decision is that option having the largest expected utility. This is the fundamental model of a decision situation. It is necessary to remark that in order for the model to represent a real-life decision situation, it must include all the options present in that situation, including, for example, the option of not deciding--which is itself a decision, although usually not the optimum one. Similarly, it should include the option of delaying the decision while the authors gather further information. Both of these options have probabilities, outcomes, impacts, and utilities like any option and should be included explicitly in the decision diagram. The reason for doing a quantitative risk or reliability analysis is always that, somewhere underlying there is a decision to be made. The decision analysis therefore always forms the context for the risk or reliability analysis, and this context shapes the form and language of that analysis. Therefore, they give in this section a brief review of the well-known decision theory diagram

  5. Hemodialysis Reliable Outflow (HeRO) device in end-stage dialysis access: a decision analysis model.

    Science.gov (United States)

    Dageforde, Leigh Anne; Bream, Peter R; Moore, Derek E

    2012-09-01

    The Hemodialysis Reliable Outflow (HeRO) dialysis access device is a permanent tunneled dialysis graft connected to a central venous catheter and is used in patients with end-stage dialysis access (ESDA) issues secondary to central venous stenosis. The safety and effectiveness of the HeRO device has previously been proven, but no study thus far has compared the cost of its use with tunneled dialysis catheters (TDCs) and thigh grafts in patients with ESDA. A decision analytic model was developed to simulate outcomes for patients with ESDA undergoing placement of a HeRO dialysis access device, TDC, or thigh graft. Outcomes of interest were infection, thrombosis, and ischemic events. Baseline values, ranges, and costs were determined from a systematic review of the literature. Total costs were based on 1 year of post-procedure outcomes. Sensitivity analyses were conducted to test model strength. The HeRO dialysis access device is the least costly dialysis access with an average 1-year cost of $6521. The 1-year cost for a TDC was $8477. A thigh graft accounted for $9567 in a 1-year time period. The HeRO dialysis access device is the least costly method of ESDA. The primary determinants of cost in this model are infection in TDCs and leg ischemia necessitating amputation in thigh grafts. Further study is necessary to incorporate patient preference and quality of life into the model. Copyright © 2012 Elsevier Inc. All rights reserved.

  6. Economic modelling for life extension decision making

    International Nuclear Information System (INIS)

    Farber, M.A.; Harrison, D.L.; Carlson, D.D.

    1987-01-01

    This paper presents a methodology for the economic and financial analysis of nuclear plant life extension under uncertainty and demonstrates its use in a case analysis. While the economic and financial evaluation of life extension does not require new analytical tools, such studies should be based on the following three premises. First, the methodology should examine effects at the level of the company or utility system, because the most important economic implications of life extension relate to the altered generation system expansion plan. Second, it should focus on the implications of uncertainty in order to understand the factors that most affect life extension benefits and identify risk management efforts. Third, the methodology should address multiple objectives, at a minimum, both economic and financial objectives. An analysis of the role of life extension for Virginia Power's generating system was performed using the MIDAS model, developed by the Electric Power Research Institute. MIDAS is particularly well suited to this type of study because of its decision analysis framework. The model incorporates modules for load analysis, capacity expansion, production costing, financial analysis, and rates. The decision tree structure facilitates the multiple-scenario analysis of uncertainty. The model's output includes many economic and financial measures, including capital expenditures, fuel and purchases power costs, revenue requirements, average rates, external financing requirements, and coverage ratio. Based on findings for Virginia Power's Surry 1 plant, nuclear plant life extension has economic benefits for a utility's customers and financial benefits for the utility's investors. These benefits depend on a number of economic, technical and regulatory factors. The economic analysis presented in this paper identifies many of the key factors and issues relevant to life extension planning

  7. "Know What to Do If You Encounter a Flash Flood": Mental Models Analysis for Improving Flash Flood Risk Communication and Public Decision Making.

    Science.gov (United States)

    Lazrus, Heather; Morss, Rebecca E; Demuth, Julie L; Lazo, Jeffrey K; Bostrom, Ann

    2016-02-01

    Understanding how people view flash flood risks can help improve risk communication, ultimately improving outcomes. This article analyzes data from 26 mental models interviews about flash floods with members of the public in Boulder, Colorado, to understand their perspectives on flash flood risks and mitigation. The analysis includes a comparison between public and professional perspectives by referencing a companion mental models study of Boulder-area professionals. A mental models approach can help to diagnose what people already know about flash flood risks and responses, as well as any critical gaps in their knowledge that might be addressed through improved risk communication. A few public interviewees mentioned most of the key concepts discussed by professionals as important for flash flood warning decision making. However, most interviewees exhibited some incomplete understandings and misconceptions about aspects of flash flood development and exposure, effects, or mitigation that may lead to ineffective warning decisions when a flash flood threatens. These include important misunderstandings about the rapid evolution of flash floods, the speed of water in flash floods, the locations and times that pose the greatest flash flood risk in Boulder, the value of situational awareness and environmental cues, and the most appropriate responses when a flash flood threatens. The findings point to recommendations for ways to improve risk communication, over the long term and when an event threatens, to help people quickly recognize and understand threats, obtain needed information, and make informed decisions in complex, rapidly evolving extreme weather events such as flash floods. © 2015 Society for Risk Analysis.

  8. Advancing Alternative Analysis: Integration of Decision Science.

    Science.gov (United States)

    Malloy, Timothy F; Zaunbrecher, Virginia M; Batteate, Christina M; Blake, Ann; Carroll, William F; Corbett, Charles J; Hansen, Steffen Foss; Lempert, Robert J; Linkov, Igor; McFadden, Roger; Moran, Kelly D; Olivetti, Elsa; Ostrom, Nancy K; Romero, Michelle; Schoenung, Julie M; Seager, Thomas P; Sinsheimer, Peter; Thayer, Kristina A

    2017-06-13

    Decision analysis-a systematic approach to solving complex problems-offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals. We assessed whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics. A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and were prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups' findings. We concluded that the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients and would also advance the science of decision analysis. We advance four recommendations: a ) engaging the systematic development and evaluation of decision approaches and tools; b ) using case studies to advance the integration of decision analysis into alternatives analysis; c ) supporting transdisciplinary research; and d ) supporting education and outreach efforts. https://doi.org/10.1289/EHP483.

  9. A Comparison of a Machine Learning Model with EuroSCORE II in Predicting Mortality after Elective Cardiac Surgery: A Decision Curve Analysis.

    Science.gov (United States)

    Allyn, Jérôme; Allou, Nicolas; Augustin, Pascal; Philip, Ivan; Martinet, Olivier; Belghiti, Myriem; Provenchere, Sophie; Montravers, Philippe; Ferdynus, Cyril

    2017-01-01

    The benefits of cardiac surgery are sometimes difficult to predict and the decision to operate on a given individual is complex. Machine Learning and Decision Curve Analysis (DCA) are recent methods developed to create and evaluate prediction models. We conducted a retrospective cohort study using a prospective collected database from December 2005 to December 2012, from a cardiac surgical center at University Hospital. The different models of prediction of mortality in-hospital after elective cardiac surgery, including EuroSCORE II, a logistic regression model and a machine learning model, were compared by ROC and DCA. Of the 6,520 patients having elective cardiac surgery with cardiopulmonary bypass, 6.3% died. Mean age was 63.4 years old (standard deviation 14.4), and mean EuroSCORE II was 3.7 (4.8) %. The area under ROC curve (IC95%) for the machine learning model (0.795 (0.755-0.834)) was significantly higher than EuroSCORE II or the logistic regression model (respectively, 0.737 (0.691-0.783) and 0.742 (0.698-0.785), p machine learning model, in this monocentric study, has a greater benefit whatever the probability threshold. According to ROC and DCA, machine learning model is more accurate in predicting mortality after elective cardiac surgery than EuroSCORE II. These results confirm the use of machine learning methods in the field of medical prediction.

  10. Probabilistic Analysis in Management Decision Making

    DEFF Research Database (Denmark)

    Delmar, M. V.; Sørensen, John Dalsgaard

    1992-01-01

    The target group in this paper is people concerned with mathematical economic decision theory. It is shown how the numerically effective First Order Reliability Methods (FORM) can be used in rational management decision making, where some parameters in the applied decision basis are uncertainty...... quantities. The uncertainties are taken into account consistently and the decision analysis is based on the general decision theory in combination with reliability and optimization theory. Examples are shown where the described technique is used and some general conclusion are stated....

  11. Arational heuristic model of economic decision making

    OpenAIRE

    Grandori, Anna

    2010-01-01

    The article discuss the limits of both the rational actor and the behavioral paradigms in explaining and guiding innovative decision making and outlines a model of economic decision making that in the course of being 'heuristic' (research and discovery oriented) is also 'rational' (in the broad sense of following correct reasoning and scientific methods, non 'biasing'). The model specifies a set of 'rational heuristics' for innovative decision making, for the various sub-processes of problem ...

  12. SPATIAL ANALYSIS AND DECISION ASSISTANCE (SADA) TRAINING COURSE

    Science.gov (United States)

    Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

  13. Hierarchical decision modeling essays in honor of Dundar F. Kocaoglu

    CERN Document Server

    2016-01-01

    This volume, developed in honor of Dr. Dundar F. Kocaoglu, aims to demonstrate the applications of the Hierarchical Decision Model (HDM) in different sectors and its capacity in decision analysis. It is comprised of essays from noted scholars, academics and researchers of engineering and technology management around the world. This book is organized into four parts: Technology Assessment, Strategic Planning, National Technology Planning and Decision Making Tools. Dr. Dundar F. Kocaoglu is one of the pioneers of multiple decision models using hierarchies, and creator of the HDM in decision analysis. HDM is a mission-oriented method for evaluation and/or selection among alternatives. A wide range of alternatives can be considered, including but not limited to, different technologies, projects, markets, jobs, products, cities to live in, houses to buy, apartments to rent, and schools to attend. Dr. Kocaoglu’s approach has been adopted for decision problems in many industrial sectors, including electronics rese...

  14. Modeling Adversaries in Counterterrorism Decisions Using Prospect Theory.

    Science.gov (United States)

    Merrick, Jason R W; Leclerc, Philip

    2016-04-01

    Counterterrorism decisions have been an intense area of research in recent years. Both decision analysis and game theory have been used to model such decisions, and more recently approaches have been developed that combine the techniques of the two disciplines. However, each of these approaches assumes that the attacker is maximizing its utility. Experimental research shows that human beings do not make decisions by maximizing expected utility without aid, but instead deviate in specific ways such as loss aversion or likelihood insensitivity. In this article, we modify existing methods for counterterrorism decisions. We keep expected utility as the defender's paradigm to seek for the rational decision, but we use prospect theory to solve for the attacker's decision to descriptively model the attacker's loss aversion and likelihood insensitivity. We study the effects of this approach in a critical decision, whether to screen containers entering the United States for radioactive materials. We find that the defender's optimal decision is sensitive to the attacker's levels of loss aversion and likelihood insensitivity, meaning that understanding such descriptive decision effects is important in making such decisions. © 2014 Society for Risk Analysis.

  15. Using discriminant analysis for credit decision

    Directory of Open Access Journals (Sweden)

    Gheorghiţa DINCĂ

    2015-12-01

    Full Text Available This paper follows to highlight the link between the results obtained applying discriminant analysis and lending decision. For this purpose, we have carried out the research on a sample of 24 Romanian private companies, pertaining to 12 different economic sectors, from I and II categories of Bucharest Stock Exchange, for the period 2010-2012. Our study works with two popular bankruptcy risk’s prediction models, the Altman model and the Anghel model. We have double-checked and confirmed the results of our research by comparing the results from applying the two fore-mentioned models as well as by checking existing debt commitments of each analyzed company to credit institutions during the 2010-2012 period. The aim of this paper was the classification of studied companies into potential bankrupt and non-bankrupt, to assist credit institutions in their decision to grant credit, understanding the approval or rejection algorithm of loan applications and even help potential investors in these ompanies.

  16. Insights from quantum cognitive models for organizational decision making

    OpenAIRE

    White, L.C.; Pothos, E. M.; Busemeyer, J. R.

    2015-01-01

    Organizational decision making is often explored with theories from the heuristics and biases research program, which have demonstrated great value as descriptions of how people in organizations make decisions. Nevertheless, rational analysis and classical probability theory are still seen by many as the best accounts of how decisions should be made and classical probability theory is the preferred framework for cognitive modelling for many researchers. The focus of this work is quantum proba...

  17. Decision analysis for dynamic accounting of nuclear material

    International Nuclear Information System (INIS)

    Shipley, J.P.

    1978-01-01

    Effective materials accounting for special nuclear material in modern fuel cycle facilities will depend heavily on sophisticated data analysis techniques. Decision analysis, which combines elements of estimation theory, decision theory, and systems analysis, is a framework well suited to the development and application of these techniques. Augmented by pattern-recognition tools such as the alarm-sequence chart, decision analysis can be used to reduce errors caused by subjective data evaluation and to condense large collections of data to a smaller set of more descriptive statistics. Application to data from a model plutonium nitrate-to-oxide conversion process illustrates the concepts

  18. Advancing Alternative Analysis: Integration of Decision Science

    DEFF Research Database (Denmark)

    Malloy, Timothy F; Zaunbrecher, Virginia M; Batteate, Christina

    2016-01-01

    Decision analysis-a systematic approach to solving complex problems-offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate......, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect......) engaging the systematic development and evaluation of decision approaches and tools; (2) using case studies to advance the integration of decision analysis into alternatives analysis; (3) supporting transdisciplinary research; and (4) supporting education and outreach efforts....

  19. A model-based analysis of decision making under risk in obsessive-compulsive and hoarding disorders.

    Science.gov (United States)

    Aranovich, Gabriel J; Cavagnaro, Daniel R; Pitt, Mark A; Myung, Jay I; Mathews, Carol A

    2017-07-01

    Attitudes towards risk are highly consequential in clinical disorders thought to be prone to "risky behavior", such as substance dependence, as well as those commonly associated with excessive risk aversion, such as obsessive-compulsive disorder (OCD) and hoarding disorder (HD). Moreover, it has recently been suggested that attitudes towards risk may serve as a behavioral biomarker for OCD. We investigated the risk preferences of participants with OCD and HD using a novel adaptive task and a quantitative model from behavioral economics that decomposes risk preferences into outcome sensitivity and probability sensitivity. Contrary to expectation, compared to healthy controls, participants with OCD and HD exhibited less outcome sensitivity, implying less risk aversion in the standard economic framework. In addition, risk attitudes were strongly correlated with depression, hoarding, and compulsion scores, while compulsion (hoarding) scores were associated with more (less) "rational" risk preferences. These results demonstrate how fundamental attitudes towards risk relate to specific psychopathology and thereby contribute to our understanding of the cognitive manifestations of mental disorders. In addition, our findings indicate that the conclusion made in recent work that decision making under risk is unaltered in OCD is premature. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. A neural model of decision making

    OpenAIRE

    Larsen, Torben

    2008-01-01

    Background: A descriptive neuroeconomic model is aimed for relativity of the concept of economic man to empirical science.Method: A 4-level client-server-integrator model integrating the brain models of McLean and Luria is the general framework for the model of empirical findings.Results: Decision making relies on integration across brain levels of emotional intelligence (LU) and logico-matematico intelligence (RIA), respectively. The integrated decision making formula approaching zero by bot...

  1. Decision analysis for a data collection system of patient-controlled analgesia with a multi-attribute utility model.

    Science.gov (United States)

    Lee, I-Jung; Huang, Shih-Yu; Tsou, Mei-Yung; Chan, Kwok-Hon; Chang, Kuang-Yi

    2010-10-01

    Data collection systems are very important for the practice of patient-controlled analgesia (PCA). This study aimed to evaluate 3 PCA data collection systems and selected the most favorable system with the aid of multiattribute utility (MAU) theory. We developed a questionnaire with 10 items to evaluate the PCA data collection system and 1 item for overall satisfaction based on MAU theory. Three systems were compared in the questionnaire, including a paper record, optic card reader and personal digital assistant (PDA). A pilot study demonstrated a good internal and test-retest reliability of the questionnaire. A weighted utility score combining the relative importance of individual items assigned by each participant and their responses to each question was calculated for each system. Sensitivity analyses with distinct weighting protocols were conducted to evaluate the stability of the final results. Thirty potential users of a PCA data collection system were recruited in the study. The item "easy to use" had the highest median rank and received the heaviest mean weight among all items. MAU analysis showed that the PDA system had a higher utility score than that in the other 2 systems. Sensitivity analyses revealed that both inverse and reciprocal weighting processes favored the PDA system. High correlations between overall satisfaction and MAU scores from miscellaneous weighting protocols suggested a good predictive validity of our MAU-based questionnaire. The PDA system was selected as the most favorable PCA data collection system by the MAU analysis. The item "easy to use" was the most important attribute of the PCA data collection system. MAU theory can evaluate alternatives by taking into account individual preferences of stakeholders and aid in better decision-making. Copyright © 2010 Elsevier. Published by Elsevier B.V. All rights reserved.

  2. True pancreaticoduodenal artery aneurysms: A decision analysis

    International Nuclear Information System (INIS)

    Takao, Hidemasa; Nojo, Takeshi; Ohtomo, Kuni

    2010-01-01

    Purpose: True pancreaticoduodenal artery aneurysms are rare. No definitive study evaluating the natural history of these lesions or their preferred method of treatment has been published. The purpose of this study was to evaluate the outcome of preventive treatment of unruptured pancreaticoduodenal artery aneurysms using a Markov model. Materials and methods: With the use of a Markov model, we performed a decision analysis to evaluate the outcome of preventive treatment of unruptured pancreaticoduodenal artery aneurysms. The risk of rupture and the mortality of preventive treatment are unknown. Therefore, we performed sensitivity analysis using these parameters. Effectiveness was measured in life expectancy. Results: For 80-year-old patients, preventive treatment was dominated by no treatment if mortality rates of preventive treatment were greater than 1.4%, greater than 2.6%, greater than 3.8%, and greater than 4.8% at annual rupture rates of 1%, 2%, 3%, and 4%, respectively. For 50-year-old patients, preventive treatment was dominated by no treatment if mortality rates of preventive treatment were greater than 3.3%, greater than 5.9%, greater than 8.0%, and greater than 9.7% at annual rupture rates of 1%, 2%, 3%, and 4%, respectively. Conclusion: The effectiveness of preventive treatment of unruptured pancreaticoduodenal artery aneurysms depends on the aneurysm rupture rate, mortality rate of preventive treatment, and patient age. Taking into account the effects of these parameters is important in making treatment decisions.

  3. Risk analysis as a decision tool

    International Nuclear Information System (INIS)

    Yadigaroglu, G.; Chakraborty, S.

    1985-01-01

    From 1983 - 1985 a lecture series entitled ''Risk-benefit analysis'' was held at the Swiss Federal Institute of Technology (ETH), Zurich, in cooperation with the Central Department for the Safety of Nuclear Installations of the Swiss Federal Agency of Energy Economy. In that setting the value of risk-oriented evaluation models as a decision tool in safety questions was discussed on a broad basis. Experts of international reputation from the Federal Republic of Germany, France, Canada, the United States and Switzerland have contributed to report in this joint volume on the uses of such models. Following an introductory synopsis on risk analysis and risk assessment the book deals with practical examples in the fields of medicine, nuclear power, chemistry, transport and civil engineering. Particular attention is paid to the dialogue between analysts and decision makers taking into account the economic-technical aspects and social values. The recent chemical disaster in the Indian city of Bhopal again signals the necessity of such analyses. All the lectures were recorded individually. (orig./HP) [de

  4. Safe models for risky decisions

    NARCIS (Netherlands)

    Steingröver, H.M.

    2017-01-01

    In everyday life, we often have to decide between options that differ in their immediate and long-term consequences. Would you, for example, opt for a delicious piece of cake or rather eat a healthy apple? To investigate how people make risky decisions, this thesis focuses on the Iowa gambling task

  5. Environmental Decision Analysis: Meeting the Challenges of Making Good Decisions at CALFED

    Directory of Open Access Journals (Sweden)

    Claire D Tomkins

    2006-09-01

    Full Text Available We present a methodology to support decision making at CALFED based on the principles of decision analysis, an analytical approach to decision making designed to handle complex decisions involving both uncertainty and multiple dimensions of value. The impetus for such an approach is a recognized need to enhance communication between scientists and management and between program elements within CALFED. In addition, the environmental decision analysis framework supports both the explicit representation of uncertainty in the decision problem and communication about risk, important elements of most environmental management decisions. The decision analysis cycle consists of four phases: 1 formulate, 2 evaluate, 3 appraise, and 4 decide. In phase one, we identify the objectives and also the alternatives, or possible actions. To facilitate inter-comparison between proposed actions, we recommend formulation of a set of common metrics for CALFED. In our pilot study, we introduced common metrics for salinity, winter-run Chinook salmon survival, and habitat health. The second phase focuses on quantifying possible impacts on the set of metrics, drawing on existing data, model runs, and expert opinions. For the evaluation phase, we employ tools such as decision trees to assess the system-wide impacts of a given action. In the final phase, tools such as expected cost-benefit analysis, value contribution diagrams, and 3-D tradeoff plots aid communication between various stakeholders, scientists, and managers. While decision analysis provides a spectrum of decision support tools, we emphasize that it does not dictate a solution but rather enhances communication about tradeoffs associated with different actions.

  6. Analysis of a planetary gear modelled with a contour graph considering the decision making complexity of game-tree structures

    Directory of Open Access Journals (Sweden)

    Deptuła Adam

    2017-01-01

    Full Text Available Analysis and synthesis of mechanisms is one of the fundamental tasks of engineering. Mechanisms can suffer from errors due to versatile reasons. Graph-based methods of analysis and synthesis of planetary gears constitute an alternative method for checking their correctness. Previous applications of the graph theory concerned modelling gears for dynamic analysis, kinematic analysis, synthesis, structural analysis, gearshift optimization and automatic design based on so-called graph grammars. Some tasks may be performed only with the methods resulting from the graph theory, e.g. enumeration of structural solutions. The contour plot method consists in distinguishing a series of consecutive rigid units of the analysed mechanism, forming a closed loop (so-called contour. At a later stage, it is possible to analyze the obtained contour graph as a directed graph of dependence. This work presents an example of the application of game-tree structures in describing the contour graph of a planetary gear. In addition, complex parametric tree structures are included.

  7. Decision analysis for deteriorating structures

    International Nuclear Information System (INIS)

    Val, Dimitri V.; Stewart, Mark G.

    2005-01-01

    Measures that improve durability of a structure usually increase its initial cost. Thus, in order to make a decision about a cost-effective solution the life-cycle cost of a structure including cost of structural failure needs to be considered. Due to uncertainties associated with structural properties, loads and environmental conditions the cost of structural failure is a random variable. The paper derives probability distributions of the cost of failure of a single structure and a group of identical structures when single or multiple failures are possible during the service life of a structure. The probability distributions are based on cumulative probabilities of failure of a single structure over its service life. It is assumed that failures occur at discrete points in time, the cost of failure set at the time of decision making remains constant for a particular design solution and the discount rate is a deterministic parameter not changing with time. The probability distributions can be employed to evaluate the expected life-cycle cost or the expected utility, which is then used in decision making. An example, which considers the selection of durability specifications for a reinforced concrete structure built on the coast, illustrates the use of the derived probability distributions

  8. The cost-effectiveness of neonatal screening for Cystic Fibrosis: an analysis of alternative scenarios using a decision model

    Directory of Open Access Journals (Sweden)

    Tu Karen

    2005-08-01

    Full Text Available Abstract Background The use of neonatal screening for cystic fibrosis is widely debated in the United Kingdom and elsewhere, but the evidence available to inform policy is limited. This paper explores the cost-effectiveness of adding screening for cystic fibrosis to an existing routine neonatal screening programme for congenital hypothyroidism and phenylketonuria, under alternative scenarios and assumptions. Methods The study is based on a decision model comparing screening to no screening in terms of a number of outcome measures, including diagnosis of cystic fibrosis, life-time treatment costs, life years and QALYs gained. The setting is a hypothetical UK health region without an existing neonatal screening programme for cystic fibrosis. Results Under initial assumptions, neonatal screening (using an immunoreactive trypsin/DNA two stage screening protocol costs £5,387 per infant diagnosed, or £1.83 per infant screened (1998 costs. Neonatal screening for cystic fibrosis produces an incremental cost-effectiveness of £6,864 per QALY gained, in our base case scenario (an assumed benefit of a 6 month delay in the emergence of symptoms. A difference of 11 months or more in the emergence of symptoms (and mean survival means neonatal screening is both less costly and produces better outcomes than no screening. Conclusion Neonatal screening is expensive as a method of diagnosis. Neonatal screening may be a cost-effective intervention if the hypothesised delays in the onset of symptoms are confirmed. Implementing both antenatal and neonatal screening would undermine potential economic benefits, since a reduction in the birth incidence of cystic fibrosis would reduce the cost-effectiveness of neonatal screening.

  9. Intuitionistic preference modeling and interactive decision making

    CERN Document Server

    Xu, Zeshui

    2014-01-01

    This book offers an in-depth and comprehensive introduction to the priority methods of intuitionistic preference relations, the consistency and consensus improving procedures for intuitionistic preference relations, the approaches to group decision making based on intuitionistic preference relations, the approaches and models for interactive decision making with intuitionistic fuzzy information, and the extended results in interval-valued intuitionistic fuzzy environments.

  10. Solid Waste Management Holistic Decision Modeling

    OpenAIRE

    World Bank

    2008-01-01

    This study provides support to the Bank's ability to conduct client dialogue on solid waste management technology selection, and will contribute to client decision-making. The goal of the study was to fully explore the use of the United States Environmental Protection Agency and the Research Triangle Institute (EPA/RTI) holistic decision model to study alternative solid waste systems in a ...

  11. Seven business models for decision management

    NARCIS (Netherlands)

    dr. Martijn Zoet; Eline de Haan; Koen Smit

    2016-01-01

    Research, advisory companies, consultants and system integrators all predict that a lot of money will be earned with decision management (business rules, algorithms and analytics). But how can you actually make money with decision management or in other words: Which business models are exactly

  12. Application of the Aquifer Impact Model to support decisions at a CO 2 sequestration site: Modeling and Analysis: Application of the Aquifer Impact Model to support decisions at a CO 2

    Energy Technology Data Exchange (ETDEWEB)

    Bacon, Diana Holford [Pacific Northwest National Laboratory, Richland WA USA; Locke II, Randall A. [University of Illinois, Illinois State Geological Survey Champaign IL USA; Keating, Elizabeth [Los Alamos National Laboratory, Los Alamos NM USA; Carroll, Susan [Lawrence Livermore National Laboratory, Livermore CA USA; Iranmanesh, Abbas [University of Illinois, Illinois State Geological Survey Champaign IL USA; Mansoor, Kayyum [Lawrence Livermore National Laboratory, Livermore CA USA; Wimmer, Bracken [University of Illinois, Illinois State Geological Survey Champaign IL USA; Zheng, Liange [Lawrence Berkeley National Laboratory, Berkeley CA USA; Shao, Hongbo [University of Illinois, Illinois State Geological Survey Champaign IL USA; Greenberg, Sallie E. [University of Illinois, Illinois State Geological Survey Champaign IL USA

    2017-10-04

    The National Risk Assessment Partnership (NRAP) has developed a suite of tools to assess and manage risk at CO2 sequestration sites (1). The NRAP tool suite includes the Aquifer Impact Model (AIM), based on reduced order models developed using site-specific data from two aquifers (alluvium and carbonate). The models accept aquifer parameters as a range of variable inputs so they may have more broad applicability. Guidelines have been developed for determining the aquifer types for which the ROMs should be applicable. This paper considers the applicability of the aquifer models in AIM to predicting the impact of CO2 or Brine leakage were it to occur at the Illinois Basin Decatur Project (IBDP). Based on the results of the sensitivity analysis, the hydraulic parameters and leakage source term magnitude are more sensitive than clay fraction or cation exchange capacity. Sand permeability was the only hydraulic parameter measured at the IBDP site. More information on the other hydraulic parameters, such as sand fraction and sand/clay correlation lengths, could reduce uncertainty in risk estimates. Some non-adjustable parameters, such as the initial pH and TDS and the pH no-impact threshold, are significantly different for the ROM than for the observations at the IBDP site. The reduced order model could be made more useful to a wider range of sites if the initial conditions and no-impact threshold values were adjustable parameters.

  13. GIS-based suitability modeling and multi-criteria decision analysis for utility scale solar plants in four states in the Southeast U.S

    Science.gov (United States)

    Tisza, Kata

    Photovoltaic (PV) development shows significantly smaller growth in the Southeast U.S., than in the Southwest; which is mainly due to the low cost of fossil-fuel based energy production in the region and the lack of solar incentives. However, the Southeast has appropriate insolation conditions (4.0-6.0 KWh/m2/day) for photovoltaic deployment and in the past decade the region has experienced the highest population growth for the entire country. These factors, combined with new renewable energy portfolio policies, could create an opportunity for PV to provide some of the energy that will be required to sustain this growth. The goal of the study was to investigate the potential for PV generation in the Southeast region by identifying suitable areas for a utility-scale solar power plant deployment. Four states with currently low solar penetration were studied: Georgia, North Carolina, South Carolina and Tennessee. Feasible areas were assessed with Geographic Information Systems (GIS) software using solar, land use and population growth criteria combined with proximity to transmission lines and roads. After the GIS-based assessment of the areas, technological potential was calculated for each state. Multi-decision analysis model (MCDA) was used to simulate the decision making method for a strategic PV installation. The model accounted for all criteria necessary to consider in case of a PV development and also included economic and policy criteria, which is thought to be a strong influence on the PV market. Three different scenarios were established, representing decision makers' theoretical preferences. Map layers created in the first part were used as basis for the MCDA and additional technical, economic and political/market criteria were added. A sensitivity analysis was conducted to test the model's robustness. Finally, weighted criteria were assigned to the GIS map layers, so that the different preference systems could be visualized. As a result, lands suitable for

  14. Model predictive control using fuzzy decision functions

    NARCIS (Netherlands)

    Kaymak, U.; Costa Sousa, da J.M.

    2001-01-01

    Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the

  15. Decision analysis of shoreline protection under climate change uncertainty

    Science.gov (United States)

    Chao, Philip T.; Hobbs, Benjamin F.

    1997-04-01

    If global warming occurs, it could significantly affect water resource distribution and availability. Yet it is unclear whether the prospect of such change is relevant to water resources management decisions being made today. We model a shoreline protection decision problem with a stochastic dynamic program (SDP) to determine whether consideration of the possibility of climate change would alter the decision. Three questions are addressed with the SDP: (l) How important is climate change compared to other uncertainties?, (2) What is the economic loss if climate change uncertainty is ignored?, and (3) How does belief in climate change affect the timing of the decision? In the case study, sensitivity analysis shows that uncertainty in real discount rates has a stronger effect upon the decision than belief in climate change. Nevertheless, a strong belief in climate change makes the shoreline protection project less attractive and often alters the decision to build it.

  16. A benefit–risk assessment model for statins using multicriteria decision analysis based on a discrete choice experiment in Korean patients

    Directory of Open Access Journals (Sweden)

    Byun JH

    2016-06-01

    Full Text Available Ji-Hye Byun,1 Sun-Hong Kwon,1 Ji-Hye Ha,2 Eui-Kyung Lee1 1School of Pharmacy, Sungkyunkwan University, Suwon-si, Gyeonggi-do, 2Ministry of Food and Drug Safety, Cheongju-si, Chungcheongbuk-do, South Korea Purpose: The benefit–risk balance for drugs can alter post approval owing to additional data on efficacy or adverse events. This study developed a quantitative benefit–risk assessment (BRA model for statins using multicriteria decision analysis with discrete choice experiments and compared a recent BRA with that at the time of approval. Patients and methods: Following a systematic review of the literature, the benefit criteria within the statin BRA model were defined as a reduction in the plasma low-density lipoprotein cholesterol level and a reduction in myocardial infarction incidence; the risk criteria were hepatotoxicity (Liv and fatal rhabdomyolysis (Rha. The scores for these criteria were estimated using mixed treatment comparison methods. Weighting was calculated from a discrete choice experiment involving 203 Korean patients. The scores and weights were integrated to produce an overall value representing the benefit–risk balance, and sensitivity analyses were conducted. Results: In this BRA model, low-density lipoprotein (relative importance [RI]: 37.50% was found to be a more important benefit criterion than myocardial infarction (RI: 35.43%, and Liv (RI: 16.28% was a more important risk criterion than Rha (RI: 10.79%. Patients preferred atorvastatin, and the preference ranking of cerivastatin and simvastatin was switched post approval because of the emergence of additional risk information related to cerivastatin. Conclusion: A quantitative statin BRA model confirmed that the preference ranking of statins changed post approval because of the identification of additional benefits or risks. Keywords: multicriteria decision analysis, statin, quantitative benefit–risk assessment, discrete choice experiment

  17. IDENTIFYING OPERATIONAL REQUIREMENTS TO SELECT SUITABLE DECISION MODELS FOR A PUBLIC SECTOR EPROCUREMENT DECISION SUPPORT SYSTEM

    Directory of Open Access Journals (Sweden)

    Mohamed Adil

    2014-10-01

    Full Text Available Public sector procurement should be a transparent and fair process. Strict legal requirements are enforced on public sector procurement to make it a standardised process. To make fair decisions on selecting suppliers, a practical method which adheres to legal requirements is important. The research that is the base for this paper aimed at identifying a suitable Multi-Criteria Decision Analysis (MCDA method for the specific legal and functional needs of the Maldivian Public Sector. To identify such operational requirements, a set of focus group interviews were conducted in the Maldives with public officials responsible for procurement decision making. Based on the operational requirements identified through focus groups, criteria-based evaluation is done on published MCDA methods to identify the suitable methods for e-procurement decision making. This paper describes the identification of the operational requirements and the results of the evaluation to select suitable decision models for the Maldivian context.

  18. Computer models for economic and silvicultural decisions

    Science.gov (United States)

    Rosalie J. Ingram

    1989-01-01

    Computer systems can help simplify decisionmaking to manage forest ecosystems. We now have computer models to help make forest management decisions by predicting changes associated with a particular management action. Models also help you evaluate alternatives. To be effective, the computer models must be reliable and appropriate for your situation.

  19. Comprehensive decision tree models in bioinformatics.

    Directory of Open Access Journals (Sweden)

    Gregor Stiglic

    Full Text Available PURPOSE: Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. METHODS: This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. RESULTS: The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. CONCLUSIONS: The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets

  20. Comprehensive decision tree models in bioinformatics.

    Science.gov (United States)

    Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter

    2012-01-01

    Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly

  1. Identification of reverse logistics decision types from mathematical models

    Directory of Open Access Journals (Sweden)

    Pascual Cortés Pellicer

    2018-04-01

    Full Text Available Purpose: The increase in social awareness, politics and environmental regulation, the scarcity of raw materials and the desired “green” image, are some of the reasons that lead companies to decide for implement processes of Reverse Logistics (RL. At the time when incorporate new RL processes as key business processes, new and important decisions need to be made. Identification and knowledge of these decisions, including the information available and the implications for the company or supply chain, will be fundamental for decision-makers to achieve the best results. In the present work, the main types of RL decisions are identified. Design/methodology/approach: This paper is based on the analysis of mathematical models designed as tools to aid decision making in the field of RL. Once the types of interest work to be analyzed are defined, those studies that really deal about the object of study are searched and analyzed. The decision variables that are taken at work are identified and grouped according to the type of decision and, finally, are showed the main types of decisions used in mathematical models developed in the field of RL.     Findings: The principal conclusion of the research is that the most commonly addressed decisions with mathematical models in the field of RL are those related to the network’s configuration, followed by tactical/operative decisions such as the selections of product’s treatments to realize and the policy of returns or prices, among other decisions. Originality/value: The identification of the main decisions types of the reverse logistics will allow the managers of these processes to know and understand them better, while offer an integrated vision of them, favoring the achievement of better results.

  2. A decision model for planetary missions

    Science.gov (United States)

    Hazelrigg, G. A., Jr.; Brigadier, W. L.

    1976-01-01

    Many techniques developed for the solution of problems in economics and operations research are directly applicable to problems involving engineering trade-offs. This paper investigates the use of utility theory for decision making in planetary exploration space missions. A decision model is derived that accounts for the objectives of the mission - science - the cost of flying the mission and the risk of mission failure. A simulation methodology for obtaining the probability distribution of science value and costs as a function spacecraft and mission design is presented and an example application of the decision methodology is given for various potential alternatives in a comet Encke mission.

  3. Decision Vulnerability Analysis (DVA) Program

    Science.gov (United States)

    2014-05-01

    31 14 Graphical Representation of the Summary Judgments of the Effectiveness, Vulnerability, and Understanding of the Subsystems’ as Judged by...posed several challenges. Numerous organizational typologies have been suggested over the years ( Robbins , 1994), and these typologies are often based...structure and functioning from a typology perspective ( Robbins , 1994), excerpts from a task analysis that described how the analysts currently performed

  4. A regret theory approach to decision curve analysis: a novel method for eliciting decision makers' preferences and decision-making.

    Science.gov (United States)

    Tsalatsanis, Athanasios; Hozo, Iztok; Vickers, Andrew; Djulbegovic, Benjamin

    2010-09-16

    Decision curve analysis (DCA) has been proposed as an alternative method for evaluation of diagnostic tests, prediction models, and molecular markers. However, DCA is based on expected utility theory, which has been routinely violated by decision makers. Decision-making is governed by intuition (system 1), and analytical, deliberative process (system 2), thus, rational decision-making should reflect both formal principles of rationality and intuition about good decisions. We use the cognitive emotion of regret to serve as a link between systems 1 and 2 and to reformulate DCA. First, we analysed a classic decision tree describing three decision alternatives: treat, do not treat, and treat or no treat based on a predictive model. We then computed the expected regret for each of these alternatives as the difference between the utility of the action taken and the utility of the action that, in retrospect, should have been taken. For any pair of strategies, we measure the difference in net expected regret. Finally, we employ the concept of acceptable regret to identify the circumstances under which a potentially wrong strategy is tolerable to a decision-maker. We developed a novel dual visual analog scale to describe the relationship between regret associated with "omissions" (e.g. failure to treat) vs. "commissions" (e.g. treating unnecessary) and decision maker's preferences as expressed in terms of threshold probability. We then proved that the Net Expected Regret Difference, first presented in this paper, is equivalent to net benefits as described in the original DCA. Based on the concept of acceptable regret we identified the circumstances under which a decision maker tolerates a potentially wrong decision and expressed it in terms of probability of disease. We present a novel method for eliciting decision maker's preferences and an alternative derivation of DCA based on regret theory. Our approach may be intuitively more appealing to a decision-maker, particularly

  5. A regret theory approach to decision curve analysis: A novel method for eliciting decision makers' preferences and decision-making

    Directory of Open Access Journals (Sweden)

    Vickers Andrew

    2010-09-01

    Full Text Available Abstract Background Decision curve analysis (DCA has been proposed as an alternative method for evaluation of diagnostic tests, prediction models, and molecular markers. However, DCA is based on expected utility theory, which has been routinely violated by decision makers. Decision-making is governed by intuition (system 1, and analytical, deliberative process (system 2, thus, rational decision-making should reflect both formal principles of rationality and intuition about good decisions. We use the cognitive emotion of regret to serve as a link between systems 1 and 2 and to reformulate DCA. Methods First, we analysed a classic decision tree describing three decision alternatives: treat, do not treat, and treat or no treat based on a predictive model. We then computed the expected regret for each of these alternatives as the difference between the utility of the action taken and the utility of the action that, in retrospect, should have been taken. For any pair of strategies, we measure the difference in net expected regret. Finally, we employ the concept of acceptable regret to identify the circumstances under which a potentially wrong strategy is tolerable to a decision-maker. Results We developed a novel dual visual analog scale to describe the relationship between regret associated with "omissions" (e.g. failure to treat vs. "commissions" (e.g. treating unnecessary and decision maker's preferences as expressed in terms of threshold probability. We then proved that the Net Expected Regret Difference, first presented in this paper, is equivalent to net benefits as described in the original DCA. Based on the concept of acceptable regret we identified the circumstances under which a decision maker tolerates a potentially wrong decision and expressed it in terms of probability of disease. Conclusions We present a novel method for eliciting decision maker's preferences and an alternative derivation of DCA based on regret theory. Our approach may

  6. Decisions, decisions: analysis of age, cohort, and time of testing on framing of risky decision options.

    Science.gov (United States)

    Mayhorn, Christopher B; Fisk, Arthur D; Whittle, Justin D

    2002-01-01

    Decision making in uncertain environments is a daily challenge faced by adults of all ages. Framing decision options as either gains or losses is a common method of altering decision-making behavior. In the experiment reported here, benchmark decision-making data collected in the 1970s by Tversky and Kahneman (1981, 1988) were compared with data collected from current samples of young and older adults to determine whether behavior was consistent across time. Although differences did emerge between the benchmark and the present samples, the effect of framing on decision behavior was relatively stable. The present findings suggest that adults of all ages are susceptible to framing effects. Results also indicated that apparent age differences might be better explained by an analysis of cohort and time-of-testing effects. Actual or potential applications of this research include an understanding of how framing might influence the decision-making behavior of people of all ages in a number of applied contexts, such as product warning interactions and medical decision scenarios.

  7. Marketing data, models and decisions

    NARCIS (Netherlands)

    Wedel, M; Kamakura, W; Bockenholt, U

    Our comments about the paper by Leeflang and Wittink [Internat. J. Res. Marketing, 17 (2000) 105] comprise of two components: first, we address two issues on which we disagree with Leeflang and Wittink: soft versus hard data, and individual-level versus segment-level models. Secondly, we supplement

  8. New decision analytical models for management of intracranial aneurysms

    NARCIS (Netherlands)

    Koffijberg, H.

    2008-01-01

    This thesis addresses decision analysis, cost-effectiveness models and the analysis of heterogeneity, applied to intracranial aneurysms and subarachnoid hemorrhage (SAH). Subarachnoid hemorrhage is a subset of stroke that usually occurs at relatively young age and has poor prognosis. Although, the

  9. A Model of Decision-Making Based on Critical Thinking

    OpenAIRE

    Uluçınar, Ufuk; Aypay, Ahmet

    2016-01-01

    The aim of this study is to examine the causal relationships between high school students' inquisitiveness, open-mindedness, causal thinking, and rational and intuitive decision-making dispositions through an assumed model based on research data. This study was designed in correlational model. Confirmatory factor analysis and path analysis, which are structural equation modelling applications, were used to explain these relationships. The participants were 404 students studying in five high s...

  10. Risk Decision Making Based on Decision-theoretic Rough Set: A Three-way View Decision Model

    OpenAIRE

    Huaxiong Li; Xianzhong Zhou

    2011-01-01

    Rough set theory has witnessed great success in data mining and knowledge discovery, which provides a good support for decision making on a certain data. However, a practical decision problem always shows diversity under the same circumstance according to different personality of the decision makers. A simplex decision model can not provide a full description on such diverse decisions. In this article, a review of Pawlak rough set models and probabilistic rough set models is presented, and a ...

  11. Financial Analysis, Budgeting, Decision and Control

    Directory of Open Access Journals (Sweden)

    Mariana Rodica TIRLEA

    2013-12-01

    Full Text Available The economic processes taking place in the economic environment are stochastic processes that involve and imply risks, arising from product diversification, competition, financial derivatives transactions: swaps, futures, options and from the large number of actors involved in the stock market with a higher or a smaller uncertainty degree. Competition and competitiveness, led to major and rapid change in the business environment, they determined actors participating in the economy to find solutions and methods of collecting and processing data, in such a way that, after being transformed into information they quickly help based on their analysis in decision making, planning and financial forecasting, having an effect on increasing their economic efficiency. In these circumstances the financial analysis, decision, forecasting and control, should be based on quality information that should be a value creation source. The active nature of the financial function implies the existence of a substantially large share of financial analysis, financial decision, forecasting and control.

  12. METHODOLOGY FOR ANALYSIS OF DECISION MAKING IN AIR NAVIGATION SYSTEM

    Directory of Open Access Journals (Sweden)

    Volodymyr Kharchenko

    2011-03-01

    Full Text Available Abstract. In the research of Air Navigation System as a complex socio-technical system the methodologyof analysis of human-operator's decision-making has been developed. The significance of individualpsychologicalfactors as well as the impact of socio-psychological factors on the professional activities of ahuman-operator during the flight situation development from normal to catastrophic were analyzed. On thebasis of the reflexive theory of bipolar choice the expected risks of decision-making by the Air NavigationSystem's operator influenced by external environment, previous experience and intentions were identified.The methods for analysis of decision-making by the human-operator of Air Navigation System usingstochastic networks have been developed.Keywords: Air Navigation System, bipolar choice, human operator, decision-making, expected risk, individualpsychologicalfactors, methodology of analysis, reflexive model, socio-psychological factors, stochastic network.

  13. Towards a Decision Making Model for City Break Travel

    OpenAIRE

    Dunne, Gerard; Flanagan, Sheila; Buckley, Joan

    2011-01-01

    Purpose The purpose of this paper is to examine the city break travel decision and in particular to develop a decision making model that reflects the characteristics of this type of trip taking. Method The research follows a sequential mixed methods approach consisting of two phases. Phase One involves a quantitative survey of 1,000 visitors to Dublin, from which city break and non city break visitor cohorts are separated and compared. Phase Two entails a qualitative analysis (involvin...

  14. PROBIT MODEL ANALYSIS OF SMALLHOLDER’S FARMERS DECISION TO USE AGROCHEMICAL INPUTS IN GWAGWALADA AND KUJE AREA COUNCILS OF FEDERAL CAPITAL TERRITORY, ABUJA, NIGERIA

    Directory of Open Access Journals (Sweden)

    Omotayo Olugbenga Alabi

    2014-01-01

    Full Text Available This study examined Probit model analysis of smallholder’s farmers decision to use agrochemical inputs in Gwagwalada and Kuje Area Councils of Federal Capital Territory, Abuja, Nigeria. Primary data were used for this study. Data were obtained using structured questionnaire. The questionnaires were administered to sixty smallholder’s farmers sampled using a two-stage sampling technique. Data obtained were analyzed using descriptive statistics and Probit model. Eight estimators, age; farm-size; education–level; extension services; access to credit; off-farm income; experiences in farming; in the Probit model were found statistically significant. Results show that the probability of using agrochemical inputs increases with age; farm-size; family-size; education-level; extension services; experiences in farming but decreases where they have off-farm income and access to credits. Mc Fadden Pseudo-R 2 gives 0.6866 and Probit model correctly classified 93%. This study concluded that capacity of agricultural extension agents needs to be improved in the study area to educate farmers to invest in agrochemicals and improved agricultural technologies. Also, Government needs to improve on good road networks and appropriate policies to regulate standard, use, safety needs and environment of use of agrochemicals in the study area.

  15. Methodology and preliminary models for analyzing nuclear safeguards decisions

    International Nuclear Information System (INIS)

    1978-11-01

    This report describes a general analytical tool designed to assist the NRC in making nuclear safeguards decisions. The approach is based on decision analysis--a quantitative procedure for making decisions under uncertain conditions. The report: describes illustrative models that quantify the probability and consequences of diverted special nuclear material and the costs of safeguarding the material, demonstrates a methodology for using this information to set safeguards regulations (safeguards criteria), and summarizes insights gained in a very preliminary assessment of a hypothetical reprocessing plant

  16. Methodology and preliminary models for analyzing nuclear-safeguards decisions

    International Nuclear Information System (INIS)

    Judd, B.R.; Weissenberger, S.

    1978-11-01

    This report describes a general analytical tool designed with Lawrence Livermore Laboratory to assist the Nuclear Regulatory Commission in making nuclear safeguards decisions. The approach is based on decision analysis - a quantitative procedure for making decisions under uncertain conditions. The report: describes illustrative models that quantify the probability and consequences of diverted special nuclear material and the costs of safeguarding the material; demonstrates a methodology for using this information to set safeguards regulations (safeguards criteria); and summarizes insights gained in a very preliminary assessment of a hypothetical reprocessing plant

  17. Medical decision making tools: Bayesian analysis and ROC analysis

    International Nuclear Information System (INIS)

    Lee, Byung Do

    2006-01-01

    During the diagnostic process of the various oral and maxillofacial lesions, we should consider the following: 'When should we order diagnostic tests? What tests should be ordered? How should we interpret the results clinically? And how should we use this frequently imperfect information to make optimal medical decision?' For the clinicians to make proper judgement, several decision making tools are suggested. This article discusses the concept of the diagnostic accuracy (sensitivity and specificity values) with several decision making tools such as decision matrix, ROC analysis and Bayesian analysis. The article also explain the introductory concept of ORAD program

  18. Risk Analysis and Decision Making FY 2013 Milestone Report

    Energy Technology Data Exchange (ETDEWEB)

    Engel, David W.; Dalton, Angela C.; Dale, Crystal; Jones, Edward; Thompson, J.

    2013-06-01

    Risk analysis and decision making is one of the critical objectives of CCSI, which seeks to use information from science-based models with quantified uncertainty to inform decision makers who are making large capital investments. The goal of this task is to develop tools and capabilities to facilitate the development of risk models tailored for carbon capture technologies, quantify the uncertainty of model predictions, and estimate the technical and financial risks associated with the system. This effort aims to reduce costs by identifying smarter demonstrations, which could accelerate development and deployment of the technology by several years.

  19. 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.

  20. Due Process in Dual Process: Model-Recovery Simulations of Decision-Bound Strategy Analysis in Category Learning

    Science.gov (United States)

    Edmunds, Charlotte E. R.; Milton, Fraser; Wills, Andy J.

    2018-01-01

    Behavioral evidence for the COVIS dual-process model of category learning has been widely reported in over a hundred publications (Ashby & Valentin, 2016). It is generally accepted that the validity of such evidence depends on the accurate identification of individual participants' categorization strategies, a task that usually falls to…

  1. an analysis of perceived prominent decision making areas in ...

    African Journals Online (AJOL)

    p2333147

    Keywords: Game ranch management, decision making, risk perception, springbuck. ABSTRACT ..... environment, herd management (herd structure) and marketing and client satisfaction .... Prospect theory: An analysis of decision under risk.

  2. A heuristic forecasting model for stock decision

    OpenAIRE

    Zhang, D.; Jiang, Q.; Li, X.

    2005-01-01

    This paper describes a heuristic forecasting model based on neural networks for stock decision-making. Some heuristic strategies are presented for enhancing the learning capability of neural networks and obtaining better trading performance. The China Shanghai Composite Index is used as case study. The forecasting model can forecast the buying and selling signs according to the result of neural network prediction. Results are compared with a benchmark buy-and-hold strategy. ...

  3. An Integrated Multi-Criteria Decision Making Model and AHP Weighting Uncertainty Analysis for Sustainability Assessment of Coal-Fired Power Units

    Directory of Open Access Journals (Sweden)

    Dianfa Wu

    2018-05-01

    Full Text Available The transformation of the power generation industry from coal-based to more sustainable energy sources is an irreversible trend. In China, the coal-fired power plant, as the main electric power supply facility at present, needs to know its own sustainability level to face the future competition. A hybrid multi-criteria decision making (MCDM model is proposed in this paper to assess the sustainability levels of the existing Chinese coal-fired power units. The areal grey relational analysis (AGRA method is involved in the hybrid model, and a combined weighting method is used to determine the priorities of the criteria. The combining weight fuses the fuzzy rough set (FRS and entropy objective weighting method together with the analytic hierarchy process (AHP subjective weighting method by game theory. Moreover, an AHP weighting uncertainty analysis using Monte Carlo (MC simulation is introduced to measure the uncertainty of the results, and a 95 percent confidence interval (CI is defined as the uncertainty measurement of the alternatives. A case study about eight coal-fired power units is carried out with a criteria system, which contains five aspects in an operational perspective, such as the flexibility, economic, environmental, reliability and technical criterion. The sustainability assessment is performed at the unit level, and the results give a priority rank of the eight alternatives; additionally, the uncertainty analysis supplies the extra information from a statistical perspective. This work expands a novel hybrid MCDM method to the sustainability assessment of the power generation systems, and it may be a benefit to the energy enterprises in assessing the sustainability at the unit level and enhance its ability in future sustainable development.

  4. Including model uncertainty in risk-informed decision making

    International Nuclear Information System (INIS)

    Reinert, Joshua M.; Apostolakis, George E.

    2006-01-01

    Model uncertainties can have a significant impact on decisions regarding licensing basis changes. We present a methodology to identify basic events in the risk assessment that have the potential to change the decision and are known to have significant model uncertainties. Because we work with basic event probabilities, this methodology is not appropriate for analyzing uncertainties that cause a structural change to the model, such as success criteria. We use the risk achievement worth (RAW) importance measure with respect to both the core damage frequency (CDF) and the change in core damage frequency (ΔCDF) to identify potentially important basic events. We cross-check these with generically important model uncertainties. Then, sensitivity analysis is performed on the basic event probabilities, which are used as a proxy for the model parameters, to determine how much error in these probabilities would need to be present in order to impact the decision. A previously submitted licensing basis change is used as a case study. Analysis using the SAPHIRE program identifies 20 basic events as important, four of which have model uncertainties that have been identified in the literature as generally important. The decision is fairly insensitive to uncertainties in these basic events. In three of these cases, one would need to show that model uncertainties would lead to basic event probabilities that would be between two and four orders of magnitude larger than modeled in the risk assessment before they would become important to the decision. More detailed analysis would be required to determine whether these higher probabilities are reasonable. Methods to perform this analysis from the literature are reviewed and an example is demonstrated using the case study

  5. A quantitative benefit-risk assessment approach to improve decision making in drug development: Application of a multicriteria decision analysis model in the development of combination therapy for overactive bladder.

    Science.gov (United States)

    de Greef-van der Sandt, I; Newgreen, D; Schaddelee, M; Dorrepaal, C; Martina, R; Ridder, A; van Maanen, R

    2016-04-01

    A multicriteria decision analysis (MCDA) approach was developed and used to estimate the benefit-risk of solifenacin and mirabegron and their combination in the treatment of overactive bladder (OAB). The objectives were 1) to develop an MCDA tool to compare drug effects in OAB quantitatively, 2) to establish transparency in the evaluation of the benefit-risk profile of various dose combinations, and 3) to quantify the added value of combination use compared to monotherapies. The MCDA model was developed using efficacy, safety, and tolerability attributes and the results of a phase II factorial design combination study were evaluated. Combinations of solifenacin 5 mg and mirabegron 25 mg and mirabegron 50 (5+25 and 5+50) scored the highest clinical utility and supported combination therapy development of solifenacin and mirabegron for phase III clinical development at these dose regimens. This case study underlines the benefit of using a quantitative approach in clinical drug development programs. © 2015 The American Society for Clinical Pharmacology and Therapeutics.

  6. Modeling reproductive decisions with simple heuristics

    Directory of Open Access Journals (Sweden)

    Peter Todd

    2013-10-01

    Full Text Available BACKGROUND Many of the reproductive decisions that humans make happen without much planning or forethought, arising instead through the use of simple choice rules or heuristics that involve relatively little information and processing. Nonetheless, these heuristic-guided decisions are typically beneficial, owing to humans' ecological rationality - the evolved fit between our constrained decision mechanisms and the adaptive problems we face. OBJECTIVE This paper reviews research on the ecological rationality of human decision making in the domain of reproduction, showing how fertility-related decisions are commonly made using various simple heuristics matched to the structure of the environment in which they are applied, rather than being made with information-hungry mechanisms based on optimization or rational economic choice. METHODS First, heuristics for sequential mate search are covered; these heuristics determine when to stop the process of mate search by deciding that a good-enough mate who is also mutually interested has been found, using a process of aspiration-level setting and assessing. These models are tested via computer simulation and comparison to demographic age-at-first-marriage data. Next, a heuristic process of feature-based mate comparison and choice is discussed, in which mate choices are determined by a simple process of feature-matching with relaxing standards over time. Parental investment heuristics used to divide resources among offspring are summarized. Finally, methods for testing the use of such mate choice heuristics in a specific population over time are then described.

  7. Decision Analysis Science Modeling for Application and Fielding Selection Applied to Equipment Dismantlement Technologies. Final Report January 1998

    International Nuclear Information System (INIS)

    Lagos, L.E.; Ebadian, M.A.

    1998-01-01

    During the decontamination and decommissioning (D and D) activities being conducted by the U.S. Department of Energy (DOE), approximately 550,000 metric tons of contaminated metal will be generated by the disposition of contaminated buildings. The majority of the structural steel is considered to be radiologically contaminated. The D and D activities require the treatment of the structural steel to reduce occupational and environmental radiological exposures during dismantlement. Treatment technologies may also be required for possible recycling. Many proven commercial treatment technologies are available. These treatment processes vary in aggressiveness, safety requirements, secondary waste generation, necessary capital, and operation and maintenance costs. Choosing the appropriate technology to meet the decontamination objectives for structural steel is a difficult process. A single information source comparing innovative and nuclear and non-nuclear technologies in the areas of safety, cost and effectiveness is not currently commercially available to perform a detailed analysis. This study presents comparable data related to operation and maintenance, cost, and health and safely aspects of three readily available technologies and one innovative technology for nuclear decontamination. The technologies include Advance Recyclable Media System (ARMStrademark), NELCO Porta Shot Blasttrademark (JHJ-2000), Pegasus Coating Removal System 7 (PCRS-7) and the innovative laser ablation technology called the Yag Erasertrademark

  8. Integrating decision management with UML modeling concepts and tools

    DEFF Research Database (Denmark)

    Könemann, Patrick

    2009-01-01

    , but also for guiding the user by proposing subsequent decisions. In model-based software development, many decisions directly affect the structural and behavioral models used to describe and develop a software system and its architecture. However, the decisions are typically not connected to these models...... of formerly disconnected tools could improve tool usability as well as decision maker productivity....

  9. A Composite Modelling Approach to Decision Support by the Use of the CBA-DK Model

    DEFF Research Database (Denmark)

    Barfod, Michael Bruhn; Salling, Kim Bang; Leleur, Steen

    2007-01-01

    This paper presents a decision support system for assessment of transport infrastructure projects. The composite modelling approach, COSIMA, combines a cost-benefit analysis by use of the CBA-DK model with multi-criteria analysis applying the AHP and SMARTER techniques. The modelling uncertaintie...

  10. The need for consumer behavior analysis in health care coverage decisions.

    Science.gov (United States)

    Thompson, A M; Rao, C P

    1990-01-01

    Demographic analysis has been the primary form of analysis connected with health care coverage decisions. This paper reviews past demographic research and shows the need to use behavioral analyses for health care coverage policy decisions. A behavioral model based research study is presented and a case is made for integrated study into why consumers make health care coverage decisions.

  11. An extended data envelopment analysis for the decision-making

    Directory of Open Access Journals (Sweden)

    Xiao-Li Meng

    2017-10-01

    Full Text Available Abstract Based on the CCR model, we propose an extended data envelopment analysis to evaluate the efficiency of decision making units with historical input and output data. The contributions of the work are threefold. First, the input and output data of the evaluated decision making unit are variable over time, and time series method is used to analyze and predict the data. Second, there are many sample decision making units, which are divided into several ordered sample standards in terms of production strategy, and the constraint condition consists of one of the sample standards. Furthermore, the efficiency is illustrated by considering the efficiency relationship between the evaluated decision making unit and sample decision making units from constraint condition. Third, to reduce the computation complexity, we introduce an algorithm based on the binary search tree in the model to choose the sample standard that has similar behavior with the evaluated decision making unit. Finally, we provide two numerical examples to illustrate the proposed model.

  12. A decision model for energy resource selection in China

    International Nuclear Information System (INIS)

    Wang Bing; Kocaoglu, Dundar F.; Daim, Tugrul U.; Yang Jiting

    2010-01-01

    This paper evaluates coal, petroleum, natural gas, nuclear energy and renewable energy resources as energy alternatives for China through use of a hierarchical decision model. The results indicate that although coal is still the major preferred energy alternative, it is followed closely by renewable energy. The sensitivity analysis indicates that the most critical criterion for energy selection is the current energy infrastructure. A hierarchical decision model is used, and expert judgments are quantified, to evaluate the alternatives. Criteria used for the evaluations are availability, current energy infrastructure, price, safety, environmental impacts and social impacts.

  13. Bureaucrats Versus the Ballot Box in Foreign Policy Decision Making: An Experimental Analysis of the Bureaucratic Politics Model and the Poliheuristic Theory

    Science.gov (United States)

    Christensen, Eben J.; Redd, Steven B.

    2004-01-01

    The bureaucratic politics model and the poliheuristic theory are used to examine how political advice presented in various contexts influences choice. Organizational advisers who offer endogenous political advice are compared with situations in which the decision maker is offered advice by a separate, or exogenous, political adviser. Results show…

  14. Reliability analysis framework for computer-assisted medical decision systems

    International Nuclear Information System (INIS)

    Habas, Piotr A.; Zurada, Jacek M.; Elmaghraby, Adel S.; Tourassi, Georgia D.

    2007-01-01

    We present a technique that enhances computer-assisted decision (CAD) systems with the ability to assess the reliability of each individual decision they make. Reliability assessment is achieved by measuring the accuracy of a CAD system with known cases similar to the one in question. The proposed technique analyzes the feature space neighborhood of the query case to dynamically select an input-dependent set of known cases relevant to the query. This set is used to assess the local (query-specific) accuracy of the CAD system. The estimated local accuracy is utilized as a reliability measure of the CAD response to the query case. The underlying hypothesis of the study is that CAD decisions with higher reliability are more accurate. The above hypothesis was tested using a mammographic database of 1337 regions of interest (ROIs) with biopsy-proven ground truth (681 with masses, 656 with normal parenchyma). Three types of decision models, (i) a back-propagation neural network (BPNN), (ii) a generalized regression neural network (GRNN), and (iii) a support vector machine (SVM), were developed to detect masses based on eight morphological features automatically extracted from each ROI. The performance of all decision models was evaluated using the Receiver Operating Characteristic (ROC) analysis. The study showed that the proposed reliability measure is a strong predictor of the CAD system's case-specific accuracy. Specifically, the ROC area index for CAD predictions with high reliability was significantly better than for those with low reliability values. This result was consistent across all decision models investigated in the study. The proposed case-specific reliability analysis technique could be used to alert the CAD user when an opinion that is unlikely to be reliable is offered. The technique can be easily deployed in the clinical environment because it is applicable with a wide range of classifiers regardless of their structure and it requires neither additional

  15. Decision Analysis: Engineering Science or Clinical Art

    Science.gov (United States)

    1979-11-01

    TECHNICAL REPORT TR 79-2-97 DECISION ANALYSIS: ENGINEERING SCIENCE OR CLINICAL ART ? by Dennis M. Buede Prepared for Defense Advanced Research...APPLICATIONS OF THE ENGINEER- ING SCIENCE AND CLINICAL ART EXTREMES 9 3.1 Applications of the Engineering Science Approach 9 3.1.1 Mexican electrical...DISCUSSION 29 4.1 Engineering Science versus Clinical Art : A Characterization of When Each is Most Attractive 30 4.2 The Implications of the Engineering

  16. Defense against nuclear weapons: a decision analysis

    International Nuclear Information System (INIS)

    Orient, J.M.

    1985-01-01

    Response to the public health threat posed by nuclear weapons is a medical imperative. The United States, in contrast to other nations, has chosen a course that assures maximal casualties in the event of a nuclear attack, on the theory that prevention of the attack is incompatible with preventive measures against its consequences, such as blast injuries and radiation sickness. A decision analysis approach clarifies the risks and benefits of a change to a strategy of preparedness

  17. Fuzziness and fuzzy modelling in Bulgaria's energy policy decision-making dilemma

    International Nuclear Information System (INIS)

    Wang Xingquan

    2006-01-01

    The decision complexity resulting from imprecision in decision variables and parameters, a major difficulty for conventional decision analysis methods, can be relevantly analysed and modelled by fuzzy logic. Bulgaria's nuclear policy decision-making process implicates such complexity of imprecise nature: stakeholders, criteria, measurement, etc. Given the suitable applicability of fuzzy logic in this case, this article tries to offer a concrete fuzzy paradigm including delimitation of decision space, quantification of imprecise variables, and, of course, parameterisation. (author)

  18. Asset Condition, Information Systems and Decision Models

    CERN Document Server

    Willett, Roger; Brown, Kerry; Mathew, Joseph

    2012-01-01

    Asset Condition, Information Systems and Decision Models, is the second volume of the Engineering Asset Management Review Series. The manuscripts provide examples of implementations of asset information systems as well as some practical applications of condition data for diagnostics and prognostics. The increasing trend is towards prognostics rather than diagnostics, hence the need for assessment and decision models that promote the conversion of condition data into prognostic information to improve life-cycle planning for engineered assets. The research papers included here serve to support the on-going development of Condition Monitoring standards. This volume comprises selected papers from the 1st, 2nd, and 3rd World Congresses on Engineering Asset Management, which were convened under the auspices of ISEAM in collaboration with a number of organisations, including CIEAM Australia, Asset Management Council Australia, BINDT UK, and Chinese Academy of Sciences, Beijing University of Chemical Technology, Chin...

  19. Decision support models for natural gas dispatch

    International Nuclear Information System (INIS)

    Chin, L.; Vollmann, T.E.

    1992-01-01

    A decision support model is presented which will give utilities the support tools to manage the purchasing of natural gas supplies in the most cost effective manner without reducing winter safety stocks to below minimum levels. In Business As Usual (BAU) purchasing quantities vary with the daily forecasts. With Material Requirements Planning (MRP) and Linear Programming (LP), two types of factors are used: seasonal weather and decision rule. Under current practices, BAU simulation uses the least expensive gas source first, then adding successively more expensive sources. Material Requirements Planning is a production planning technique which uses a parent item master production schedule to determine time phased requirements for component points. Where the MPS is the aggregate gas demand forecasts for the contract year. This satisfies daily demand with least expensive gas and uses more expensive when necessary with automatic computation of available-to-promise (ATP) gas a dispacher knows daily when extra gas supplies may be ATP. Linear Programming is a mathematical algorithm used to determine optimal allocations of scarce resources to achieve a desired result. The LP model determines optimal daily gas purchase decisions with respect to supply cost minimization. Using these models, it appears possible to raise gross income margins 6 to 10% with minimal additions of customers and no new gas supply

  20. Decision support models for natural gas dispatch

    Energy Technology Data Exchange (ETDEWEB)

    Chin, L. (Bentley College, Waltham, MA (United States)); Vollmann, T.E. (International Inst. for Management Development, Lausanne (Switzerland))

    A decision support model is presented which will give utilities the support tools to manage the purchasing of natural gas supplies in the most cost effective manner without reducing winter safety stocks to below minimum levels. In Business As Usual (BAU) purchasing quantities vary with the daily forecasts. With Material Requirements Planning (MRP) and Linear Programming (LP), two types of factors are used: seasonal weather and decision rule. Under current practices, BAU simulation uses the least expensive gas source first, then adding successively more expensive sources. Material Requirements Planning is a production planning technique which uses a parent item master production schedule to determine time phased requirements for component points. Where the MPS is the aggregate gas demand forecasts for the contract year. This satisfies daily demand with least expensive gas and uses more expensive when necessary with automatic computation of available-to-promise (ATP) gas a dispacher knows daily when extra gas supplies may be ATP. Linear Programming is a mathematical algorithm used to determine optimal allocations of scarce resources to achieve a desired result. The LP model determines optimal daily gas purchase decisions with respect to supply cost minimization. Using these models, it appears possible to raise gross income margins 6 to 10% with minimal additions of customers and no new gas supply.

  1. Decision Analysis Tools for Volcano Observatories

    Science.gov (United States)

    Hincks, T. H.; Aspinall, W.; Woo, G.

    2005-12-01

    Staff at volcano observatories are predominantly engaged in scientific activities related to volcano monitoring and instrumentation, data acquisition and analysis. Accordingly, the academic education and professional training of observatory staff tend to focus on these scientific functions. From time to time, however, staff may be called upon to provide decision support to government officials responsible for civil protection. Recognizing that Earth scientists may have limited technical familiarity with formal decision analysis methods, specialist software tools that assist decision support in a crisis should be welcome. A review is given of two software tools that have been under development recently. The first is for probabilistic risk assessment of human and economic loss from volcanic eruptions, and is of practical use in short and medium-term risk-informed planning of exclusion zones, post-disaster response, etc. A multiple branch event-tree architecture for the software, together with a formalism for ascribing probabilities to branches, have been developed within the context of the European Community EXPLORIS project. The second software tool utilizes the principles of the Bayesian Belief Network (BBN) for evidence-based assessment of volcanic state and probabilistic threat evaluation. This is of practical application in short-term volcano hazard forecasting and real-time crisis management, including the difficult challenge of deciding when an eruption is over. An open-source BBN library is the software foundation for this tool, which is capable of combining synoptically different strands of observational data from diverse monitoring sources. A conceptual vision is presented of the practical deployment of these decision analysis tools in a future volcano observatory environment. Summary retrospective analyses are given of previous volcanic crises to illustrate the hazard and risk insights gained from use of these tools.

  2. Emergent collective decision-making: Control, model and behavior

    Science.gov (United States)

    Shen, Tian

    In this dissertation we study emergent collective decision-making in social groups with time-varying interactions and heterogeneously informed individuals. First we analyze a nonlinear dynamical systems model motivated by animal collective motion with heterogeneously informed subpopulations, to examine the role of uninformed individuals. We find through formal analysis that adding uninformed individuals in a group increases the likelihood of a collective decision. Secondly, we propose a model for human shared decision-making with continuous-time feedback and where individuals have little information about the true preferences of other group members. We study model equilibria using bifurcation analysis to understand how the model predicts decisions based on the critical threshold parameters that represent an individual's tradeoff between social and environmental influences. Thirdly, we analyze continuous-time data of pairs of human subjects performing an experimental shared tracking task using our second proposed model in order to understand transient behavior and the decision-making process. We fit the model to data and show that it reproduces a wide range of human behaviors surprisingly well, suggesting that the model may have captured the mechanisms of observed behaviors. Finally, we study human behavior from a game-theoretic perspective by modeling the aforementioned tracking task as a repeated game with incomplete information. We show that the majority of the players are able to converge to playing Nash equilibrium strategies. We then suggest with simulations that the mean field evolution of strategies in the population resemble replicator dynamics, indicating that the individual strategies may be myopic. Decisions form the basis of control and problems involving deciding collectively between alternatives are ubiquitous in nature and in engineering. Understanding how multi-agent systems make decisions among alternatives also provides insight for designing

  3. Municipal solid waste management system: decision support through systems analysis

    OpenAIRE

    Pires, Ana Lúcia Lourenço

    2010-01-01

    Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia for the degree of Doctor of Philosophy in Environmental Engineering The present study intends to show the development of systems analysis model applied to solid waste management system, applied into AMARSUL, a solid waste management system responsible for the management of municipal solid waste produced in Setúbal peninsula, Portugal. The model developed intended to promote sustainable decision making, ...

  4. Mental models of decision-making in a healthcare executive

    OpenAIRE

    Long, Katrina

    2017-01-01

    Purpose The importance of shared mental models in teamwork has been explored in a diverse array of artificial work groups. This study extends such research to explore the role of mental models in the strategic decision-making of a real-world senior management group. Design/Methodology Data were collected from an intact group of senior healthcare executives (N=13) through semi-structured interviews, meeting observations and internal document analysis. Participants responded to intervi...

  5. Structural Model Error and Decision Relevancy

    Science.gov (United States)

    Goldsby, M.; Lusk, G.

    2017-12-01

    The extent to which climate models can underwrite specific climate policies has long been a contentious issue. Skeptics frequently deny that climate models are trustworthy in an attempt to undermine climate action, whereas policy makers often desire information that exceeds the capabilities of extant models. While not skeptics, a group of mathematicians and philosophers [Frigg et al. (2014)] recently argued that even tiny differences between the structure of a complex dynamical model and its target system can lead to dramatic predictive errors, possibly resulting in disastrous consequences when policy decisions are based upon those predictions. They call this result the Hawkmoth effect (HME), and seemingly use it to rebuke rightwing proposals to forgo mitigation in favor of adaptation. However, a vigorous debate has emerged between Frigg et al. on one side and another philosopher-mathematician pair [Winsberg and Goodwin (2016)] on the other. On one hand, Frigg et al. argue that their result shifts the burden to climate scientists to demonstrate that their models do not fall prey to the HME. On the other hand, Winsberg and Goodwin suggest that arguments like those asserted by Frigg et al. can be, if taken seriously, "dangerous": they fail to consider the variety of purposes for which models can be used, and thus too hastily undermine large swaths of climate science. They put the burden back on Frigg et al. to show their result has any effect on climate science. This paper seeks to attenuate this debate by establishing an irenic middle position; we find that there is more agreement between sides than it first seems. We distinguish a `decision standard' from a `burden of proof', which helps clarify the contributions to the debate from both sides. In making this distinction, we argue that scientists bear the burden of assessing the consequences of HME, but that the standard Frigg et al. adopt for decision relevancy is too strict.

  6. Decision analysis for INEL hazardous waste storage

    Energy Technology Data Exchange (ETDEWEB)

    Page, L.A.; Roach, J.A.

    1994-01-01

    In mid-November 1993, the Idaho National Engineering Laboratory (INEL) Waste Reduction Operations Complex (WROC) Manager requested that the INEL Hazardous Waste Type Manager perform a decision analysis to determine whether or not a new Hazardous Waste Storage Facility (HWSF) was needed to store INEL hazardous waste (HW). In response to this request, a team was formed to perform a decision analysis for recommending the best configuration for storage of INEL HW. Personnel who participated in the decision analysis are listed in Appendix B. The results of the analysis indicate that the existing HWSF is not the best configuration for storage of INEL HW. The analysis detailed in Appendix C concludes that the best HW storage configuration would be to modify and use a portion of the Waste Experimental Reduction Facility (WERF) Waste Storage Building (WWSB), PBF-623 (Alternative 3). This facility was constructed in 1991 to serve as a waste staging facility for WERF incineration. The modifications include an extension of the current Room 105 across the south end of the WWSB and installing heating, ventilation, and bay curbing, which would provide approximately 1,600 ft{sup 2} of isolated HW storage area. Negotiations with the State to discuss aisle space requirements along with modifications to WWSB operating procedures are also necessary. The process to begin utilizing the WWSB for HW storage includes planned closure of the HWSF, modification to the WWSB, and relocation of the HW inventory. The cost to modify the WWSB can be funded by a reallocation of funding currently identified to correct HWSF deficiencies.

  7. Decision analysis for INEL hazardous waste storage

    International Nuclear Information System (INIS)

    Page, L.A.; Roach, J.A.

    1994-01-01

    In mid-November 1993, the Idaho National Engineering Laboratory (INEL) Waste Reduction Operations Complex (WROC) Manager requested that the INEL Hazardous Waste Type Manager perform a decision analysis to determine whether or not a new Hazardous Waste Storage Facility (HWSF) was needed to store INEL hazardous waste (HW). In response to this request, a team was formed to perform a decision analysis for recommending the best configuration for storage of INEL HW. Personnel who participated in the decision analysis are listed in Appendix B. The results of the analysis indicate that the existing HWSF is not the best configuration for storage of INEL HW. The analysis detailed in Appendix C concludes that the best HW storage configuration would be to modify and use a portion of the Waste Experimental Reduction Facility (WERF) Waste Storage Building (WWSB), PBF-623 (Alternative 3). This facility was constructed in 1991 to serve as a waste staging facility for WERF incineration. The modifications include an extension of the current Room 105 across the south end of the WWSB and installing heating, ventilation, and bay curbing, which would provide approximately 1,600 ft 2 of isolated HW storage area. Negotiations with the State to discuss aisle space requirements along with modifications to WWSB operating procedures are also necessary. The process to begin utilizing the WWSB for HW storage includes planned closure of the HWSF, modification to the WWSB, and relocation of the HW inventory. The cost to modify the WWSB can be funded by a reallocation of funding currently identified to correct HWSF deficiencies

  8. Learning Markov Decision Processes for Model Checking

    DEFF Research Database (Denmark)

    Mao, Hua; Chen, Yingke; Jaeger, Manfred

    2012-01-01

    . The proposed learning algorithm is adapted from algorithms for learning deterministic probabilistic finite automata, and extended to include both probabilistic and nondeterministic transitions. The algorithm is empirically analyzed and evaluated by learning system models of slot machines. The evaluation......Constructing an accurate system model for formal model verification can be both resource demanding and time-consuming. To alleviate this shortcoming, algorithms have been proposed for automatically learning system models based on observed system behaviors. In this paper we extend the algorithm...... on learning probabilistic automata to reactive systems, where the observed system behavior is in the form of alternating sequences of inputs and outputs. We propose an algorithm for automatically learning a deterministic labeled Markov decision process model from the observed behavior of a reactive system...

  9. Best-estimate analysis and decision making under uncertainty

    International Nuclear Information System (INIS)

    Orechwa, Y.

    2004-01-01

    In many engineering analyses of system safety the traditional reliance on conservative evaluation model calculations is being replaced with so called best-estimate analysis. These best-estimate analyses differentiate themselves from the traditional conservative analyses through two ingredients, namely realistic models and an account of the residual uncertainty associated with the model calculations. Best-estimate analysis, in the context of this paper, refers to the numerical evaluation of system properties of interest in situations where direct confirmatory measurements are not feasible. A decision with regard to the safety of the system is then made based on the computed numerical values of the system properties of interest. These situations generally arise in the design of systems that require computed and generally nontrivial extrapolations from the available data. In the case of nuclear reactors, examples are criticality of spent fuel pools, neutronic parameters of new advanced designs where insufficient material is available for mockup critical experiments and, the large break loss of coolant accident (LOCA). In this paper the case of LOCA, is taken to discuss the best-estimate analysis and decision making. Central to decision making is information. Thus, of interest is the source, quantity and quality of the information obtained in a best-estimate analysis, and used to define the acceptance criteria and to formulate a decision rule. This in effect expands the problem from the calculation of a conservative margin to a predefined acceptance criterion, to the formulation of a consistent decision rule and the computation of a test statistic for application of the decision rule. The latter view is a necessary condition for developing risk informed decision rules, and, thus, the relation between design basis analysis criteria and probabilistic risk assessment criteria is key. The discussion is in the context of making a decision under uncertainty for a reactor

  10. Modelling and Decision Support of Clinical Pathways

    Science.gov (United States)

    Gabriel, Roland; Lux, Thomas

    The German health care market is under a rapid rate of change, forcing especially hospitals to provide high-quality services at low costs. Appropriate measures for more effective and efficient service provision are process orientation and decision support by information technology of clinical pathway of a patient. The essential requirements are adequate modelling of clinical pathways as well as usage of adequate systems, which are capable of assisting the complete path of a patient within a hospital, and preferably also outside of it, in a digital way. To fulfil these specifications the authors present a suitable concept, which meets the challenges of well-structured clinical pathways as well as rather poorly structured diagnostic and therapeutic decisions, by interplay of process-oriented and knowledge-based hospital information systems.

  11. Applications of decision analysis and related techniques to industrial engineering problems at KSC

    Science.gov (United States)

    Evans, Gerald W.

    1995-01-01

    This report provides: (1) a discussion of the origination of decision analysis problems (well-structured problems) from ill-structured problems; (2) a review of the various methodologies and software packages for decision analysis and related problem areas; (3) a discussion of how the characteristics of a decision analysis problem affect the choice of modeling methodologies, thus providing a guide as to when to choose a particular methodology; and (4) examples of applications of decision analysis to particular problems encountered by the IE Group at KSC. With respect to the specific applications at KSC, particular emphasis is placed on the use of the Demos software package (Lumina Decision Systems, 1993).

  12. Application of TOPSIS and VIKOR improved versions in a multi criteria decision analysis to develop an optimized municipal solid waste management model.

    Science.gov (United States)

    Aghajani Mir, M; Taherei Ghazvinei, P; Sulaiman, N M N; Basri, N E A; Saheri, S; Mahmood, N Z; Jahan, A; Begum, R A; Aghamohammadi, N

    2016-01-15

    Selecting a suitable Multi Criteria Decision Making (MCDM) method is a crucial stage to establish a Solid Waste Management (SWM) system. Main objective of the current study is to demonstrate and evaluate a proposed method using Multiple Criteria Decision Making methods (MCDM). An improved version of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) applied to obtain the best municipal solid waste management method by comparing and ranking the scenarios. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Besides, Viekriterijumsko Kompromisno Rangiranje (VIKOR) compromise solution method applied for sensitivity analyses. The proposed method can assist urban decision makers in prioritizing and selecting an optimized Municipal Solid Waste (MSW) treatment system. Besides, a logical and systematic scientific method was proposed to guide an appropriate decision-making. A modified TOPSIS methodology as a superior to existing methods for first time was applied for MSW problems. Applying this method in order to rank treatment methods is introduced as one contribution of the study. Next, 11 scenarios of MSW treatment methods are defined and compared environmentally and economically based on the waste management conditions. Results show that integrating a sanitary landfill (18.1%), RDF (3.1%), composting (2%), anaerobic digestion (40.4%), and recycling (36.4%) was an optimized model of integrated waste management. An applied decision-making structure provides the opportunity for optimum decision-making. Therefore, the mix of recycling and anaerobic digestion and a sanitary landfill with Electricity Production (EP) are the preferred options for MSW management. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. Accommodating complexity and human behaviors in decision analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A.; Siirola, John Daniel; Schoenwald, David Alan; Strip, David R.; Hirsch, Gary B.; Bastian, Mark S.; Braithwaite, Karl R.; Homer, Jack [Homer Consulting

    2007-11-01

    This is the final report for a LDRD effort to address human behavior in decision support systems. One sister LDRD effort reports the extension of this work to include actual human choices and additional simulation analyses. Another provides the background for this effort and the programmatic directions for future work. This specific effort considered the feasibility of five aspects of model development required for analysis viability. To avoid the use of classified information, healthcare decisions and the system embedding them became the illustrative example for assessment.

  14. Multi-criteria decision analysis: Limitations, pitfalls, and practical difficulties

    Energy Technology Data Exchange (ETDEWEB)

    Kujawski, Edouard

    2003-02-01

    The 2002 Winter Olympics women's figure skating competition is used as a case study to illustrate some of the limitations, pitfalls, and practical difficulties of Multi-Criteria Decision Analysis (MCDA). The paper compares several widely used models for synthesizing the multiple attributes into a single aggregate value. The various MCDA models can provide conflicting rankings of the alternatives for a common set of information even under states of certainty. Analysts involved in MCDA need to deal with the following challenging tasks: (1) selecting an appropriate analysis method, and (2) properly interpreting the results. An additional trap is the availability of software tools that implement specific MCDA models that can beguile the user with quantitative scores. These conclusions are independent of the decision domain and they should help foster better MCDA practices in many fields including systems engineering trade studies.

  15. Analysis of the decision-making process of nurse managers: a collective reflection.

    Science.gov (United States)

    Eduardo, Elizabete Araujo; Peres, Aida Maris; de Almeida, Maria de Lourdes; Roglio, Karina de Dea; Bernardino, Elizabeth

    2015-01-01

    to analyze the decision-making model adopted by nurses from the perspective of some decision-making process theories. qualitative approach, based on action research. Semi-structured questionnaires and seminars were conducted from April to June 2012 in order to understand the nature of decisions and the decision-making process of nine nurses in position of managers at a public hospital in Southern Brazil. Data were subjected to content analysis. data were classified in two categories: the current situation of decision-making, which showed a lack of systematization; the construction and collective decision-making, which emphasizes the need to develop a decision-making model. the decision-making model used by nurses is limited because it does not consider two important factors: the limits of human rationality, and the external and internal organizational environments that influence and determine right decisions.

  16. [HEALTH ECONOMIC ANALYSIS AND FAIR DECISION MAKING].

    Science.gov (United States)

    Jeantet, Marine; Lopez, Alain

    2015-09-01

    Health technology assessment consists in evaluating the incremental cost-benefit ratio of a medicine, a medical device, a vaccine, a health strategy, in comparison to alternative health technologies. This form of socio-eoonomic evaluation aims at optimizing resource allocation within the health system. By setting the terms of valid alternatives, it is useful to highlight public choices, but it cannot in itself make the decision as regards the public funding of patient's access to the considered technology. The decision to include such technology in the basket of health goods and sercices covered, the levels and conditions of the coverage, also result from budget constraints, from economic situation and from a political vision about health policy, social protection and public expenditure. Accordingly, health economic analysis must be implemented on specific and targeted topics. The decision making process, with its health, economic and ethical stakes, calls for a public procedure and debate, based on shared information and argument. Otherwise, health system regulation, confronted with radical and costly innovations in the coming years, will become harder to handle. This requires the development of health economic research teams able to contribute to this assessment exercise.

  17. A framework for sensitivity analysis of decision trees.

    Science.gov (United States)

    Kamiński, Bogumił; Jakubczyk, Michał; Szufel, Przemysław

    2018-01-01

    In the paper, we consider sequential decision problems with uncertainty, represented as decision trees. Sensitivity analysis is always a crucial element of decision making and in decision trees it often focuses on probabilities. In the stochastic model considered, the user often has only limited information about the true values of probabilities. We develop a framework for performing sensitivity analysis of optimal strategies accounting for this distributional uncertainty. We design this robust optimization approach in an intuitive and not overly technical way, to make it simple to apply in daily managerial practice. The proposed framework allows for (1) analysis of the stability of the expected-value-maximizing strategy and (2) identification of strategies which are robust with respect to pessimistic/optimistic/mode-favoring perturbations of probabilities. We verify the properties of our approach in two cases: (a) probabilities in a tree are the primitives of the model and can be modified independently; (b) probabilities in a tree reflect some underlying, structural probabilities, and are interrelated. We provide a free software tool implementing the methods described.

  18. Human-centric decision-making models for social sciences

    CERN Document Server

    Pedrycz, Witold

    2014-01-01

    The volume delivers a wealth of effective methods to deal with various types of uncertainty inherently existing in human-centric decision problems. It elaborates on  comprehensive decision frameworks to handle different decision scenarios, which help use effectively the explicit and tacit knowledge and intuition, model perceptions and preferences in a more human-oriented style. The book presents original approaches and delivers new results on fundamentals and applications related to human-centered decision making approaches to business, economics and social systems. Individual chapters cover multi-criteria (multiattribute) decision making, decision making with prospect theory, decision making with incomplete probabilistic information, granular models of decision making and decision making realized with the use of non-additive measures. New emerging decision theories being presented as along with a wide spectrum of ongoing research make the book valuable to all interested in the field of advanced decision-mak...

  19. Market orientation in the mental models of decision-makers

    DEFF Research Database (Denmark)

    Grunert, Klaus G.; Trondsen, Torbjørn; Campos, Emilio Gonzalo

    2010-01-01

    Purpose: This study determines whether predictions about different degrees of market orientation in two cross-border value chains also appear in the mental models of decision makers at two levels of these value chains. Design: The laddering method elicits mental models of actors in two value chains......: Norwegian salmon exported to Japan and Danish pork exported to Japan. The analysis of the mental models centers on potential overlap and linkages between actors in the value chain, including elements in the mental models that may relate to the actors' market orientation. Findings: In both value chains......, decision makers exhibit overlap in their views of what drives their business. The pork chain appears dominated by a focus on efficiency, technology, and quality control, though it also acknowledges communication as important. The salmon chain places more emphasis on new product development and good...

  20. Decision-making in irrigation networks: Selecting appropriate canal structures using multi-attribute decision analysis.

    Science.gov (United States)

    Hosseinzade, Zeinab; Pagsuyoin, Sheree A; Ponnambalam, Kumaraswamy; Monem, Mohammad J

    2017-12-01

    The stiff competition for water between agriculture and non-agricultural production sectors makes it necessary to have effective management of irrigation networks in farms. However, the process of selecting flow control structures in irrigation networks is highly complex and involves different levels of decision makers. In this paper, we apply multi-attribute decision making (MADM) methodology to develop a decision analysis (DA) framework for evaluating, ranking and selecting check and intake structures for irrigation canals. The DA framework consists of identifying relevant attributes for canal structures, developing a robust scoring system for alternatives, identifying a procedure for data quality control, and identifying a MADM model for the decision analysis. An application is illustrated through an analysis for automation purposes of the Qazvin irrigation network, one of the oldest and most complex irrigation networks in Iran. A survey questionnaire designed based on the decision framework was distributed to experts, managers, and operators of the Qazvin network and to experts from the Ministry of Power in Iran. Five check structures and four intake structures were evaluated. A decision matrix was generated from the average scores collected from the survey, and was subsequently solved using TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method. To identify the most critical structure attributes for the selection process, optimal attribute weights were calculated using Entropy method. For check structures, results show that the duckbill weir is the preferred structure while the pivot weir is the least preferred. Use of the duckbill weir can potentially address the problem with existing Amil gates where manual intervention is required to regulate water levels during periods of flow extremes. For intake structures, the Neyrpic® gate and constant head orifice are the most and least preferred alternatives, respectively. Some advantages

  1. Logit Estimation of a Gravity Model of the College Enrollment Decision.

    Science.gov (United States)

    Leppel, Karen

    1993-01-01

    A study investigated the factors influencing students' decisions about attending a college to which they had been admitted. Logit analysis confirmed gravity model predictions that geographic distance and student ability would most influence the enrollment decision and found other variables, although affecting earlier stages of decision making, did…

  2. Empirically evaluating decision-analytic models.

    Science.gov (United States)

    Goldhaber-Fiebert, Jeremy D; Stout, Natasha K; Goldie, Sue J

    2010-08-01

    Model-based cost-effectiveness analyses support decision-making. To augment model credibility, evaluation via comparison to independent, empirical studies is recommended. We developed a structured reporting format for model evaluation and conducted a structured literature review to characterize current model evaluation recommendations and practices. As an illustration, we applied the reporting format to evaluate a microsimulation of human papillomavirus and cervical cancer. The model's outputs and uncertainty ranges were compared with multiple outcomes from a study of long-term progression from high-grade precancer (cervical intraepithelial neoplasia [CIN]) to cancer. Outcomes included 5 to 30-year cumulative cancer risk among women with and without appropriate CIN treatment. Consistency was measured by model ranges overlapping study confidence intervals. The structured reporting format included: matching baseline characteristics and follow-up, reporting model and study uncertainty, and stating metrics of consistency for model and study results. Structured searches yielded 2963 articles with 67 meeting inclusion criteria and found variation in how current model evaluations are reported. Evaluation of the cervical cancer microsimulation, reported using the proposed format, showed a modeled cumulative risk of invasive cancer for inadequately treated women of 39.6% (30.9-49.7) at 30 years, compared with the study: 37.5% (28.4-48.3). For appropriately treated women, modeled risks were 1.0% (0.7-1.3) at 30 years, study: 1.5% (0.4-3.3). To support external and projective validity, cost-effectiveness models should be iteratively evaluated as new studies become available, with reporting standardized to facilitate assessment. Such evaluations are particularly relevant for models used to conduct comparative effectiveness analyses.

  3. Integrating a Decision Management Tool with UML Modeling Tools

    DEFF Research Database (Denmark)

    Könemann, Patrick

    by proposing potential subsequent design issues. In model-based software development, many decisions directly affect the structural and behavioral models used to describe and develop a software system and its architecture. However, these decisions are typically not connected to the models created during...... integration of formerly disconnected tools improves tool usability as well as decision maker productivity....

  4. The two-model problem in rational decision making

    NARCIS (Netherlands)

    Boumans, Marcel

    2011-01-01

    A model of a decision problem frames that problem in three dimensions: sample space, target probability and information structure. Each specific model imposes a specific rational decision. As a result, different models may impose different, even contradictory, rational decisions, creating choice

  5. Managing health care decisions and improvement through simulation modeling.

    Science.gov (United States)

    Forsberg, Helena Hvitfeldt; Aronsson, Håkan; Keller, Christina; Lindblad, Staffan

    2011-01-01

    Simulation modeling is a way to test changes in a computerized environment to give ideas for improvements before implementation. This article reviews research literature on simulation modeling as support for health care decision making. The aim is to investigate the experience and potential value of such decision support and quality of articles retrieved. A literature search was conducted, and the selection criteria yielded 59 articles derived from diverse applications and methods. Most met the stated research-quality criteria. This review identified how simulation can facilitate decision making and that it may induce learning. Furthermore, simulation offers immediate feedback about proposed changes, allows analysis of scenarios, and promotes communication on building a shared system view and understanding of how a complex system works. However, only 14 of the 59 articles reported on implementation experiences, including how decision making was supported. On the basis of these articles, we proposed steps essential for the success of simulation projects, not just in the computer, but also in clinical reality. We also presented a novel concept combining simulation modeling with the established plan-do-study-act cycle for improvement. Future scientific inquiries concerning implementation, impact, and the value for health care management are needed to realize the full potential of simulation modeling.

  6. Ethical analysis to improve decision-making on health technologies

    DEFF Research Database (Denmark)

    Saarni, Samuli I; Hofmann, Bjørn; Lampe, Kristian

    2008-01-01

    Health technology assessment (HTA) is the multidisciplinary study of the implications of the development, diffusion and use of health technologies. It supports health-policy decisions by providing a joint knowledge base for decision-makers. To increase its policy relevance, HTA tries to extend...... beyond effectiveness and costs to also considering the social, organizational and ethical implications of technologies. However, a commonly accepted method for analysing the ethical aspects of health technologies is lacking. This paper describes a model for ethical analysis of health technology...... to only analyse the ethical consequences of a technology, but also the ethical issues of the whole HTA process must be considered. Selection of assessment topics, methods and outcomes is essentially a value-laden decision. Health technologies may challenge moral or cultural values and beliefs...

  7. Decisions under uncertainty using Bayesian analysis

    Directory of Open Access Journals (Sweden)

    Stelian STANCU

    2006-01-01

    Full Text Available The present paper makes a short presentation of the Bayesian decions method, where extrainformation brings a great support to decision making process, but also attract new costs. In this situation, getting new information, generally experimentaly based, contributes to diminushing the uncertainty degree that influences decision making process. As a conclusion, in a large number of decision problems, there is the possibility that the decision makers will renew some decisions already taken because of the facilities offered by obtainig extrainformation.

  8. IMPORTANCE OF DIFFERENT MODELS IN DECISION MAKING, EXPLAINING THE STRATEGIC BEHAVIOR IN ORGANIZATIONS

    Directory of Open Access Journals (Sweden)

    Cristiano de Oliveira Maciel

    2006-11-01

    Full Text Available This study is about the different models of decision process analyzing the organizational strategy. The article presents the strategy according to a cognitive approach. The discussion about that approach has three models of decision process: rational actor model, organizational behavior, and political model. These models, respectively, present some improvement in the decision making results, search for a good decision facing the cognitive restrictions of the administrator, and lots of talks for making a decision. According to the emphasis of each model, the possibilities for analyzing the strategy are presented. The article also shows that it is necessary to take into account the three different ways of analysis. That statement is justified once the analysis as well as the decision making become more complex, mainly those which are more important for the organizations.

  9. A hierarchical Markov decision process modeling feeding and marketing decisions of growing pigs

    DEFF Research Database (Denmark)

    Pourmoayed, Reza; Nielsen, Lars Relund; Kristensen, Anders Ringgaard

    2016-01-01

    Feeding is the most important cost in the production of growing pigs and has a direct impact on the marketing decisions, growth and the final quality of the meat. In this paper, we address the sequential decision problem of when to change the feed-mix within a finisher pig pen and when to pick pigs...... for marketing. We formulate a hierarchical Markov decision process with three levels representing the decision process. The model considers decisions related to feeding and marketing and finds the optimal decision given the current state of the pen. The state of the system is based on information from on...

  10. Robustness of Multiple Objective Decision Analysis Preference Functions

    Science.gov (United States)

    2002-06-01

    Bayesian Decision Theory and Utilitarian Ethics ,” American Economic Review Papers and Proceedings, 68: 223-228 (May 1978). Hartsough, Bruce R. “A...1983). Morrell, Darryl and Eric Driver. “ Bayesian Network Implementation of Levi’s Epistemic Utility Decision Theory ,” International Journal Of...elicitation efficiency for the decision maker. Subject Terms Decision Analysis, Utility Theory , Elicitation Error, Operations Research, Decision

  11. A model-referenced procedure to support adversarial decision processes

    International Nuclear Information System (INIS)

    Bunn, D.W.; Vlahos, K.

    1992-01-01

    In public enquiries concerning major facilities, such as the construction of a new electric power plant, it is observed that a useable decision model should be made commonly available alongside the open provision of data and assumptions. The protagonist, eg the electric utility, generally makes use of a complex, proprietary model for detailed evaluation of options. A simple emulator of this, based upon a regression analysis of numerous scenarios, and validated by further simulations is shown to be feasible and potentially attractive. It would be in the interests of the utility to make such a model-referenced decision support method generally available. The approach is considered in relation to the recent Hinkley Point C public enquiry for a new nuclear power plant in the UK. (Author)

  12. Decision Support Model for Optimal Management of Coastal Gate

    Science.gov (United States)

    Ditthakit, Pakorn; Chittaladakorn, Suwatana

    2010-05-01

    The coastal areas are intensely settled by human beings owing to their fertility of natural resources. However, at present those areas are facing with water scarcity problems: inadequate water and poor water quality as a result of saltwater intrusion and inappropriate land-use management. To solve these problems, several measures have been exploited. The coastal gate construction is a structural measure widely performed in several countries. This manner requires the plan for suitably operating coastal gates. Coastal gate operation is a complicated task and usually concerns with the management of multiple purposes, which are generally conflicted one another. This paper delineates the methodology and used theories for developing decision support modeling for coastal gate operation scheduling. The developed model was based on coupling simulation and optimization model. The weighting optimization technique based on Differential Evolution (DE) was selected herein for solving multiple objective problems. The hydrodynamic and water quality models were repeatedly invoked during searching the optimal gate operations. In addition, two forecasting models:- Auto Regressive model (AR model) and Harmonic Analysis model (HA model) were applied for forecasting water levels and tide levels, respectively. To demonstrate the applicability of the developed model, it was applied to plan the operations for hypothetical system of Pak Phanang coastal gate system, located in Nakhon Si Thammarat province, southern part of Thailand. It was found that the proposed model could satisfyingly assist decision-makers for operating coastal gates under various environmental, ecological and hydraulic conditions.

  13. Environmental sustainable decision making – The need and obstacles for integration of LCA into decision analysis

    DEFF Research Database (Denmark)

    Dong, Yan; Miraglia, Simona; Manzo, Stefano

    2018-01-01

    systems, revealing potential problem shifting between life cycle stages. Through the integration with traditional risk based decision analysis, LCA may thus facilitate a better informed decision process. In this study we explore how environmental impacts are taken into account in different fields......Decision analysis is often used to help decision makers choose among alternatives, based on the expected utility associated to each alternative as function of its consequences and potential impacts. Environmental impacts are not always among the prioritized concerns of traditional decision making...... of interest for decision makers to identify the need, potential and obstacles for integrating LCA into conventional approaches to decision problems. Three application areas are used as examples: transportation planning, flood management, and food production and consumption. The analysis of these cases shows...

  14. Modelling of the costs of decision support for small and medium-sized enterprises

    Directory of Open Access Journals (Sweden)

    Viera Tomišová

    2017-01-01

    Full Text Available The support of decision-making activities in small and medium-sized enterprises (SME has its specific features. When suggesting steps for the implementation of decision-support tools in the enterprise, we identified two main ways of decision-making support based on the data analysis: ERP (Enterprise Resource Planning without BI (Business Intelligence and ERP with BI. In our contribution, we present costs models of both mentioned decision support systems and their practical interpretation.

  15. Making ethical choices: a comprehensive decision-making model for Canadian psychologists.

    Science.gov (United States)

    Hadjistavropoulos, T; Malloy, D C

    2000-05-01

    This paper proposes a theoretical augmentation of the seven-step decision-making model outlined in the Canadian Code of Ethics for Psychologists. We propose that teleological, deontological, and existential ethical perspectives should be taken into account in the decision-making process. We also consider the influence of individual, issue-specific, significant-other, situational, and external factors on ethical decision-making. This theoretical analysis demonstrates the richness and complexity of ethical decision-making.

  16. Análise dos modelos de tomada decisão sob o enfoque cognitivo ANALYSIS OF MODELS OF DECISION MAKING IN THE COGNITIVE APPROACH

    Directory of Open Access Journals (Sweden)

    Eugênio de Oliveira Simonetto

    2010-08-01

    Full Text Available The rationality has been defined from the Greeks as one of the main characteristic that distinguishes man from the other animals. The Greeks ‘influence like Plato and Aristotle and the philosophers empiricist /rationalist,as Descartes and Thomas Hobbes, were remarkable for the formation of models of decision making in organizations proposed by Simon, Allison and Lindblon. This study aims to identify the mainly decision making models and check how the cognitive aspects can affect the behavior of the agents involved in the process. The results show that there is no way to overlook the subjective factors, the different cognitive styles in the decision, there is a system of relations between the elements of nature objective and subjective elements,whichever is the predominant influence of the values of decision makers involved, which is seen as a motivator for the decision.A racionalidade vem sendo definida a partir dos gregos como uma das principais características que distingue o homem dos outros animais. A influência dos gregos, como Platão e Aristóteles, e dos filósofos empiristas/racionalistas, como Descartes e Thomas Hobbes, foram marcantes para a formação dos modelos de tomadas de decisão nas organizações propostas por Simon, Allison e Lindblon. Assim, este trabalho tem o objetivo de identificar os principais modelos de tomada de decisão e verificar como os aspectos cognitivos podem afetar o comportamento dos agentes envolvidos no processo. Os resultados demonstram que não há como negligenciar os fatores subjetivos e os diferentes estilos cognitivos na decisão, pois há um sistema de relações entre os elementos de natureza objetiva e os elementos de natureza subjetiva, prevalecendo o predomínio da influência dos valores dos decisores envolvidos, o que é visto como elemento motivador da decisão.

  17. Acid rain compliance planning using decision analysis

    International Nuclear Information System (INIS)

    Norris, C.; Sweet, T.; Borison, A.

    1991-01-01

    Illinois Power Company (IP) is an investor-owned electric and natural gas utility serving portions of downstate Illinois. In addition to one nuclear unit and several small gas and/or oil-fired units, IP has ten coal-fired units. It is easy to understand the impact the Clean Air Act Amendments of 1990 (CAAA) could have on IP. Prior to passage of the CAAA, IP formed several teams to evaluate the specific compliance options at each of the high sulfur coal units. Following that effort, numerous economic analyses of compliance strategies were conducted. The CAAA have introduced a new dimension to planning under uncertainty. Not only are many of the familiar variables uncertain, but the specific form of regulation, and indeed, the compliance goal itself is hard to define. For IP, this led them to use techniques not widely used within their corporation. This paper summarizes the analytical methods used in these analyses and the preliminary results as of July, 1991. The analysis used three approaches to examine the acid rain compliance decision. These approaches were: (1) the 'most-likely,' or single-path scenario approach; (2) a multi-path strategy analysis using the strategies defined in the single-scenario analysis; and (3) a less constrained multi-path option analysis which selects the least cost compliance option for each unit

  18. Making decision process knowledge explicit using the product data model

    NARCIS (Netherlands)

    Petrusel, R.; Vanderfeesten, I.T.P.; Dolean, Cristina; Mican, D.

    2011-01-01

    In this paper, we present a new knowledge acquisition and formalization method: the decision mining approach. Basically, we aim to produce a model of the workflow of mental actions performed by decision makers during the decision process. We show that through the use of a Product Data Model (PDM) we

  19. Subjective Expected Utility: A Model of Decision-Making.

    Science.gov (United States)

    Fischoff, Baruch; And Others

    1981-01-01

    Outlines a model of decision making known to researchers in the field of behavioral decision theory (BDT) as subjective expected utility (SEU). The descriptive and predictive validity of the SEU model, probability and values assessment using SEU, and decision contexts are examined, and a 54-item reference list is provided. (JL)

  20. Dissolving decision making? : Models and their roles in decision-making processes and policy at large

    NARCIS (Netherlands)

    Zeiss, Ragna; van Egmond, S.

    2014-01-01

    This article studies the roles three science-based models play in Dutch policy and decision making processes. Key is the interaction between model construction and environment. Their political and scientific environments form contexts that shape the roles of models in policy decision making.

  1. Systematic approaches to data analysis from the Critical Decision Method

    Directory of Open Access Journals (Sweden)

    Martin Sedlár

    2015-01-01

    Full Text Available The aim of the present paper is to introduce how to analyse the qualitative data from the Critical Decision Method. At first, characterizing the method provides the meaningful introduction into the issue. This method used in naturalistic decision making research is one of the cognitive task analysis methods, it is based on the retrospective semistructured interview about critical incident from the work and it may be applied in various domains such as emergency services, military, transport, sport or industry. Researchers can make two types of methodological adaptation. Within-method adaptations modify the way of conducting the interviews and cross-method adaptations combine this method with other related methods. There are many decsriptions of conducting the interview, but the descriptions how the data should be analysed are rare. Some researchers use conventional approaches like content analysis, grounded theory or individual procedures with reference to the objectives of research project. Wong (2004 describes two approaches to data analysis proposed for this method of data collection, which are described and reviewed in the details. They enable systematic work with a large amount of data. The structured approach organizes the data according to an a priori analysis framework and it is suitable for clearly defined object of research. Each incident is studied separately. At first, the decision chart showing the main decision points and then the incident summary are made. These decision points are used to identify the relevant statements from the transcript, which are analysed in terms of the Recognition-Primed Decision Model. Finally, the results from all the analysed incidents are integrated. The limitation of the structured approach is it may not reveal some interesting concepts. The emergent themes approach helps to identify these concepts while maintaining a systematic framework for analysis and it is used for exploratory research design. It

  2. Robustness of Multiple Objective Decision Analysis Preference Functions

    National Research Council Canada - National Science Library

    Klimack, William

    2002-01-01

    .... The impact of these differences was examined to improve implementation efficiency. The robustness of the decision model was examined with respect to the preference functions to reduce the time burden imposed on the decision maker...

  3. Modelling group decision simulation through argumentation

    OpenAIRE

    Marreiros, Goreti; Novais, Paulo; Machado, José; Ramos, Carlos; Neves, José

    2007-01-01

    Group decision making plays an important role in today’s organisations. The impact of decision making is so high and complex, that rarely the decision making process is made individually. In Group Decision Argumentation, there is a set of participants, with different profiles and expertise levels, that exchange ideas or engage in a process of argumentation and counter-argumentation, negotiate, cooperate, collaborate or even discuss techniques and/or methodologies for problem solving. In this ...

  4. The Limitations of Applying Rational Decision-Making Models

    African Journals Online (AJOL)

    decision-making models as applied to child spacing and more. specificaDy to the use .... also assumes that the individual operates as a rational decision- making organism in ..... work involves: Motivation; Counselling; Distribution ofIEC mate-.

  5. Modeling decisions information fusion and aggregation operators

    CERN Document Server

    Torra, Vicenc

    2007-01-01

    Information fusion techniques and aggregation operators produce the most comprehensive, specific datum about an entity using data supplied from different sources, thus enabling us to reduce noise, increase accuracy, summarize and extract information, and make decisions. These techniques are applied in fields such as economics, biology and education, while in computer science they are particularly used in fields such as knowledge-based systems, robotics, and data mining. This book covers the underlying science and application issues related to aggregation operators, focusing on tools used in practical applications that involve numerical information. Starting with detailed introductions to information fusion and integration, measurement and probability theory, fuzzy sets, and functional equations, the authors then cover the following topics in detail: synthesis of judgements, fuzzy measures, weighted means and fuzzy integrals, indices and evaluation methods, model selection, and parameter extraction. The method...

  6. Models of sequential decision making in consumer lending

    OpenAIRE

    Kanshukan Rajaratnam; Peter A. Beling; George A. Overstreet

    2016-01-01

    Abstract In this paper, we introduce models of sequential decision making in consumer lending. From the definition of adverse selection in static lending models, we show that homogenous borrowers take-up offers at different instances of time when faced with a sequence of loan offers. We postulate that bounded rationality and diverse decision heuristics used by consumers drive the decisions they make about credit offers. Under that postulate, we show how observation of early decisions in a seq...

  7. Feasibility Risk Assessment of Transport Infrastructure Projects: The CBA-DK Decision Support Model

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Banister, David

    2010-01-01

    informed decision support towards decision-makers and stakeholders in terms of accumulated descending graphs. The decision support method developed in this paper aims to provide assistance in the analysis and ultimately the choice of action, while accounting for the uncertainties surrounding any transport......This paper presents the final version of the CBA-DK decision support model for assessment of transport projects. The model makes use of conventional cost-benefit analysis resulting in aggregated single point estimates and quantitative risk analysis using Monte Carlo simulation resulting in interval...... result, and the determination of suitable probability distributions. Use is made of the reference class forecasting information, such as that developed in Optimism Bias for adjustments to investment decisions that relate to all modes of transport. The CBA-DK decision support model results in more...

  8. A communication model of shared decision making: accounting for cancer treatment decisions.

    Science.gov (United States)

    Siminoff, Laura A; Step, Mary M

    2005-07-01

    The authors present a communication model of shared decision making (CMSDM) that explicitly identifies the communication process as the vehicle for decision making in cancer treatment. In this view, decision making is necessarily a sociocommunicative process whereby people enter into a relationship, exchange information, establish preferences, and choose a course of action. The model derives from contemporary notions of behavioral decision making and ethical conceptions of the doctor-patient relationship. This article briefly reviews the theoretical approaches to decision making, notes deficiencies, and embeds a more socially based process into the dynamics of the physician-patient relationship, focusing on cancer treatment decisions. In the CMSDM, decisions depend on (a) antecedent factors that have potential to influence communication, (b) jointly constructed communication climate, and (c) treatment preferences established by the physician and the patient.

  9. Stochastic Watershed Models for Risk Based Decision Making

    Science.gov (United States)

    Vogel, R. M.

    2017-12-01

    Over half a century ago, the Harvard Water Program introduced the field of operational or synthetic hydrology providing stochastic streamflow models (SSMs), which could generate ensembles of synthetic streamflow traces useful for hydrologic risk management. The application of SSMs, based on streamflow observations alone, revolutionized water resources planning activities, yet has fallen out of favor due, in part, to their inability to account for the now nearly ubiquitous anthropogenic influences on streamflow. This commentary advances the modern equivalent of SSMs, termed `stochastic watershed models' (SWMs) useful as input to nearly all modern risk based water resource decision making approaches. SWMs are deterministic watershed models implemented using stochastic meteorological series, model parameters and model errors, to generate ensembles of streamflow traces that represent the variability in possible future streamflows. SWMs combine deterministic watershed models, which are ideally suited to accounting for anthropogenic influences, with recent developments in uncertainty analysis and principles of stochastic simulation

  10. Risk Decision Making Model for Reservoir Floodwater resources Utilization

    Science.gov (United States)

    Huang, X.

    2017-12-01

    Floodwater resources utilization(FRU) can alleviate the shortage of water resources, but there are risks. In order to safely and efficiently utilize the floodwater resources, it is necessary to study the risk of reservoir FRU. In this paper, the risk rate of exceeding the design flood water level and the risk rate of exceeding safety discharge are estimated. Based on the principle of the minimum risk and the maximum benefit of FRU, a multi-objective risk decision making model for FRU is constructed. Probability theory and mathematical statistics method is selected to calculate the risk rate; C-D production function method and emergy analysis method is selected to calculate the risk benefit; the risk loss is related to flood inundation area and unit area loss; the multi-objective decision making problem of the model is solved by the constraint method. Taking the Shilianghe reservoir in Jiangsu Province as an example, the optimal equilibrium solution of FRU of the Shilianghe reservoir is found by using the risk decision making model, and the validity and applicability of the model are verified.

  11. Preference, resistance to change, and the cumulative decision model.

    Science.gov (United States)

    Grace, Randolph C

    2018-01-01

    According to behavioral momentum theory (Nevin & Grace, 2000a), preference in concurrent chains and resistance to change in multiple schedules are independent measures of a common construct representing reinforcement history. Here I review the original studies on preference and resistance to change in which reinforcement variables were manipulated parametrically, conducted by Nevin, Grace and colleagues between 1997 and 2002, as well as more recent research. The cumulative decision model proposed by Grace and colleagues for concurrent chains is shown to provide a good account of both preference and resistance to change, and is able to predict the increased sensitivity to reinforcer rate and magnitude observed with constant-duration components. Residuals from fits of the cumulative decision model to preference and resistance to change data were positively correlated, supporting the prediction of behavioral momentum theory. Although some questions remain, the learning process assumed by the cumulative decision model, in which outcomes are compared against a criterion that represents the average outcome value in the current context, may provide a plausible model for the acquisition of differential resistance to change. © 2018 Society for the Experimental Analysis of Behavior.

  12. Regulator Loss Functions and Hierarchical Modeling for Safety Decision Making.

    Science.gov (United States)

    Hatfield, Laura A; Baugh, Christine M; Azzone, Vanessa; Normand, Sharon-Lise T

    2017-07-01

    Regulators must act to protect the public when evidence indicates safety problems with medical devices. This requires complex tradeoffs among risks and benefits, which conventional safety surveillance methods do not incorporate. To combine explicit regulator loss functions with statistical evidence on medical device safety signals to improve decision making. In the Hospital Cost and Utilization Project National Inpatient Sample, we select pediatric inpatient admissions and identify adverse medical device events (AMDEs). We fit hierarchical Bayesian models to the annual hospital-level AMDE rates, accounting for patient and hospital characteristics. These models produce expected AMDE rates (a safety target), against which we compare the observed rates in a test year to compute a safety signal. We specify a set of loss functions that quantify the costs and benefits of each action as a function of the safety signal. We integrate the loss functions over the posterior distribution of the safety signal to obtain the posterior (Bayes) risk; the preferred action has the smallest Bayes risk. Using simulation and an analysis of AMDE data, we compare our minimum-risk decisions to a conventional Z score approach for classifying safety signals. The 2 rules produced different actions for nearly half of hospitals (45%). In the simulation, decisions that minimize Bayes risk outperform Z score-based decisions, even when the loss functions or hierarchical models are misspecified. Our method is sensitive to the choice of loss functions; eliciting quantitative inputs to the loss functions from regulators is challenging. A decision-theoretic approach to acting on safety signals is potentially promising but requires careful specification of loss functions in consultation with subject matter experts.

  13. Modeling and Testing Landslide Hazard Using Decision Tree

    Directory of Open Access Journals (Sweden)

    Mutasem Sh. Alkhasawneh

    2014-01-01

    Full Text Available This paper proposes a decision tree model for specifying the importance of 21 factors causing the landslides in a wide area of Penang Island, Malaysia. These factors are vegetation cover, distance from the fault line, slope angle, cross curvature, slope aspect, distance from road, geology, diagonal length, longitude curvature, rugosity, plan curvature, elevation, rain perception, soil texture, surface area, distance from drainage, roughness, land cover, general curvature, tangent curvature, and profile curvature. Decision tree models are used for prediction, classification, and factors importance and are usually represented by an easy to interpret tree like structure. Four models were created using Chi-square Automatic Interaction Detector (CHAID, Exhaustive CHAID, Classification and Regression Tree (CRT, and Quick-Unbiased-Efficient Statistical Tree (QUEST. Twenty-one factors were extracted using digital elevation models (DEMs and then used as input variables for the models. A data set of 137570 samples was selected for each variable in the analysis, where 68786 samples represent landslides and 68786 samples represent no landslides. 10-fold cross-validation was employed for testing the models. The highest accuracy was achieved using Exhaustive CHAID (82.0% compared to CHAID (81.9%, CRT (75.6%, and QUEST (74.0% model. Across the four models, five factors were identified as most important factors which are slope angle, distance from drainage, surface area, slope aspect, and cross curvature.

  14. Using Consumer Behavior and Decision Models to Aid Students in Choosing a Major.

    Science.gov (United States)

    Kaynama, Shohreh A.; Smith, Louise W.

    1996-01-01

    A study found that using consumer behavior and decision models to guide students to a major can be useful and enjoyable for students. Students consider many of the basic parameters through multi-attribute and decision-analysis models, so time with professors, who were found to be the most influential group, can be used for more individual and…

  15. DECISION ANALYSIS OF INCINERATION COSTS IN SUPERFUND SITE REMEDIATION

    Science.gov (United States)

    This study examines the decision-making process of the remedial design (RD) phase of on-site incineration projects conducted at Superfund sites. Decisions made during RD affect the cost and schedule of remedial action (RA). Decision analysis techniques are used to determine the...

  16. Leadership of risk decision making in a complex, technology organization: The deliberative decision making model

    Science.gov (United States)

    Flaming, Susan C.

    2007-12-01

    The continuing saga of satellite technology development is as much a story of successful risk management as of innovative engineering. How do program leaders on complex, technology projects manage high stakes risks that threaten business success and satellite performance? This grounded theory study of risk decision making portrays decision leadership practices at one communication satellite company. Integrated product team (IPT) leaders of multi-million dollar programs were interviewed and observed to develop an extensive description of the leadership skills required to navigate organizational influences and drive challenging risk decisions to closure. Based on the study's findings the researcher proposes a new decision making model, Deliberative Decision Making, to describe the program leaders' cognitive and organizational leadership practices. This Deliberative Model extends the insights of prominent decision making models including the rational (or classical) and the naturalistic and qualifies claims made by bounded rationality theory. The Deliberative Model describes how leaders proactively engage resources to play a variety of decision leadership roles. The Model incorporates six distinct types of leadership decision activities, undertaken in varying sequence based on the challenges posed by specific risks. Novel features of the Deliberative Decision Model include: an inventory of leadership methods for managing task challenges, potential stakeholder bias and debates; four types of leadership meta-decisions that guide decision processes, and aligned organizational culture. Both supporting and constraining organizational influences were observed as leaders managed major risks, requiring active leadership on the most difficult decisions. Although the company's engineering culture emphasized the importance of data-based decisions, the uncertainties intrinsic to satellite risks required expert engineering judgment to be exercised throughout. An investigation into

  17. Modelling contractor’s bidding decision

    Directory of Open Access Journals (Sweden)

    Biruk Sławomir

    2017-03-01

    Full Text Available The authors aim to provide a set of tools to facilitate the main stages of the competitive bidding process for construction contractors. These involve 1 deciding whether to bid, 2 calculating the total price, and 3 breaking down the total price into the items of the bill of quantities or the schedule of payments to optimise contractor cash flows. To define factors that affect the decision to bid, the authors rely upon literature on the subject and put forward that multi-criteria methods are applied to calculate a single measure of contract attractiveness (utility value. An attractive contract implies that the contractor is likely to offer a lower price to increase chances of winning the competition. The total bid price is thus to be interpolated between the lowest acceptable and the highest justifiable price based on the contract attractiveness. With the total bid price established, the next step is to split it between the items of the schedule of payments. A linear programming model is proposed for this purpose. The application of the models is illustrated with a numerical example.

  18. Theoretical Background for the Decision-Making Process Modelling under Controlled Intervention Conditions

    OpenAIRE

    Bakanauskienė Irena; Baronienė Laura

    2017-01-01

    This article is intended to theoretically justify the decision-making process model for the cases, when active participation of investing entities in controlling the activities of an organisation and their results is noticeable. Based on scientific literature analysis, a concept of controlled conditions is formulated, and using a rational approach to the decision-making process, a model of the 11-steps decision-making process under controlled intervention is presented. Also, there have been u...

  19. FUZZY DECISION MAKING MODEL FOR BYZANTINE AGREEMENT

    Directory of Open Access Journals (Sweden)

    S. MURUGAN

    2014-04-01

    Full Text Available Byzantine fault tolerance is of high importance in the distributed computing environment where malicious attacks and software errors are common. A Byzantine process sends arbitrary messages to every other process. An effective fuzzy decision making approach is proposed to eliminate the Byzantine behaviour of the services in the distributed environment. It is proposed to derive a fuzzy decision set in which the alternatives are ranked with grade of membership and based on that an appropriate decision can be arrived on the messages sent by the different services. A balanced decision is to be taken from the messages received across the services. To accomplish this, Hurwicz criterion is used to balance the optimistic and pessimistic views of the decision makers on different services. Grades of membership for the services are assessed using the non-functional Quality of Service parameters and have been estimated using fuzzy entropy measure which logically ranks the participant services. This approach for decision making is tested by varying the number of processes, varying the number of faulty services, varying the message values sent to different services and considering the variation in the views of the decision makers about the services. The experimental result shows that the decision reached is an enhanced one and in case of conflict, the proposed approach provides a concrete result, whereas decision taken using the Lamport’s algorithm is an arbitrary one.

  20. Decision analysis in the clinical neurosciences

    NARCIS (Netherlands)

    D.W.J. Dippel (Diederik)

    1994-01-01

    textabstractDiagnostic and therapeutic choice in neurology can fortunately be made without formal decision support in the majority of cases. in many patients a diagnosis and treatment choice are relatively easy to establish. This study however, concerns the application of a decision support

  1. LEADERSHIP MODELS AND EFFICIENCY IN DECISION CRISIS SITUATIONS, DURING DISASTERS

    Directory of Open Access Journals (Sweden)

    JAIME RIQUELME CASTAÑEDA

    2017-09-01

    Full Text Available This article explains how an effective leadership is made on a team during an emergency, during a decision crisis in the context of a disaster. From the approach of the process, we analyze some variables such as flexibility, value congruence, rationality, politicization, and quality of design. To achieve that, we made a fi eld work with the information obtained from the three Emergency headquarters deployed by the Chilean Armed Forces, due to the effects of the 8.8 earthquake on February 27th 2010. The data is analyzed through econometric technics. The results suggested that the original ideas and the rigorous analysis are the keys to secure the quality of the decision. It also, made possible to unveil the fact, that to have efficiency in operations in a disaster, it requires a big presence of a vision, mission, and inspiration about a solid and pre-existing base of goals and motivations. Finally, we can fi nd the support to the relationship between kinds of leadership and efficiency on crisis decision-making process of the disaster and opens a space to build a decision making theoretic model.

  2. Multi-criteria decision analysis using hydrological indicators for decision support - a conceptual framework.

    Science.gov (United States)

    Butchart-Kuhlmann, Daniel; Kralisch, Sven; Meinhardt, Markus; Fleischer, Melanie

    2017-04-01

    Assessing the quantity and quality of water available in water stressed environments under various potential climate and land-use changes is necessary for good water and environmental resources management and governance. Within the region covered by the Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) project, such areas are common. One goal of the SASSCAL project is to develop and provide an integrated decision support system (DSS) with which decision makers (DMs) within a given catchment can obtain objective information regarding potential changes in water flow quantity and timing. The SASSCAL DSS builds upon existing data storage and distribution capability, through the SASSCAL Information System (IS), as well as the J2000 hydrological model. Using output from validated J2000 models, the SASSCAL DSS incorporates the calculation of a range of hydrological indicators based upon Indicators of Hydrological Alteration/Environmental Flow Components (IHA/EFC) calculated for a historic time series (pre-impact) and a set of model simulations based upon a selection of possible climate and land-use change scenarios (post-impact). These indicators, obtained using the IHA software package, are then used as input for a multi-criteria decision analysis (MCDA) undertaken using the open source diviz software package. The results of these analyses will provide DMs with an indication as to how various hydrological indicators within a catchment may be altered under different future scenarios, as well providing a ranking of how each scenario is preferred according to different DM preferences. Scenarios are represented through a combination of model input data and parameter settings in J2000, and preferences are represented through criteria weighting in the MCDA. Here, the methodology is presented and applied to the J2000 Luanginga model results using a set of hypothetical decision maker preference values as input for an MCDA based on

  3. A generic methodology for developing fuzzy decision models

    NARCIS (Netherlands)

    Bosma, R.H.; Berg, van den J.; Kaymak, Uzay; Udo, H.M.J.; Verreth, J.A.J.

    2012-01-01

    An important paradigm in decision-making models is utility-maximization where most models do not include actors’ motives. Fuzzy set theory on the other hand offers a method to simulate human decision-making. However, the literature describing expert-driven fuzzy logic models, rarely gives precise

  4. Theoretical Background for the Decision-Making Process Modelling under Controlled Intervention Conditions

    Directory of Open Access Journals (Sweden)

    Bakanauskienė Irena

    2017-12-01

    Full Text Available This article is intended to theoretically justify the decision-making process model for the cases, when active participation of investing entities in controlling the activities of an organisation and their results is noticeable. Based on scientific literature analysis, a concept of controlled conditions is formulated, and using a rational approach to the decision-making process, a model of the 11-steps decision-making process under controlled intervention is presented. Also, there have been unified conditions, describing the case of controlled interventions thus providing preconditions to ensure the adequacy of the proposed decision-making process model.

  5. Combining morphological analysis and Bayesian networks for strategic decision support

    Directory of Open Access Journals (Sweden)

    A de Waal

    2007-12-01

    Full Text Available Morphological analysis (MA and Bayesian networks (BN are two closely related modelling methods, each of which has its advantages and disadvantages for strategic decision support modelling. MA is a method for defining, linking and evaluating problem spaces. BNs are graphical models which consist of a qualitative and quantitative part. The qualitative part is a cause-and-effect, or causal graph. The quantitative part depicts the strength of the causal relationships between variables. Combining MA and BN, as two phases in a modelling process, allows us to gain the benefits of both of these methods. The strength of MA lies in defining, linking and internally evaluating the parameters of problem spaces and BN modelling allows for the definition and quantification of causal relationships between variables. Short summaries of MA and BN are provided in this paper, followed by discussions how these two computer aided methods may be combined to better facilitate modelling procedures. A simple example is presented, concerning a recent application in the field of environmental decision support.

  6. A Primer on Bayesian Decision Analysis With an Application to a Kidney Transplant Decision.

    Science.gov (United States)

    Neapolitan, Richard; Jiang, Xia; Ladner, Daniela P; Kaplan, Bruce

    2016-03-01

    A clinical decision support system (CDSS) is a computer program, which is designed to assist health care professionals with decision making tasks. A well-developed CDSS weighs the benefits of therapy versus the cost in terms of loss of quality of life and financial loss and recommends the decision that can be expected to provide maximum overall benefit. This article provides an introduction to developing CDSSs using Bayesian networks, such CDSS can help with the often complex decisions involving transplants. First, we review Bayes theorem in the context of medical decision making. Then, we introduce Bayesian networks, which can model probabilistic relationships among many related variables and are based on Bayes theorem. Next, we discuss influence diagrams, which are Bayesian networks augmented with decision and value nodes and which can be used to develop CDSSs that are able to recommend decisions that maximize the expected utility of the predicted outcomes to the patient. By way of comparison, we examine the benefit and challenges of using the Kidney Donor Risk Index as the sole decision tool. Finally, we develop a schema for an influence diagram that models generalized kidney transplant decisions and show how the influence diagram approach can provide the clinician and the potential transplant recipient with a valuable decision support tool.

  7. A novel sustainable decision making model for municipal solid waste management

    International Nuclear Information System (INIS)

    Hung, M.-L.; Ma Hwongwen; Yang, W.-F.

    2007-01-01

    This paper reviews several models developed to support decision making in municipal solid waste management (MSWM). The concepts underlying sustainable MSWM models can be divided into two categories: one incorporates social factors into decision making methods, and the other includes public participation in the decision-making process. The public is only apprised or takes part in discussion, and has little effect on decision making in most research efforts. Few studies have considered public participation in the decision-making process, and the methods have sought to strike a compromise between concerned criteria, not between stakeholders. However, the source of the conflict arises from the stakeholders' complex web of value. Such conflict affects the feasibility of implementing any decision. The purpose of this study is to develop a sustainable decision making model for MSWM to overcome these shortcomings. The proposed model combines multicriteria decision making (MCDM) and a consensus analysis model (CAM). The CAM is built up to aid in decision-making when MCDM methods are utilized and, subsequently, a novel sustainable decision making model for MSWM is developed. The main feature of CAM is the assessment of the degree of consensus between stakeholders for particular alternatives. A case study for food waste management in Taiwan is presented to demonstrate the practicality of this model

  8. Risk-based decision analysis for groundwater operable units

    International Nuclear Information System (INIS)

    Chiaramonte, G.R.

    1995-01-01

    This document proposes a streamlined approach and methodology for performing risk assessment in support of interim remedial measure (IRM) decisions involving the remediation of contaminated groundwater on the Hanford Site. This methodology, referred to as ''risk-based decision analysis,'' also supports the specification of target cleanup volumes and provides a basis for design and operation of the groundwater remedies. The risk-based decision analysis can be completed within a short time frame and concisely documented. The risk-based decision analysis is more versatile than the qualitative risk assessment (QRA), because it not only supports the need for IRMs, but also provides criteria for defining the success of the IRMs and provides the risk-basis for decisions on final remedies. For these reasons, it is proposed that, for groundwater operable units, the risk-based decision analysis should replace the more elaborate, costly, and time-consuming QRA

  9. Simulation Models of Human Decision-Making Processes

    Directory of Open Access Journals (Sweden)

    Nina RIZUN

    2014-10-01

    Full Text Available The main purpose of the paper is presentation of the new concept of human decision-making process modeling via using the analogy with Automatic Control Theory. From the author's point of view this concept allows to develop and improve the theory of decision-making in terms of the study and classification of specificity of the human intellectual processes in different conditions. It was proved that the main distinguishing feature between the Heuristic / Intuitive and Rational Decision-Making Models is the presence of so-called phenomenon of "enrichment" of the input information with human propensity, hobbies, tendencies, expectations, axioms and judgments, presumptions or bias and their justification. In order to obtain additional knowledge about the basic intellectual processes as well as the possibility of modeling the decision results in various parameters characterizing the decision-maker, the complex of the simulation models was developed. These models are based on the assumptions that:  basic intellectual processes of the Rational Decision-Making Model can be adequately simulated and identified by the transient processes of the proportional-integral-derivative controller; basic intellectual processes of the Bounded Rationality and Intuitive Models can be adequately simulated and identified by the transient processes of the nonlinear elements.The taxonomy of the most typical automatic control theory elements and their compliance with certain decision-making models with a point of view of decision-making process specificity and decision-maker behavior during a certain time of professional activity was obtained.

  10. [Decision modeling for economic evaluation of health technologies].

    Science.gov (United States)

    de Soárez, Patrícia Coelho; Soares, Marta Oliveira; Novaes, Hillegonda Maria Dutilh

    2014-10-01

    Most economic evaluations that participate in decision-making processes for incorporation and financing of technologies of health systems use decision models to assess the costs and benefits of the compared strategies. Despite the large number of economic evaluations conducted in Brazil, there is a pressing need to conduct an in-depth methodological study of the types of decision models and their applicability in our setting. The objective of this literature review is to contribute to the knowledge and use of decision models in the national context of economic evaluations of health technologies. This article presents general definitions about models and concerns with their use; it describes the main models: decision trees, Markov chains, micro-simulation, simulation of discrete and dynamic events; it discusses the elements involved in the choice of model; and exemplifies the models addressed in national economic evaluation studies of diagnostic and therapeutic preventive technologies and health programs.

  11. Multivariate analysis: models and method

    International Nuclear Information System (INIS)

    Sanz Perucha, J.

    1990-01-01

    Data treatment techniques are increasingly used since computer methods result of wider access. Multivariate analysis consists of a group of statistic methods that are applied to study objects or samples characterized by multiple values. A final goal is decision making. The paper describes the models and methods of multivariate analysis

  12. An interpretive structural modeling (ISM) and decision-making trail and evaluation laboratory (DEMATEL) method approach for the analysis of barriers of waste recycling in India.

    Science.gov (United States)

    Chauhan, Ankur; Singh, Amol; Jharkharia, Sanjay

    2018-02-01

    Increasing amount of wastes is posing great difficulties for all countries across the world. The problem of waste management is more severe in developing countries such as India where the rates of economic growth and urbanization are increasing at a fast pace. The governments in these countries are often constrained by limited technical and financial capabilities, which prevent them from effectively addressing these problems. There is a limited participation from the private players too in terms of setting up of waste recycling units. The present study aims at identifying various barriers that challenge the establishment of these units, specific to India. Further, it attempts to identify the most influential barriers by utilizing multicriterion decision-making tools of interpretive structural modeling (ISM) and decision-making trail and evaluation laboratory (DEMATEL). The findings of the study suggest that the lack of funds, input material, and subsidy are the most influential barriers that are needed to be addressed for the development of waste recycling infrastructure in India. This work has been carried out to address the problem of proper waste management in India. To deal with this problem, the method of waste recycling has been felt appropriate by the government of various countries, including India. Therefore, the barriers that play vital role in waste recycling for private players have been identified and their importance has been established with the help of ISM and DEMATEL methods. Doing so will assist the government to take appropriate steps for the betterment of waste recycling infrastructure in India and enhance waste management.

  13. A Layered Decision Model for Cost-Effective System Security

    Energy Technology Data Exchange (ETDEWEB)

    Wei, Huaqiang; Alves-Foss, James; Soule, Terry; Pforsich, Hugh; Zhang, Du; Frincke, Deborah A.

    2008-10-01

    System security involves decisions in at least three areas: identification of well-defined security policies, selection of cost-effective defence strategies, and implementation of real-time defence tactics. Although choices made in each of these areas affect the others, existing decision models typically handle these three decision areas in isolation. There is no comprehensive tool that can integrate them to provide a single efficient model for safeguarding a network. In addition, there is no clear way to determine which particular combinations of defence decisions result in cost-effective solutions. To address these problems, this paper introduces a Layered Decision Model (LDM) for use in deciding how to address defence decisions based on their cost-effectiveness. To validate the LDM and illustrate how it is used, we used simulation to test model rationality and applied the LDM to the design of system security for an e-commercial business case.

  14. Economic decision making and the application of nonparametric prediction models

    Science.gov (United States)

    Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

    2008-01-01

    Sustained increases in energy prices have focused attention on gas resources in low-permeability shale or in coals that were previously considered economically marginal. Daily well deliverability is often relatively small, although the estimates of the total volumes of recoverable resources in these settings are often large. Planning and development decisions for extraction of such resources must be areawide because profitable extraction requires optimization of scale economies to minimize costs and reduce risk. For an individual firm, the decision to enter such plays depends on reconnaissance-level estimates of regional recoverable resources and on cost estimates to develop untested areas. This paper shows how simple nonparametric local regression models, used to predict technically recoverable resources at untested sites, can be combined with economic models to compute regional-scale cost functions. The context of the worked example is the Devonian Antrim-shale gas play in the Michigan basin. One finding relates to selection of the resource prediction model to be used with economic models. Models chosen because they can best predict aggregate volume over larger areas (many hundreds of sites) smooth out granularity in the distribution of predicted volumes at individual sites. This loss of detail affects the representation of economic cost functions and may affect economic decisions. Second, because some analysts consider unconventional resources to be ubiquitous, the selection and order of specific drilling sites may, in practice, be determined arbitrarily by extraneous factors. The analysis shows a 15-20% gain in gas volume when these simple models are applied to order drilling prospects strategically rather than to choose drilling locations randomly. Copyright ?? 2008 Society of Petroleum Engineers.

  15. Investment timing decisions in a stochastic duopoly model

    Energy Technology Data Exchange (ETDEWEB)

    Marseguerra, Giovanni [Istituto di Econometria e CRANEC, Universita Cattolica del Sacro Cuore di Milan (Italy)]. E-mail: giovanni.marseguerra@unicatt.it; Cortelezzi, Flavia [Dipartimento di Diritto ed Economia delle Persone e delle Imprese, Universita dell' Insubria (Italy)]. E-mail: flavia.cortelezzi@uninsubria.it; Dominioni, Armando [CORE-Catholique de Louvain la Neuve (Belgium)]. E-mail: dominioni@core.ucl.ac.be

    2006-08-15

    We investigate the role of strategic considerations on the optimal timing of investment when firms compete for a new market (e.g., the provision of an innovative product) under demand uncertainty. Within a continuous time model of stochastic oligopoly, we show that strategic considerations are likely to be of limited impact when the new product is radically innovative whilst the fear of a rival's entry may deeply affect firms' decisions whenever innovation is to some extent limited. The welfare analysis shows surprisingly that the desirability of the different market structures considered does not depend on the fixed entry cost.

  16. Investment timing decisions in a stochastic duopoly model

    International Nuclear Information System (INIS)

    Marseguerra, Giovanni; Cortelezzi, Flavia; Dominioni, Armando

    2006-01-01

    We investigate the role of strategic considerations on the optimal timing of investment when firms compete for a new market (e.g., the provision of an innovative product) under demand uncertainty. Within a continuous time model of stochastic oligopoly, we show that strategic considerations are likely to be of limited impact when the new product is radically innovative whilst the fear of a rival's entry may deeply affect firms' decisions whenever innovation is to some extent limited. The welfare analysis shows surprisingly that the desirability of the different market structures considered does not depend on the fixed entry cost

  17. Modeling Based Decision Support Environment, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Phoenix Integration's vision is the creation of an intuitive human-in-the-loop engineering environment called Decision Navigator that leverages recent advances in...

  18. A cooperative model of decision making

    International Nuclear Information System (INIS)

    Armour, A.M.

    1993-01-01

    This paper will describe an experiment aimed at increasing the social responsiveness of planning and decision processes. It involves an on-going effort by the canadian federal government to site a facility to manage low level radioactive wastes

  19. Generative Agents for Player Decision Modeling in Games

    DEFF Research Database (Denmark)

    Holmgård, Christoffer; Liapis, Antonios; Togelius, Julian

    2014-01-01

    This paper presents a method for modeling player decision making through the use of agents as AI-driven personas. The paper argues that artificial agents, as generative player models, have properties that allow them to be used as psyhometrically valid, abstract simulations of a human player......’s internal decision making processes. Such agents can then be used to interpret human decision making, as personas and playtesting tools in the game design process, as baselines for adapting agents to mimic classes of human players, or as believable, human-like opponents. This argument is explored...... in a crowdsourced decision making experiment, in which the decisions of human players are recorded in a small-scale dungeon themed puzzle game. Human decisions are compared to the decisions of a number of a priori defined “archetypical” agent-personas, and the humans are characterized by their likeness...

  20. MARKET EVALUATION MODEL: TOOL FORBUSINESS DECISIONS

    OpenAIRE

    Porlles Loarte, José; Yenque Dedios, Julio; Lavado Soto, Aurelio

    2014-01-01

    In the present work the concepts of potential market and global market are analyzed as the basis for strategic decisions of market with long term perspectives, when the implantation of a business in certain geographic area is evaluated. On this conceptual frame, the methodological tool is proposed to evaluate a commercial decision, for which it is taken as reference the case from the brewing industry in Peru, considering that this industry faces in the region entrepreneurial reorderings withi...

  1. Use of the sensitivity analysis for multi-attributes decision models for oil exploration and production systems; Uso da analise de sensibilidade em modelos de decisao multiatributos para sistemas de exploracao e producao de petroleo

    Energy Technology Data Exchange (ETDEWEB)

    Furtado, Ricardo

    2000-07-01

    Today, oil companies must be able to survive in a hostile and competitive environment. Such environment involves volatility of oil prices, the narrow margins of profitability, and ever increasing environmental restrictions. In order to survive, firms must have the appropriate tools to consider the tradeoffs involving the financial, environmental, technological and of market parameters which are the key elements within the investment decision-making process. The aim of the present work is to analyze the behavior of the weights (relative importance) of the attributes int the multi-criteria decision model through a high dimension sensitivity analysis. Among the benefits of such method are: provide the analyst (decision-maker) with a better characterization and control of the weights of the attributes, providing the user with a clear view of the entire decision process. The methodology suggested in this dissertation was applied in two oil exploration and production case studies. The first case involved the selection of an exploratory target among three options. In this case, there is interaction of the objectives of the company, where financial, technological and of market parameters interact. In the second case, a hypothetical production project is suggested. For this second study, the decision-maker has the option of using one of the following production systems: a FPSO (Floating, Production, Storage and Offloading); a TLP (Tension Leg Platform); or a SS (Semi Submersible). The attributes for each one of the production systems are financial, technological and environmental. In this second case, the model makes it possible to simulate several options, providing the manager with the choice of the most appropriate production system to this objectives and preferences. (author)

  2. Evolution of quantum-like modeling in decision making processes

    Science.gov (United States)

    Khrennikova, Polina

    2012-12-01

    The application of the mathematical formalism of quantum mechanics to model behavioral patterns in social science and economics is a novel and constantly emerging field. The aim of the so called 'quantum like' models is to model the decision making processes in a macroscopic setting, capturing the particular 'context' in which the decisions are taken. Several subsequent empirical findings proved that when making a decision people tend to violate the axioms of expected utility theory and Savage's Sure Thing principle, thus violating the law of total probability. A quantum probability formula was devised to describe more accurately the decision making processes. A next step in the development of QL-modeling in decision making was the application of Schrödinger equation to describe the evolution of people's mental states. A shortcoming of Schrödinger equation is its inability to capture dynamics of an open system; the brain of the decision maker can be regarded as such, actively interacting with the external environment. Recently the master equation, by which quantum physics describes the process of decoherence as the result of interaction of the mental state with the environmental 'bath', was introduced for modeling the human decision making. The external environment and memory can be referred to as a complex 'context' influencing the final decision outcomes. The master equation can be considered as a pioneering and promising apparatus for modeling the dynamics of decision making in different contexts.

  3. Evolution of quantum-like modeling in decision making processes

    Energy Technology Data Exchange (ETDEWEB)

    Khrennikova, Polina [School of Management, University of Leicester, University Road Leicester LE1 7RH (United Kingdom)

    2012-12-18

    The application of the mathematical formalism of quantum mechanics to model behavioral patterns in social science and economics is a novel and constantly emerging field. The aim of the so called 'quantum like' models is to model the decision making processes in a macroscopic setting, capturing the particular 'context' in which the decisions are taken. Several subsequent empirical findings proved that when making a decision people tend to violate the axioms of expected utility theory and Savage's Sure Thing principle, thus violating the law of total probability. A quantum probability formula was devised to describe more accurately the decision making processes. A next step in the development of QL-modeling in decision making was the application of Schroedinger equation to describe the evolution of people's mental states. A shortcoming of Schroedinger equation is its inability to capture dynamics of an open system; the brain of the decision maker can be regarded as such, actively interacting with the external environment. Recently the master equation, by which quantum physics describes the process of decoherence as the result of interaction of the mental state with the environmental 'bath', was introduced for modeling the human decision making. The external environment and memory can be referred to as a complex 'context' influencing the final decision outcomes. The master equation can be considered as a pioneering and promising apparatus for modeling the dynamics of decision making in different contexts.

  4. Evolution of quantum-like modeling in decision making processes

    International Nuclear Information System (INIS)

    Khrennikova, Polina

    2012-01-01

    The application of the mathematical formalism of quantum mechanics to model behavioral patterns in social science and economics is a novel and constantly emerging field. The aim of the so called 'quantum like' models is to model the decision making processes in a macroscopic setting, capturing the particular 'context' in which the decisions are taken. Several subsequent empirical findings proved that when making a decision people tend to violate the axioms of expected utility theory and Savage's Sure Thing principle, thus violating the law of total probability. A quantum probability formula was devised to describe more accurately the decision making processes. A next step in the development of QL-modeling in decision making was the application of Schrödinger equation to describe the evolution of people's mental states. A shortcoming of Schrödinger equation is its inability to capture dynamics of an open system; the brain of the decision maker can be regarded as such, actively interacting with the external environment. Recently the master equation, by which quantum physics describes the process of decoherence as the result of interaction of the mental state with the environmental 'bath', was introduced for modeling the human decision making. The external environment and memory can be referred to as a complex 'context' influencing the final decision outcomes. The master equation can be considered as a pioneering and promising apparatus for modeling the dynamics of decision making in different contexts.

  5. An Analysis of Design Decision-Making in Industrial Practice

    DEFF Research Database (Denmark)

    Ahmed, Saeema; Hansen, Claus Thorp

    2002-01-01

    This paper describes research that confronts a generic decision-making model with design strategies employed by experienced designers. The relationship between the decision-making activities proposed by the model and the eight design strategies identified by an empirical study of design work is e...

  6. A Model for Evidence Accumulation in the Lexical Decision Task

    Science.gov (United States)

    Wagenmakers, Eric-Jan; Steyvers, Mark; Raaijmakers, Jeroen G. W.; Shiffrin, Richard M.; van Rijn, Hedderik; Zeelenberg, Rene

    2004-01-01

    We present a new model for lexical decision, REM-LD, that is based on REM theory (e.g., Shiffrin & Steyvers, 1997). REM-LD uses a principled (i.e., Bayes' rule) decision process that simultaneously considers the diagnosticity of the evidence for the 'WORD' response and the 'NONWORD' response. The model calculates the odds ratio that the presented…

  7. Relevance of a Managerial Decision-Model to Educational Administration.

    Science.gov (United States)

    Lundin, Edward.; Welty, Gordon

    The rational model of classical economic theory assumes that the decision maker has complete information on alternatives and consequences, and that he chooses the alternative that maximizes expected utility. This model does not allow for constraints placed on the decision maker resulting from lack of information, organizational pressures,…

  8. Embedding a State Space Model Into a Markov Decision Process

    DEFF Research Database (Denmark)

    Nielsen, Lars Relund; Jørgensen, Erik; Højsgaard, Søren

    2011-01-01

    In agriculture Markov decision processes (MDPs) with finite state and action space are often used to model sequential decision making over time. For instance, states in the process represent possible levels of traits of the animal and transition probabilities are based on biological models...

  9. Reviewing model application to support animal health decision making.

    Science.gov (United States)

    Singer, Alexander; Salman, Mo; Thulke, Hans-Hermann

    2011-04-01

    Animal health is of societal importance as it affects human welfare, and anthropogenic interests shape decision making to assure animal health. Scientific advice to support decision making is manifold. Modelling, as one piece of the scientific toolbox, is appreciated for its ability to describe and structure data, to give insight in complex processes and to predict future outcome. In this paper we study the application of scientific modelling to support practical animal health decisions. We reviewed the 35 animal health related scientific opinions adopted by the Animal Health and Animal Welfare Panel of the European Food Safety Authority (EFSA). Thirteen of these documents were based on the application of models. The review took two viewpoints, the decision maker's need and the modeller's approach. In the reviewed material three types of modelling questions were addressed by four specific model types. The correspondence between tasks and models underpinned the importance of the modelling question in triggering the modelling approach. End point quantifications were the dominating request from decision makers, implying that prediction of risk is a major need. However, due to knowledge gaps corresponding modelling studies often shed away from providing exact numbers. Instead, comparative scenario analyses were performed, furthering the understanding of the decision problem and effects of alternative management options. In conclusion, the most adequate scientific support for decision making - including available modelling capacity - might be expected if the required advice is clearly stated. Copyright © 2011 Elsevier B.V. All rights reserved.

  10. Multicriteria decision group model for the selection of suppliers

    Directory of Open Access Journals (Sweden)

    Luciana Hazin Alencar

    2008-08-01

    Full Text Available Several authors have been studying group decision making over the years, which indicates how relevant it is. This paper presents a multicriteria group decision model based on ELECTRE IV and VIP Analysis methods, to those cases where there is great divergence among the decision makers. This model includes two stages. In the first, the ELECTRE IV method is applied and a collective criteria ranking is obtained. In the second, using criteria ranking, VIP Analysis is applied and the alternatives are selected. To illustrate the model, a numerical application in the context of the selection of suppliers in project management is used. The suppliers that form part of the project team have a crucial role in project management. They are involved in a network of connected activities that can jeopardize the success of the project, if they are not undertaken in an appropriate way. The question tackled is how to select service suppliers for a project on behalf of an enterprise that assists the multiple objectives of the decision-makers.Vários autores têm estudado decisão em grupo nos últimos anos, o que indica a relevância do assunto. Esse artigo apresenta um modelo multicritério de decisão em grupo baseado nos métodos ELECTRE IV e VIP Analysis, adequado aos casos em que se tem uma grande divergência entre os decisores. Esse modelo é composto por dois estágios. No primeiro, o método ELECTRE IV é aplicado e uma ordenação dos critérios é obtida. No próximo estágio, com a ordenação dos critérios, o método VIP Analysis é aplicado e as alternativas são selecionadas. Para ilustrar o modelo, uma aplicação numérica no contexto da seleção de fornecedores em projetos é realizada. Os fornecedores que fazem parte da equipe do projeto têm um papel fundamental no gerenciamento de projetos. Eles estão envolvidos em uma rede de atividades conectadas que, caso não sejam executadas de forma apropriada, podem colocar em risco o sucesso do

  11. A multicriteria decision making model for assessment and selection of an ERP in a logistics context

    Science.gov (United States)

    Pereira, Teresa; Ferreira, Fernanda A.

    2017-07-01

    The aim of this work is to apply a methodology of decision support based on a multicriteria decision analyses (MCDA) model that allows the assessment and selection of an Enterprise Resource Planning (ERP) in a Portuguese logistics company by Group Decision Maker (GDM). A Decision Support system (DSS) that implements a MCDA - Multicriteria Methodology for the Assessment and Selection of Information Systems / Information Technologies (MMASSI / IT) is used based on its features and facility to change and adapt the model to a given scope. Using this DSS it was obtained the information system that best suited to the decisional context, being this result evaluated through a sensitivity and robustness analysis.

  12. Ethical analysis to improve decision-making on health technologies

    DEFF Research Database (Denmark)

    Saarni, Samuli I; Hofmann, Bjørn; Lampe, Kristian

    2008-01-01

    beyond effectiveness and costs to also considering the social, organizational and ethical implications of technologies. However, a commonly accepted method for analysing the ethical aspects of health technologies is lacking. This paper describes a model for ethical analysis of health technology...... that is easy and flexible to use in different organizational settings and cultures. The model is part of the EUnetHTA project, which focuses on the transferability of HTAs between countries. The EUnetHTA ethics model is based on the insight that the whole HTA process is value laden. It is not sufficient...... to only analyse the ethical consequences of a technology, but also the ethical issues of the whole HTA process must be considered. Selection of assessment topics, methods and outcomes is essentially a value-laden decision. Health technologies may challenge moral or cultural values and beliefs...

  13. Rodent models of adaptive decision making.

    Science.gov (United States)

    Izquierdo, Alicia; Belcher, Annabelle M

    2012-01-01

    Adaptive decision making affords the animal the ability to respond quickly to changes in a dynamic environment: one in which attentional demands, cost or effort to procure the reward, and reward contingencies change frequently. The more flexible the organism is in adapting choice behavior, the more command and success the organism has in navigating its environment. Maladaptive decision making is at the heart of much neuropsychiatric disease, including addiction. Thus, a better understanding of the mechanisms that underlie normal, adaptive decision making helps achieve a better understanding of certain diseases that incorporate maladaptive decision making as a core feature. This chapter presents three general domains of methods that the experimenter can manipulate in animal decision-making tasks: attention, effort, and reward contingency. Here, we present detailed methods of rodent tasks frequently employed within these domains: the Attentional Set-Shift Task, Effortful T-maze Task, and Visual Discrimination Reversal Learning. These tasks all recruit regions within the frontal cortex and the striatum, and performance is heavily modulated by the neurotransmitter dopamine, making these assays highly valid measures in the study of psychostimulant addiction.

  14. Relating cost-benefit analysis results with transport project decisions in the Netherlands

    NARCIS (Netherlands)

    Annema, Jan Anne; Frenken, Koen|info:eu-repo/dai/nl/207145253; Koopmans, Carl; Kroesen, Maarten

    2017-01-01

    This paper relates the cost-benefit analysis (CBA) results of transportation policy proposals in the Netherlands with the decision to implement or abandon the proposal. The aim of this study is to explore the relation between the CBA results and decision-making. Multinomial logit regression models

  15. Knowledge-Based Decision Model Construction for Dynamic Interpretation Tasks

    National Research Council Canada - National Science Library

    Wellman, Michael

    1997-01-01

    ...) is highly variable, precluding specification of a fixed model in advance. The project yielded technical results in four areas of reasoning and decision making under uncertainty involving model construction: (1...

  16. Ethical analysis to improve decision-making on health technologies.

    Science.gov (United States)

    Saarni, Samuli I; Hofmann, Bjørn; Lampe, Kristian; Lühmann, Dagmar; Mäkelä, Marjukka; Velasco-Garrido, Marcial; Autti-Rämö, Ilona

    2008-08-01

    Health technology assessment (HTA) is the multidisciplinary study of the implications of the development, diffusion and use of health technologies. It supports health-policy decisions by providing a joint knowledge base for decision-makers. To increase its policy relevance, HTA tries to extend beyond effectiveness and costs to also considering the social, organizational and ethical implications of technologies. However, a commonly accepted method for analysing the ethical aspects of health technologies is lacking. This paper describes a model for ethical analysis of health technology that is easy and flexible to use in different organizational settings and cultures. The model is part of the EUnetHTA project, which focuses on the transferability of HTAs between countries. The EUnetHTA ethics model is based on the insight that the whole HTA process is value laden. It is not sufficient to only analyse the ethical consequences of a technology, but also the ethical issues of the whole HTA process must be considered. Selection of assessment topics, methods and outcomes is essentially a value-laden decision. Health technologies may challenge moral or cultural values and beliefs, and their implementation may also have significant impact on people other than the patient. These are essential considerations for health policy. The ethics model is structured around key ethical questions rather than philosophical theories, to be applicable to different cultures and usable by non-philosophers. Integrating ethical considerations into HTA can improve the relevance of technology assessments for health care and health policy in both developed and developing countries.

  17. Bayesian model selection techniques as decision support for shaping a statistical analysis plan of a clinical trial: An example from a vertigo phase III study with longitudinal count data as primary endpoint

    Directory of Open Access Journals (Sweden)

    Adrion Christine

    2012-09-01

    Full Text Available Abstract Background A statistical analysis plan (SAP is a critical link between how a clinical trial is conducted and the clinical study report. To secure objective study results, regulatory bodies expect that the SAP will meet requirements in pre-specifying inferential analyses and other important statistical techniques. To write a good SAP for model-based sensitivity and ancillary analyses involves non-trivial decisions on and justification of many aspects of the chosen setting. In particular, trials with longitudinal count data as primary endpoints pose challenges for model choice and model validation. In the random effects setting, frequentist strategies for model assessment and model diagnosis are complex and not easily implemented and have several limitations. Therefore, it is of interest to explore Bayesian alternatives which provide the needed decision support to finalize a SAP. Methods We focus on generalized linear mixed models (GLMMs for the analysis of longitudinal count data. A series of distributions with over- and under-dispersion is considered. Additionally, the structure of the variance components is modified. We perform a simulation study to investigate the discriminatory power of Bayesian tools for model criticism in different scenarios derived from the model setting. We apply the findings to the data from an open clinical trial on vertigo attacks. These data are seen as pilot data for an ongoing phase III trial. To fit GLMMs we use a novel Bayesian computational approach based on integrated nested Laplace approximations (INLAs. The INLA methodology enables the direct computation of leave-one-out predictive distributions. These distributions are crucial for Bayesian model assessment. We evaluate competing GLMMs for longitudinal count data according to the deviance information criterion (DIC or probability integral transform (PIT, and by using proper scoring rules (e.g. the logarithmic score. Results The instruments under study

  18. Bayesian model selection techniques as decision support for shaping a statistical analysis plan of a clinical trial: an example from a vertigo phase III study with longitudinal count data as primary endpoint.

    Science.gov (United States)

    Adrion, Christine; Mansmann, Ulrich

    2012-09-10

    A statistical analysis plan (SAP) is a critical link between how a clinical trial is conducted and the clinical study report. To secure objective study results, regulatory bodies expect that the SAP will meet requirements in pre-specifying inferential analyses and other important statistical techniques. To write a good SAP for model-based sensitivity and ancillary analyses involves non-trivial decisions on and justification of many aspects of the chosen setting. In particular, trials with longitudinal count data as primary endpoints pose challenges for model choice and model validation. In the random effects setting, frequentist strategies for model assessment and model diagnosis are complex and not easily implemented and have several limitations. Therefore, it is of interest to explore Bayesian alternatives which provide the needed decision support to finalize a SAP. We focus on generalized linear mixed models (GLMMs) for the analysis of longitudinal count data. A series of distributions with over- and under-dispersion is considered. Additionally, the structure of the variance components is modified. We perform a simulation study to investigate the discriminatory power of Bayesian tools for model criticism in different scenarios derived from the model setting. We apply the findings to the data from an open clinical trial on vertigo attacks. These data are seen as pilot data for an ongoing phase III trial. To fit GLMMs we use a novel Bayesian computational approach based on integrated nested Laplace approximations (INLAs). The INLA methodology enables the direct computation of leave-one-out predictive distributions. These distributions are crucial for Bayesian model assessment. We evaluate competing GLMMs for longitudinal count data according to the deviance information criterion (DIC) or probability integral transform (PIT), and by using proper scoring rules (e.g. the logarithmic score). The instruments under study provide excellent tools for preparing decisions

  19. 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 ...

  20. Engaging stakeholders for adaptive management using structured decision analysis

    Science.gov (United States)

    Irwin, Elise R.; Kathryn, D.; Kennedy, Mickett

    2009-01-01

    Adaptive management is different from other types of management in that it includes all stakeholders (versus only policy makers) in the process, uses resource optimization techniques to evaluate competing objectives, and recognizes and attempts to reduce uncertainty inherent in natural resource systems. Management actions are negotiated by stakeholders, monitored results are compared to predictions of how the system should respond, and management strategies are adjusted in a “monitor-compare-adjust” iterative routine. Many adaptive management projects fail because of the lack of stakeholder identification, engagement, and continued involvement. Primary reasons for this vary but are usually related to either stakeholders not having ownership (or representation) in decision processes or disenfranchisement of stakeholders after adaptive management begins. We present an example in which stakeholders participated fully in adaptive management of a southeastern regulated river. Structured decision analysis was used to define management objectives and stakeholder values and to determine initial flow prescriptions. The process was transparent, and the visual nature of the modeling software allowed stakeholders to see how their interests and values were represented in the decision process. The development of a stakeholder governance structure and communication mechanism has been critical to the success of the project.

  1. Multivariate Analysis of Household Decision Making, Contraceptive ...

    African Journals Online (AJOL)

    Nneka Umera-Okeke

    contraceptives and fertility behaviour of ever-married men in Nigeria. ... exposure. The study concluded that women empowerment in decision ... through the prevention of unwanted and unplanned births is one of the most effective .... visitors who slept in the household the previous night before the survey) were eligible ...

  2. Decision support modeling for milk valorization

    NARCIS (Netherlands)

    Banaszewska, A.

    2014-01-01

    The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating

  3. Modeling uncertainty in requirements engineering decision support

    Science.gov (United States)

    Feather, Martin S.; Maynard-Zhang, Pedrito; Kiper, James D.

    2005-01-01

    One inherent characteristic of requrements engineering is a lack of certainty during this early phase of a project. Nevertheless, decisions about requirements must be made in spite of this uncertainty. Here we describe the context in which we are exploring this, and some initial work to support elicitation of uncertain requirements, and to deal with the combination of such information from multiple stakeholders.

  4. Decision Making Analysis: Critical Factors-Based Methodology

    Science.gov (United States)

    2010-04-01

    the pitfalls associated with current wargaming methods such as assuming a western view of rational values in decision - making regardless of the cultures...Utilization theory slightly expands the rational decision making model as it states that “actors try to maximize their expected utility by weighing the...items to categorize the decision - making behavior of political leaders which tend to demonstrate either a rational or cognitive leaning. Leaders

  5. Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management.

    Science.gov (United States)

    Convertino, Matteo; Valverde, L James

    2013-01-01

    Management of natural resources in coastal ecosystems is a complex process that is made more challenging by the need for stakeholders to confront the prospect of sea level rise and a host of other environmental stressors. This situation is especially true for coastal military installations, where resource managers need to balance conflicting objectives of environmental conservation against military mission. The development of restoration plans will necessitate incorporating stakeholder preferences, and will, moreover, require compliance with applicable federal/state laws and regulations. To promote the efficient allocation of scarce resources in space and time, we develop a portfolio decision analytic (PDA) framework that integrates models yielding policy-dependent predictions for changes in land cover and species metapopulations in response to restoration plans, under different climate change scenarios. In a manner that is somewhat analogous to financial portfolios, infrastructure and natural resources are classified as human and natural assets requiring management. The predictions serve as inputs to a Multi Criteria Decision Analysis model (MCDA) that is used to measure the benefits of restoration plans, as well as to construct Pareto frontiers that represent optimal portfolio allocations of restoration actions and resources. Optimal plans allow managers to maintain or increase asset values by contrasting the overall degradation of the habitat and possible increased risk of species decline against the benefits of mission success. The optimal combination of restoration actions that emerge from the PDA framework allows decision-makers to achieve higher environmental benefits, with equal or lower costs, than those achievable by adopting the myopic prescriptions of the MCDA model. The analytic framework presented here is generalizable for the selection of optimal management plans in any ecosystem where human use of the environment conflicts with the needs of

  6. Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management.

    Directory of Open Access Journals (Sweden)

    Matteo Convertino

    Full Text Available Management of natural resources in coastal ecosystems is a complex process that is made more challenging by the need for stakeholders to confront the prospect of sea level rise and a host of other environmental stressors. This situation is especially true for coastal military installations, where resource managers need to balance conflicting objectives of environmental conservation against military mission. The development of restoration plans will necessitate incorporating stakeholder preferences, and will, moreover, require compliance with applicable federal/state laws and regulations. To promote the efficient allocation of scarce resources in space and time, we develop a portfolio decision analytic (PDA framework that integrates models yielding policy-dependent predictions for changes in land cover and species metapopulations in response to restoration plans, under different climate change scenarios. In a manner that is somewhat analogous to financial portfolios, infrastructure and natural resources are classified as human and natural assets requiring management. The predictions serve as inputs to a Multi Criteria Decision Analysis model (MCDA that is used to measure the benefits of restoration plans, as well as to construct Pareto frontiers that represent optimal portfolio allocations of restoration actions and resources. Optimal plans allow managers to maintain or increase asset values by contrasting the overall degradation of the habitat and possible increased risk of species decline against the benefits of mission success. The optimal combination of restoration actions that emerge from the PDA framework allows decision-makers to achieve higher environmental benefits, with equal or lower costs, than those achievable by adopting the myopic prescriptions of the MCDA model. The analytic framework presented here is generalizable for the selection of optimal management plans in any ecosystem where human use of the environment conflicts with the

  7. Portfolio Decision Analysis Framework for Value-Focused Ecosystem Management

    Science.gov (United States)

    Convertino, Matteo; Valverde, L. James

    2013-01-01

    Management of natural resources in coastal ecosystems is a complex process that is made more challenging by the need for stakeholders to confront the prospect of sea level rise and a host of other environmental stressors. This situation is especially true for coastal military installations, where resource managers need to balance conflicting objectives of environmental conservation against military mission. The development of restoration plans will necessitate incorporating stakeholder preferences, and will, moreover, require compliance with applicable federal/state laws and regulations. To promote the efficient allocation of scarce resources in space and time, we develop a portfolio decision analytic (PDA) framework that integrates models yielding policy-dependent predictions for changes in land cover and species metapopulations in response to restoration plans, under different climate change scenarios. In a manner that is somewhat analogous to financial portfolios, infrastructure and natural resources are classified as human and natural assets requiring management. The predictions serve as inputs to a Multi Criteria Decision Analysis model (MCDA) that is used to measure the benefits of restoration plans, as well as to construct Pareto frontiers that represent optimal portfolio allocations of restoration actions and resources. Optimal plans allow managers to maintain or increase asset values by contrasting the overall degradation of the habitat and possible increased risk of species decline against the benefits of mission success. The optimal combination of restoration actions that emerge from the PDA framework allows decision-makers to achieve higher environmental benefits, with equal or lower costs, than those achievable by adopting the myopic prescriptions of the MCDA model. The analytic framework presented here is generalizable for the selection of optimal management plans in any ecosystem where human use of the environment conflicts with the needs of

  8. Integrated Environmental Modelling: Human decisions, human challenges

    Science.gov (United States)

    Glynn, Pierre D.

    2015-01-01

    Integrated Environmental Modelling (IEM) is an invaluable tool for understanding the complex, dynamic ecosystems that house our natural resources and control our environments. Human behaviour affects the ways in which the science of IEM is assembled and used for meaningful societal applications. In particular, human biases and heuristics reflect adaptation and experiential learning to issues with frequent, sharply distinguished, feedbacks. Unfortunately, human behaviour is not adapted to the more diffusely experienced problems that IEM typically seeks to address. Twelve biases are identified that affect IEM (and science in general). These biases are supported by personal observations and by the findings of behavioural scientists. A process for critical analysis is proposed that addresses some human challenges of IEM and solicits explicit description of (1) represented processes and information, (2) unrepresented processes and information, and (3) accounting for, and cognizance of, potential human biases. Several other suggestions are also made that generally complement maintaining attitudes of watchful humility, open-mindedness, honesty and transparent accountability. These suggestions include (1) creating a new area of study in the behavioural biogeosciences, (2) using structured processes for engaging the modelling and stakeholder communities in IEM, and (3) using ‘red teams’ to increase resilience of IEM constructs and use.

  9. Decision making analysis of walnut seedling production on a small ...

    African Journals Online (AJOL)

    The decision has to be made between those three alternatives aiming at achievement of optimal/best economic result for the family farm. Summarizing results obtained from the decision tree, simulation and sensitivity analysis, the optimal solution for the family farm should be to continue production of walnut seedlings with ...

  10. Household consumption, female employment and fertility decisions; A microeconometric analysis

    NARCIS (Netherlands)

    Kalwij, A.S.

    1999-01-01

    This thesis is mainly concerned with a simultaneous analysis of the economic determinants of female employment and fertility decisions on a household level in the Netherlands. In particular, this thesis is interested in the role of the employment decisions of women in the observed behavior that

  11. Decision Analysis of Dynamic Spectrum Access Rules

    Energy Technology Data Exchange (ETDEWEB)

    Juan D. Deaton; Luiz A. DaSilva; Christian Wernz

    2011-12-01

    A current trend in spectrum regulation is to incorporate spectrum sharing through the design of spectrum access rules that support Dynamic Spectrum Access (DSA). This paper develops a decision-theoretic framework for regulators to assess the impacts of different decision rules on both primary and secondary operators. We analyze access rules based on sensing and exclusion areas, which in practice can be enforced through geolocation databases. Our results show that receiver-only sensing provides insufficient protection for primary and co-existing secondary users and overall low social welfare. On the other hand, using sensing information between the transmitter and receiver of a communication link, provides dramatic increases in system performance. The performance of using these link end points is relatively close to that of using many cooperative sensing nodes associated to the same access point and large link exclusion areas. These results are useful to regulators and network developers in understanding in developing rules for future DSA regulation.

  12. PATIENT-CENTERED DECISION MAKING: LESSONS FROM MULTI-CRITERIA DECISION ANALYSIS FOR QUANTIFYING PATIENT PREFERENCES.

    Science.gov (United States)

    Marsh, Kevin; Caro, J Jaime; Zaiser, Erica; Heywood, James; Hamed, Alaa

    2018-01-01

    Patient preferences should be a central consideration in healthcare decision making. However, stories of patients challenging regulatory and reimbursement decisions has led to questions on whether patient voices are being considered sufficiently during those decision making processes. This has led some to argue that it is necessary to quantify patient preferences before they can be adequately considered. This study considers the lessons from the use of multi-criteria decision analysis (MCDA) for efforts to quantify patient preferences. It defines MCDA and summarizes the benefits it can provide to decision makers, identifies examples of MCDAs that have involved patients, and summarizes good practice guidelines as they relate to quantifying patient preferences. The guidance developed to support the use of MCDA in healthcare provide some useful considerations for the quantification of patient preferences, namely that researchers should give appropriate consideration to: the heterogeneity of patient preferences, and its relevance to decision makers; the cognitive challenges posed by different elicitation methods; and validity of the results they produce. Furthermore, it is important to consider how the relevance of these considerations varies with the decision being supported. The MCDA literature holds important lessons for how patient preferences should be quantified to support healthcare decision making.

  13. IT investment decision making : Usability of a normative model

    NARCIS (Netherlands)

    Wijnhoven, Alphonsus B.J.M.; Heerkens, Johannes M.G.

    This article analyzes the usability of a multi-criteria decision analysis based on a real options AHP (ROAHP) method for IT-investment decisions. The study presents ROAHP to Chief Information Officers (CIO’s) and collects their opinions on prerequisites for usability, strengths and weaknesses. To

  14. Parametric vs. Nonparametric Regression Modelling within Clinical Decision Support

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan; Zvárová, Jana

    2017-01-01

    Roč. 5, č. 1 (2017), s. 21-27 ISSN 1805-8698 R&D Projects: GA ČR GA17-01251S Institutional support: RVO:67985807 Keywords : decision support systems * decision rules * statistical analysis * nonparametric regression Subject RIV: IN - Informatics, Computer Science OBOR OECD: Statistics and probability

  15. A Signal Detection Model of Compound Decision Tasks

    Science.gov (United States)

    2006-12-01

    strict isolation (for many examples of such models see Egan, 1975; Macmillan & Creelman , 1991). The result has been twofold: A rich corpus of decision...Macmillan & Creelman , 1991). It is important to point out that SDT models are primarily decision models. They specify the rules and procedures for how...Broadbent, 1958; Macmillan & Creelman , 1991; Nolte & Jaarsma, 1967; Swensson & Judy, 1981; Tanner & Norman, 1954). To better understand how these two

  16. 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.

  17. Using the Logistic Regression model in supporting decisions of establishing marketing strategies

    Directory of Open Access Journals (Sweden)

    Cristinel CONSTANTIN

    2015-12-01

    Full Text Available This paper is about an instrumental research regarding the using of Logistic Regression model for data analysis in marketing research. The decision makers inside different organisation need relevant information to support their decisions regarding the marketing strategies. The data provided by marketing research could be computed in various ways but the multivariate data analysis models can enhance the utility of the information. Among these models we can find the Logistic Regression model, which is used for dichotomous variables. Our research is based on explanation the utility of this model and interpretation of the resulted information in order to help practitioners and researchers to use it in their future investigations

  18. Microsimulation Modeling for Health Decision Sciences Using R: A Tutorial.

    Science.gov (United States)

    Krijkamp, Eline M; Alarid-Escudero, Fernando; Enns, Eva A; Jalal, Hawre J; Hunink, M G Myriam; Pechlivanoglou, Petros

    2018-04-01

    Microsimulation models are becoming increasingly common in the field of decision modeling for health. Because microsimulation models are computationally more demanding than traditional Markov cohort models, the use of computer programming languages in their development has become more common. R is a programming language that has gained recognition within the field of decision modeling. It has the capacity to perform microsimulation models more efficiently than software commonly used for decision modeling, incorporate statistical analyses within decision models, and produce more transparent models and reproducible results. However, no clear guidance for the implementation of microsimulation models in R exists. In this tutorial, we provide a step-by-step guide to build microsimulation models in R and illustrate the use of this guide on a simple, but transferable, hypothetical decision problem. We guide the reader through the necessary steps and provide generic R code that is flexible and can be adapted for other models. We also show how this code can be extended to address more complex model structures and provide an efficient microsimulation approach that relies on vectorization solutions.

  19. Ethnographic Decision Tree Modeling: A Research Method for Counseling Psychology.

    Science.gov (United States)

    Beck, Kirk A.

    2005-01-01

    This article describes ethnographic decision tree modeling (EDTM; C. H. Gladwin, 1989) as a mixed method design appropriate for counseling psychology research. EDTM is introduced and located within a postpositivist research paradigm. Decision theory that informs EDTM is reviewed, and the 2 phases of EDTM are highlighted. The 1st phase, model…

  20. A decision-making model for engineering designers

    DEFF Research Database (Denmark)

    Ahmed, S.; Hansen, Claus Thorp

    2002-01-01

    This paper describes research that combines the generic decision-making model of Hansen, together with design strategies employed by experienced engineering designers. The relationship between the six decision-making sub-activities and the eight design strategies are examined. By combining...

  1. Introductie Decision Model and Notation (DMN) : Deel 1

    NARCIS (Netherlands)

    dr. Martijn Zoet; Koen Smit

    2017-01-01

    Sinds september 2015 is de ‘business rule management wereld’ / ‘decision management wereld’ weer een standaard rijker: The Decision Model and Notation (DMN). De Object Management Group (OMG) heeft deze nieuwe standaard uitgebracht met als doel een standaard taal te creëren om 1) requirements voor

  2. Introductie Decision Model and Notation (DMN) : Deel 2

    NARCIS (Netherlands)

    dr. Martijn Zoet; Koen Smit

    2017-01-01

    Sinds september 2015 is de ‘business rule management wereld’ / ‘decision management wereld’ weer een standaard rijker: The Decision Model and Notation (DMN). De Object Management Group (OMG) heeft deze nieuwe standaard uitgebracht met als doel een standaard taal te creëren om 1) requirements voor

  3. Introductie Decision Model and Notation (DMN) : Deel 3

    NARCIS (Netherlands)

    dr. Martijn Zoet; Koen Smit

    2017-01-01

    Sinds september 2015 is de ‘business rule management wereld’ / ‘decision management wereld’ weer een standaard rijker: The Decision Model and Notation (DMN). De Object Management Group (OMG) heeft deze nieuwe standaard uitgebracht met als doel een standaardtaal te creëren om 1) requirements voor

  4. An Evaluation on Factors Influencing Decision making for Malaysia Disaster Management: The Confirmatory Factor Analysis Approach

    Science.gov (United States)

    Zubir, S. N. A.; Thiruchelvam, S.; Mustapha, K. N. M.; Che Muda, Z.; Ghazali, A.; Hakimie, H.

    2017-12-01

    For the past few years, natural disaster has been the subject of debate in disaster management especially in flood disaster. Each year, natural disaster results in significant loss of life, destruction of homes and public infrastructure, and economic hardship. Hence, an effective and efficient flood disaster management would assure non-futile efforts for life saving. The aim of this article is to examine the relationship between approach, decision maker, influence factor, result, and ethic to decision making for flood disaster management in Malaysia. The key elements of decision making in the disaster management were studied based on the literature. Questionnaire surveys were administered among lead agencies at East Coast of Malaysia in the state of Kelantan and Pahang. A total of 307 valid responses had been obtained for further analysis. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were carried out to analyse the measurement model involved in the study. The CFA for second-order reflective and first-order reflective measurement model indicates that approach, decision maker, influence factor, result, and ethic have a significant and direct effect on decision making during disaster. The results from this study showed that decision- making during disaster is an important element for disaster management to necessitate a successful collaborative decision making. The measurement model is accepted to proceed with further analysis known as Structural Equation Modeling (SEM) and can be assessed for the future research.

  5. Hesitant fuzzy methods for multiple criteria decision analysis

    CERN Document Server

    Zhang, Xiaolu

    2017-01-01

    The book offers a comprehensive introduction to methods for solving multiple criteria decision making and group decision making problems with hesitant fuzzy information. It reports on the authors’ latest research, as well as on others’ research, providing readers with a complete set of decision making tools, such as hesitant fuzzy TOPSIS, hesitant fuzzy TODIM, hesitant fuzzy LINMAP, hesitant fuzzy QUALIFEX, and the deviation modeling approach with heterogeneous fuzzy information. The main focus is on decision making problems in which the criteria values and/or the weights of criteria are not expressed in crisp numbers but are more suitable to be denoted as hesitant fuzzy elements. The largest part of the book is devoted to new methods recently developed by the authors to solve decision making problems in situations where the available information is vague or hesitant. These methods are presented in detail, together with their application to different type of decision-making problems. All in all, the book ...

  6. A spiral model of musical decision-making.

    Science.gov (United States)

    Bangert, Daniel; Schubert, Emery; Fabian, Dorottya

    2014-01-01

    This paper describes a model of how musicians make decisions about performing notated music. The model builds on psychological theories of decision-making and was developed from empirical studies of Western art music performance that aimed to identify intuitive and deliberate processes of decision-making, a distinction consistent with dual-process theories of cognition. The model proposes that the proportion of intuitive (Type 1) and deliberate (Type 2) decision-making processes changes with increasing expertise and conceptualizes this change as movement along a continually narrowing upward spiral where the primary axis signifies principal decision-making type and the vertical axis marks level of expertise. The model is intended to have implications for the development of expertise as described in two main phases. The first is movement from a primarily intuitive approach in the early stages of learning toward greater deliberation as analytical techniques are applied during practice. The second phase occurs as deliberate decisions gradually become automatic (procedural), increasing the role of intuitive processes. As a performer examines more issues or reconsiders decisions, the spiral motion toward the deliberate side and back to the intuitive is repeated indefinitely. With increasing expertise, the spiral tightens to signify greater control over decision type selection. The model draws on existing theories, particularly Evans' (2011) Intervention Model of dual-process theories, Cognitive Continuum Theory Hammond et al. (1987), Hammond (2007), Baylor's (2001) U-shaped model for the development of intuition by level of expertise. By theorizing how musical decision-making operates over time and with increasing expertise, this model could be used as a framework for future research in music performance studies and performance science more generally.

  7. A spiral model of musical decision-making

    Directory of Open Access Journals (Sweden)

    Daniel eBangert

    2014-04-01

    Full Text Available This paper describes a model of how musicians make decisions about performing notated music. The model builds on psychological theories of decision-making and was developed from empirical studies of Western art music performance that aimed to identify intuitive and deliberate processes of decision-making, a distinction consistent with dual-process theories of cognition. The model proposes that the proportion of intuitive (Type 1 and deliberate (Type 2 decision-making processes changes with increasing expertise and conceptualises this change as movement along a continually narrowing upward spiral where the primary axis signifies principal decision-making type and the vertical axis marks level of expertise. The model is intended to have implications for the development of expertise as described in two main phases. The first is movement from a primarily intuitive approach in the early stages of learning towards greater deliberation as analytical techniques are applied during practice. The second phase occurs as deliberate decisions gradually become automatic (procedural, increasing the role of intuitive processes. As a performer examines more issues or reconsiders decisions, the spiral motion towards the deliberate side and back to the intuitive is repeated indefinitely. With increasing expertise, the spiral tightens to signify greater control over decision type selection. The model draws on existing theories, particularly Evans’ (2011 Intervention Model of dual-process theories, Cognitive Continuum Theory (Hammond et al., 1987; Hammond, 2007, and Baylor’s (2001 U-shaped model for the development of intuition by level of expertise. By theorising how musical decision-making operates over time and with increasing expertise, this model could be used as a framework for future research in music performance studies and performance science more generally.

  8. Integrating Design Decision Management with Model-based Software Development

    DEFF Research Database (Denmark)

    Könemann, Patrick

    Design decisions are continuously made during the development of software systems and are important artifacts for design documentation. Dedicated decision management systems are often used to capture such design knowledge. Most such systems are, however, separated from the design artifacts...... of the system. In model-based software development, where design models are used to develop a software system, outcomes of many design decisions have big impact on design models. The realization of design decisions is often manual and tedious work on design models. Moreover, keeping design models consistent......, or by ignoring the causes. This substitutes manual reviews to some extent. The concepts, implemented in a tool, have been validated with design patterns, refactorings, and domain level tests that comprise a replay of a real project. This proves the applicability of the solution to realistic examples...

  9. Modular Architecture for Integrated Model-Based Decision Support.

    Science.gov (United States)

    Gaebel, Jan; Schreiber, Erik; Oeser, Alexander; Oeltze-Jafra, Steffen

    2018-01-01

    Model-based decision support systems promise to be a valuable addition to oncological treatments and the implementation of personalized therapies. For the integration and sharing of decision models, the involved systems must be able to communicate with each other. In this paper, we propose a modularized architecture of dedicated systems for the integration of probabilistic decision models into existing hospital environments. These systems interconnect via web services and provide model sharing and processing capabilities for clinical information systems. Along the lines of IHE integration profiles from other disciplines and the meaningful reuse of routinely recorded patient data, our approach aims for the seamless integration of decision models into hospital infrastructure and the physicians' daily work.

  10. Assumptions and Policy Decisions for Vital Area Identification Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Myungsu; Bae, Yeon-Kyoung; Lee, Youngseung [KHNP CRI, Daejeon (Korea, Republic of)

    2016-10-15

    U.S. Nuclear Regulatory Commission and IAEA guidance indicate that certain assumptions and policy questions should be addressed to a Vital Area Identification (VAI) process. Korea Hydro and Nuclear Power conducted a VAI based on current Design Basis Threat and engineering judgement to identify APR1400 vital areas. Some of the assumptions were inherited from Probabilistic Safety Assessment (PSA) as a sabotage logic model was based on PSA logic tree and equipment location data. This paper illustrates some important assumptions and policy decisions for APR1400 VAI analysis. Assumptions and policy decisions could be overlooked at the beginning stage of VAI, however they should be carefully reviewed and discussed among engineers, plant operators, and regulators. Through APR1400 VAI process, some of the policy concerns and assumptions for analysis were applied based on document research and expert panel discussions. It was also found that there are more assumptions to define for further studies for other types of nuclear power plants. One of the assumptions is mission time, which was inherited from PSA.

  11. ANALYSIS AND COMPARISON OF EXISTING DECISION SUPPORT TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    V. A. Rybak

    2016-01-01

    Full Text Available The article presents the results of an analytical review and comparison of the most common managerial decision support technologies: the analytic hierarchy method, neural networks, fuzzy set theory, genetic algorithms and neural-fuzzy modeling. The advantages and disadvantages of these approaches are shown. Determine the scope of their application. It is shown that the hierarchy analysis method works well with the full initial information, but due to the need for expert comparison of alternatives and the selection of evaluation criteria has a high proportion of subjectivity. For problems in the conditions of risk and uncertainty prediction seems reasonable use of the theory of fuzzy sets and neural networks. It is also considered technology collective decision applied both in the general election, and the group of experts. It reduces the time for conciliation meetings to reach a consensus by the preliminary analysis of all views submitted for the plane in the form of points. At the same time the consistency of opinion is determined by the distance between them.

  12. Licensing method for new nuclear power plant: A study on decision making modeling

    International Nuclear Information System (INIS)

    Ramli, N; Ohaga, E. O.; Jung, J. C.

    2012-01-01

    This work provides a study on decision making modeling for a licensing method of a new nuclear power plant. SWOT analysis provides the licensing alternatives attributes, then the expectation from either COL or two step licensing method is decided by inputting the output from the Hurwitz mathematical model. From the analysis, COL shows the best candidate for both optimistic and pessimistic conditions

  13. Licensing method for new nuclear power plant: A study on decision making modeling

    Energy Technology Data Exchange (ETDEWEB)

    Ramli, N; Ohaga, E. O.; Jung, J. C. [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

    2012-10-15

    This work provides a study on decision making modeling for a licensing method of a new nuclear power plant. SWOT analysis provides the licensing alternatives attributes, then the expectation from either COL or two step licensing method is decided by inputting the output from the Hurwitz mathematical model. From the analysis, COL shows the best candidate for both optimistic and pessimistic conditions.

  14. Model Driven Integrated Decision-Making in Manufacturing Enterprises

    Directory of Open Access Journals (Sweden)

    Richard H. Weston

    2012-01-01

    Full Text Available Decision making requirements and solutions are observed in four world class Manufacturing Enterprises (MEs. Observations made focus on deployed methods of complexity handling that facilitate multi-purpose, distributed decision making. Also observed are examples of partially deficient “integrated decision making” which stem from lack of understanding about how ME structural relations enable and/or constrain reachable ME behaviours. To begin to address this deficiency the paper outlines the use of a “reference model of ME decision making” which can inform the structural design of decision making systems in MEs. Also outlined is a “systematic model driven approach to modelling ME systems” which can particularise the reference model in specific case enterprises and thereby can “underpin integrated ME decision making”. Coherent decomposition and representational mechanisms have been incorporated into the model driven approach to systemise complexity handling. The paper also describes in outline an application of the modelling method in a case study ME and explains how its use has improved the integration of previously distinct planning functions. The modelling approach is particularly innovative in respect to the way it structures the coherent creation and experimental re-use of “fit for purpose” discrete event (predictive simulation models at the multiple levels of abstraction.

  15. Uncertainty about probability: a decision analysis perspective

    International Nuclear Information System (INIS)

    Howard, R.A.

    1988-01-01

    The issue of how to think about uncertainty about probability is framed and analyzed from the viewpoint of a decision analyst. The failure of nuclear power plants is used as an example. The key idea is to think of probability as describing a state of information on an uncertain event, and to pose the issue of uncertainty in this quantity as uncertainty about a number that would be definitive: it has the property that you would assign it as the probability if you knew it. Logical consistency requires that the probability to assign to a single occurrence in the absence of further information be the mean of the distribution of this definitive number, not the medium as is sometimes suggested. Any decision that must be made without the benefit of further information must also be made using the mean of the definitive number's distribution. With this formulation, they find further that the probability of r occurrences in n exchangeable trials will depend on the first n moments of the definitive number's distribution. In making decisions, the expected value of clairvoyance on the occurrence of the event must be at least as great as that on the definitive number. If one of the events in question occurs, then the increase in probability of another such event is readily computed. This means, in terms of coin tossing, that unless one is absolutely sure of the fairness of a coin, seeing a head must increase the probability of heads, in distinction to usual thought. A numerical example for nuclear power shows that the failure of one plant of a group with a low probability of failure can significantly increase the probability that must be assigned to failure of a second plant in the group

  16. ANALISIS IKLAN SIMPATI DENGAN MENGGUNAKAN CONSUMER DECISION MODEL

    Directory of Open Access Journals (Sweden)

    Reni Shinta Dewi

    2016-02-01

    Full Text Available In order that position of a brand always engage in the mind of consumers, the company does not only act positioning strategy, but they have to give the right information about their product, and advertising on the television is one of the most effective promotion media. The main reaction of advertisement is purchase, but it’s happened in the end of the long process before the consumer makes their decision. Usually the effect of advertising communication is to measure the awareness, knowledge, preference and confidence. One of model can be used to measure the advertising effectiveness is Consumer Decision Model (CMD by Howard, Shay and Green. The findings indicated that information, brand recognition, attitude, and confidence are identified as intervening variable which can strongly effect information to customer’s intention. Structural analysis seen that the biggest influence to intention shown by variable of advertisement message through attitude and confidence. The ability of advertisement to create attitude and confidence which supporting a product oftentimes hinging to consumer’s attitude and confidence to advertisement itself. The advertisement which evaluated better can yield positive attitude to product. Even sometimes, that unwelcome advertisement can succeed. This matter happens because the advertisement schema is salience in consumer’s view. The fact said that attitude developed by brand is more difficult than customer’s confidence. To create consumer’s attitude which is direct to consumer’s intention, continuity and intensity of commercials are recommended.

  17. Computer analysis of the exercise electrocardiogram and control of radionuclide ventriculography: an optimal statistical decision model for diagnosis of coronary artery disease

    International Nuclear Information System (INIS)

    Hsia, P.W.E.

    1987-01-01

    A new automated technique for the diagnosis of coronary artery disease (CAD) by stress electrocardiography and radionuclide ventriculography (RNV) has been developed. The method employs digital signal processing of the electrocardiogram (ECG) for recognition of ischemic and arrhythmic events. On-line detection of abnormal beats is used for control image acquisition by the gamma camera resulting in improved image quality since only identical beats are included in the composite images of the cardiac cycle. A combined stress ECG analysis which measures ST changes indicative of ischemia, and radionuclide results, which reveal corresponding ejection fraction abnormalities yields greater sensitivity and specificity than either test alone. Digitized data from the electrocardiogram are analyzed in a beat-by-beat mode and a contextual diagnosis of underlying rhythm is given. Template generation, R wave detection, QRS window size, baseline correction, and continuous updating of heart rate are completely automated. A statistical model base on computerized ST segment measurements combined with radionuclide ventriculography data has been developed by using a logistic model with stepwise regression fitting. A previously acquired database of similar measurements was used for designing the model. The most significant parameters were found to be (1) ejection fraction of exercise RNV; (2) difference of ST level between exercise and resting test (stdif); and (3) ejection fraction difference between exercise and resting test. The new parameter stdif, not previously used in ECG interpretation, was found to be of great diagnostic significance

  18. Decision support models for solid waste management: Review and game-theoretic approaches

    International Nuclear Information System (INIS)

    Karmperis, Athanasios C.; Aravossis, Konstantinos; Tatsiopoulos, Ilias P.; Sotirchos, Anastasios

    2013-01-01

    Highlights: ► The mainly used decision support frameworks for solid waste management are reviewed. ► The LCA, CBA and MCDM models are presented and their strengths, weaknesses, similarities and possible combinations are analyzed. ► The game-theoretic approach in a solid waste management context is presented. ► The waste management bargaining game is introduced as a specific decision support framework. ► Cooperative and non-cooperative game-theoretic approaches to decision support for solid waste management are discussed. - Abstract: This paper surveys decision support models that are commonly used in the solid waste management area. Most models are mainly developed within three decision support frameworks, which are the life-cycle assessment, the cost–benefit analysis and the multi-criteria decision-making. These frameworks are reviewed and their strengths and weaknesses as well as their critical issues are analyzed, while their possible combinations and extensions are also discussed. Furthermore, the paper presents how cooperative and non-cooperative game-theoretic approaches can be used for the purpose of modeling and analyzing decision-making in situations with multiple stakeholders. Specifically, since a waste management model is sustainable when considering not only environmental and economic but also social aspects, the waste management bargaining game is introduced as a specific decision support framework in which future models can be developed

  19. Decision support models for solid waste management: Review and game-theoretic approaches

    Energy Technology Data Exchange (ETDEWEB)

    Karmperis, Athanasios C., E-mail: athkarmp@mail.ntua.gr [Sector of Industrial Management and Operational Research, School of Mechanical Engineering, National Technical University of Athens, Iroon Polytechniou 9, 15780 Athens (Greece); Army Corps of Engineers, Hellenic Army General Staff, Ministry of Defence (Greece); Aravossis, Konstantinos; Tatsiopoulos, Ilias P.; Sotirchos, Anastasios [Sector of Industrial Management and Operational Research, School of Mechanical Engineering, National Technical University of Athens, Iroon Polytechniou 9, 15780 Athens (Greece)

    2013-05-15

    Highlights: ► The mainly used decision support frameworks for solid waste management are reviewed. ► The LCA, CBA and MCDM models are presented and their strengths, weaknesses, similarities and possible combinations are analyzed. ► The game-theoretic approach in a solid waste management context is presented. ► The waste management bargaining game is introduced as a specific decision support framework. ► Cooperative and non-cooperative game-theoretic approaches to decision support for solid waste management are discussed. - Abstract: This paper surveys decision support models that are commonly used in the solid waste management area. Most models are mainly developed within three decision support frameworks, which are the life-cycle assessment, the cost–benefit analysis and the multi-criteria decision-making. These frameworks are reviewed and their strengths and weaknesses as well as their critical issues are analyzed, while their possible combinations and extensions are also discussed. Furthermore, the paper presents how cooperative and non-cooperative game-theoretic approaches can be used for the purpose of modeling and analyzing decision-making in situations with multiple stakeholders. Specifically, since a waste management model is sustainable when considering not only environmental and economic but also social aspects, the waste management bargaining game is introduced as a specific decision support framework in which future models can be developed.

  20. Decoding Problem Gamblers' Signals: A Decision Model for Casino Enterprises.

    Science.gov (United States)

    Ifrim, Sandra

    2015-12-01

    The aim of the present study is to offer a validated decision model for casino enterprises. The model enables those users to perform early detection of problem gamblers and fulfill their ethical duty of social cost minimization. To this end, the interpretation of casino customers' nonverbal communication is understood as a signal-processing problem. Indicators of problem gambling recommended by Delfabbro et al. (Identifying problem gamblers in gambling venues: final report, 2007) are combined with Viterbi algorithm into an interdisciplinary model that helps decoding signals emitted by casino customers. Model output consists of a historical path of mental states and cumulated social costs associated with a particular client. Groups of problem and non-problem gamblers were simulated to investigate the model's diagnostic capability and its cost minimization ability. Each group consisted of 26 subjects and was subsequently enlarged to 100 subjects. In approximately 95% of the cases, mental states were correctly decoded for problem gamblers. Statistical analysis using planned contrasts revealed that the model is relatively robust to the suppression of signals performed by casino clientele facing gambling problems as well as to misjudgments made by staff regarding the clients' mental states. Only if the last mentioned source of error occurs in a very pronounced manner, i.e. judgment is extremely faulty, cumulated social costs might be distorted.

  1. A decision analysis of an exploratory studies facility

    International Nuclear Information System (INIS)

    Merkhofer, M.W.; Gnirk, P.

    1991-01-01

    An Exploratory Studies Facility (ESF) is planned to support the characterization of a potential site for a high-level nuclear waste repository at Yucca Mountain, NV. The selection of a design for the ESF is a critical decision, because the ESF design may affect the accuracy of characterization testing and subsequent repository design. The assist the design process, a comparative evaluation was conducted to rank 34 alternative relied on techniques from formal decision analysis, including decision trees and multiattribute utility analysis (MUA). The results helped to identify favorable design features and convinced the Department of Energy to adopt the top-ranked option as the preferred ESF design

  2. A Decision Support Model and Tool to Assist Financial Decision-Making in Universities

    Science.gov (United States)

    Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive

    2015-01-01

    In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…

  3. Cognitive processes, models and metaphors in decision research

    Directory of Open Access Journals (Sweden)

    Ben Newell

    2008-03-01

    Full Text Available Decision research in psychology has traditionally been influenced by the extit{homo oeconomicus} metaphor with its emphasis on normative models and deviations from the predictions of those models. In contrast, the principal metaphor of cognitive psychology conceptualizes humans as `information processors', employing processes of perception, memory, categorization, problem solving and so on. Many of the processes described in cognitive theories are similar to those involved in decision making, and thus increasing cross-fertilization between the two areas is an important endeavour. A wide range of models and metaphors has been proposed to explain and describe `information processing' and many models have been applied to decision making in ingenious ways. This special issue encourages cross-fertilization between cognitive psychology and decision research by providing an overview of current perspectives in one area that continues to highlight the benefits of the synergistic approach: cognitive modeling of multi-attribute decision making. In this introduction we discuss aspects of the cognitive system that need to be considered when modeling multi-attribute decision making (e.g., automatic versus controlled processing, learning and memory constraints, metacognition and illustrate how such aspects are incorporated into the approaches proposed by contributors to the special issue. We end by discussing the challenges posed by the contrasting and sometimes incompatible assumptions of the models and metaphors.

  4. Spreadsheet Decision Support Model for Training Exercise Material Requirements Planning

    National Research Council Canada - National Science Library

    Tringali, Arthur

    1997-01-01

    This thesis focuses on developing a spreadsheet decision support model that can be used by combat engineer platoon and company commanders in determining the material requirements and estimated costs...

  5. Optimization for decision making linear and quadratic models

    CERN Document Server

    Murty, Katta G

    2010-01-01

    While maintaining the rigorous linear programming instruction required, Murty's new book is unique in its focus on developing modeling skills to support valid decision-making for complex real world problems, and includes solutions to brand new algorithms.

  6. Research of Strategic Alliance Stable Decision-making Model Based on Rough Set and DEA

    OpenAIRE

    Zhang Yi

    2013-01-01

    This article uses rough set theory for stability evaluation system of strategic alliance at first. Uses data analysis method for reduction, eliminates redundant indexes. Selected 6 enterprises as a decision-making unit, then select 4 inputs and 2 outputs indexes data, using DEA model to calculate, analysis reasons for poor benefit of decision-making unit, find out improvement direction and quantity for changing, provide a reference for the alliance stability.

  7. Ethics and rationality in information-enriched decisions: A model for technical communication

    Science.gov (United States)

    Dressel, S. B.; Carlson, P.; Killingsworth, M. J.

    1993-12-01

    In a technological culture, information has a crucial impact upon decisions, but exactly how information plays into decisions is not always clear. Decisions that are effective, efficient, and ethical must be rational. That is, we must be able to determine and present good reasons for our actions. The topic in this paper is how information relates to good reasons and thereby affects the best decisions. A brief sketch of a model for decision-making, is presented which offers a synthesis of theoretical approaches to argument and to information analysis. Then the model is applied to a brief hypothetical case. The main purpose is to put the model before an interested audience in hopes of stimulating discussion and further research.

  8. Pharmaceutical expenditure forecast model to support health policy decision making

    OpenAIRE

    R?muzat, C?cile; Urbinati, Duccio; Kornfeld, ?sa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aball?a, Samuel; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    Background and objective: With constant incentives for healthcare payers to contain their pharmaceutical budgets, modelling policy decision impact became critical. The objective of this project was to test the impact of various policy decisions on pharmaceutical budget (developed for the European Commission for the project ‘European Union (EU) Pharmaceutical expenditure forecast’ – http://ec.europa.eu/health/healthcare/key_documents/index_en.htm).Methods: A model was built to assess policy sc...

  9. Dual processing model of medical decision-making

    OpenAIRE

    Djulbegovic, Benjamin; Hozo, Iztok; Beckstead, Jason; Tsalatsanis, Athanasios; Pauker, Stephen G

    2012-01-01

    Abstract Background Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administe...

  10. Decision Making under Uncertainty: A Neural Model based on Partially Observable Markov Decision Processes

    Directory of Open Access Journals (Sweden)

    Rajesh P N Rao

    2010-11-01

    Full Text Available A fundamental problem faced by animals is learning to select actions based on noisy sensory information and incomplete knowledge of the world. It has been suggested that the brain engages in Bayesian inference during perception but how such probabilistic representations are used to select actions has remained unclear. Here we propose a neural model of action selection and decision making based on the theory of partially observable Markov decision processes (POMDPs. Actions are selected based not on a single optimal estimate of state but on the posterior distribution over states (the belief state. We show how such a model provides a unified framework for explaining experimental results in decision making that involve both information gathering and overt actions. The model utilizes temporal difference (TD learning for maximizing expected reward. The resulting neural architecture posits an active role for the neocortex in belief computation while ascribing a role to the basal ganglia in belief representation, value computation, and action selection. When applied to the random dots motion discrimination task, model neurons representing belief exhibit responses similar to those of LIP neurons in primate neocortex. The appropriate threshold for switching from information gathering to overt actions emerges naturally during reward maximization. Additionally, the time course of reward prediction error in the model shares similarities with dopaminergic responses in the basal ganglia during the random dots task. For tasks with a deadline, the model learns a decision making strategy that changes with elapsed time, predicting a collapsing decision threshold consistent with some experimental studies. The model provides a new framework for understanding neural decision making and suggests an important role for interactions between the neocortex and the basal ganglia in learning the mapping between probabilistic sensory representations and actions that maximize

  11. An Analysis of Decision Factors on the Price of South Korea’s Certified Emission Reductions in Use of Vector Error Correction Model

    Directory of Open Access Journals (Sweden)

    Sumin Park

    2017-09-01

    Full Text Available This study analyzes factors affecting the price of South Korea’s Certified Emission Reduction (CER using statistical methods. CER refers to the transaction price for the amount of carbon emitted. Analysis of results found a co-integration relationship among the price of South Korea’s CER, oil price (WTI, and South Korea’s maximum electric power demand, which means that there is a long-term relationship among the three variables. Based on this result, VECM (vector error correction model analysis, impulse response function, and variance decomposition were performed. As the oil price (WTI increases, the demand for gas in power generation in Korea declines while the demand for coal increases. This leads to increased greenhouse gas (GHG; e.g., CO2 emissions and increased price of South Korea’s CERs. In addition, rising oil prices (WTI cause a decline in demand for oil products such as kerosene, which results in an increase in South Korea’s maximum power demand.

  12. Decision Analysis for Metric Selection on a Clinical Quality Scorecard.

    Science.gov (United States)

    Guth, Rebecca M; Storey, Patricia E; Vitale, Michael; Markan-Aurora, Sumita; Gordon, Randolph; Prevost, Traci Q; Dunagan, Wm Claiborne; Woeltje, Keith F

    2016-09-01

    Clinical quality scorecards are used by health care institutions to monitor clinical performance and drive quality improvement. Because of the rapid proliferation of quality metrics in health care, BJC HealthCare found it increasingly difficult to select the most impactful scorecard metrics while still monitoring metrics for regulatory purposes. A 7-step measure selection process was implemented incorporating Kepner-Tregoe Decision Analysis, which is a systematic process that considers key criteria that must be satisfied in order to make the best decision. The decision analysis process evaluates what metrics will most appropriately fulfill these criteria, as well as identifies potential risks associated with a particular metric in order to identify threats to its implementation. Using this process, a list of 750 potential metrics was narrowed to 25 that were selected for scorecard inclusion. This decision analysis process created a more transparent, reproducible approach for selecting quality metrics for clinical quality scorecards. © The Author(s) 2015.

  13. A Representation for Gaining Insight into Clinical Decision Models

    Science.gov (United States)

    Jimison, Holly B.

    1988-01-01

    For many medical domains uncertainty and patient preferences are important components of decision making. Decision theory is useful as a representation for such medical models in computer decision aids, but the methodology has typically had poor performance in the areas of explanation and user interface. The additional representation of probabilities and utilities as random variables serves to provide a framework for graphical and text insight into complicated decision models. The approach allows for efficient customization of a generic model that describes the general patient population of interest to a patient- specific model. Monte Carlo simulation is used to calculate the expected value of information and sensitivity for each model variable, thus providing a metric for deciding what to emphasize in the graphics and text summary. The computer-generated explanation includes variables that are sensitive with respect to the decision or that deviate significantly from what is typically observed. These techniques serve to keep the assessment and explanation of the patient's decision model concise, allowing the user to focus on the most important aspects for that patient.

  14. Multi-level decision making models, methods and applications

    CERN Document Server

    Zhang, Guangquan; Gao, Ya

    2015-01-01

    This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.  

  15. Decision modelling tools for utilities in the deregulated energy market

    Energy Technology Data Exchange (ETDEWEB)

    Makkonen, S. [Process Vision Oy, Helsinki (Finland)

    2005-07-01

    This thesis examines the impact of the deregulation of the energy market on decision making and optimisation in utilities and demonstrates how decision support applications can solve specific encountered tasks in this context. The themes of the thesis are presented in different frameworks in order to clarify the complex decision making and optimisation environment where new sources of uncertainties arise due to the convergence of energy markets, globalisation of energy business and increasing competition. This thesis reflects the changes in the decision making and planning environment of European energy companies during the period from 1995 to 2004. It also follows the development of computational performance and evolution of energy information systems during the same period. Specifically, this thesis consists of studies at several levels of the decision making hierarchy ranging from top-level strategic decision problems to specific optimisation algorithms. On the other hand, the studies also follow the progress of the liberalised energy market from the monopolistic era to the fully competitive market with new trading instruments and issues like emissions trading. This thesis suggests that there is an increasing need for optimisation and multiple criteria decision making methods, and that new approaches based on the use of operations research are welcome as the deregulation proceeds and uncertainties increase. Technically, the optimisation applications presented are based on Lagrangian relaxation techniques and the dedicated Power Simplex algorithm supplemented with stochastic scenario analysis for decision support, a heuristic method to allocate common benefits and potential losses of coalitions of power companies, and an advanced Branch- and-Bound algorithm to solve efficiently nonconvex optimisation problems. The optimisation problems are part of the operational and tactical decision making process that has become very complex in the recent years. Similarly

  16. Modeling integrated water user decisions in intermittent supply systems

    Science.gov (United States)

    Rosenberg, David E.; Tarawneh, Tarek; Abdel-Khaleq, Rania; Lund, Jay R.

    2007-07-01

    We apply systems analysis to estimate household water use in an intermittent supply system considering numerous interdependent water user behaviors. Some 39 household actions include conservation; improving local storage or water quality; and accessing sources having variable costs, availabilities, reliabilities, and qualities. A stochastic optimization program with recourse decisions identifies the infrastructure investments and short-term coping actions a customer can adopt to cost-effectively respond to a probability distribution of piped water availability. Monte Carlo simulations show effects for a population of customers. Model calibration reproduces the distribution of billed residential water use in Amman, Jordan. Parametric analyses suggest economic and demand responses to increased availability and alternative pricing. It also suggests potential market penetration for conservation actions, associated water savings, and subsidies to entice further adoption. We discuss new insights to size, target, and finance conservation.

  17. Distributed Hydrologic Modeling Apps for Decision Support in the Cloud

    Science.gov (United States)

    Swain, N. R.; Latu, K.; Christiensen, S.; Jones, N.; Nelson, J.

    2013-12-01

    Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it

  18. A generic methodology for developing fuzzy decision models

    NARCIS (Netherlands)

    Bosma, R.; Berg, van den J.; Kaymak, U.; Udo, H.; Verreth, J.

    2012-01-01

    An important paradigm in decision-making models is utility-maximization where most models do not include actors’ motives. Fuzzy set theory on the other hand offers a method to simulate human decisionmaking. However, the literature describing expert-driven fuzzy logic models, rarely gives precise

  19. Building models for marketing decisions : Past, present and future

    NARCIS (Netherlands)

    Leeflang, PSH; Wittink, DR

    We review five eras of model building in marketing, with special emphasis on the fourth and the fifth eras, the present and the future. At many firms managers now routinely use model-based results for marketing decisions. Given an increasing number of successful applications, the demand for models

  20. Modelling the Role of Cognitive Metaphors in Joint Decision Making

    NARCIS (Netherlands)

    van Ments, L.; Thilakarathne, D.J.; Treur, J.

    2016-01-01

    In this paper, a social agent model is presented for the influence of cognitive metaphors on joint decision making processes. The social agent model is based on mechanisms known from cognitive and social neuroscience and cognitive metaphor theory. The model was illustrated in particular for two

  1. Personalized prophylactic anticoagulation decision analysis in patients with membranous nephropathy

    Science.gov (United States)

    Lee, Taewoo; Biddle, Andrea K.; Lionaki, Sofia; Derebail, Vimal K.; Barbour, Sean J.; Tannous, Sameer; Hladunewich, Michelle A.; Hu, Yichun; Poulton, Caroline J.; Mahoney, Shannon L.; Jennette, J. Charles; Hogan, Susan L.; Falk, Ronald J.; Cattran, Daniel C.; Reich, Heather N.; Nachman, Patrick H.

    2014-01-01

    Primary membranous nephropathy is associated with increased risk of venous thromboembolic events, which are inversely correlated with serum albumin levels. To evaluate the potential benefit of prophylactic anticoagulation (venous thromboembolic events prevented) relative to the risk (major bleeds), we constructed a Markov decision model. The venous thromboembolic event risk according to serum albumin was obtained from an inception cohort of 898 patients with primary membranous nephropathy. Risk estimates of hemorrhage were obtained from a systematic literature review. Benefit-to-risk ratios were predicted according to bleeding risk and serum albumin. This ratio increased with worsening hypoalbuminemia from 4.5:1 for an albumin under 3 g/dl to 13.1:1 for an albumin under 2 g/dl in patients at low bleeding risk. Patients at intermediate bleeding risk with an albumin under 2 g/dl have a moderately favorable benefit-to-risk ratio (under 5:1). Patients at high bleeding risk are unlikely to benefit from prophylactic anticoagulation regardless of albuminemia. Probabilistic sensitivity analysis, to account for uncertainty in risk estimates, confirmed these trends. From these data, we constructed a tool to estimate the likelihood of benefit based on an individual’s bleeding risk profile, serum albumin level, and acceptable benefit-to-risk ratio (http://www.gntools.com). This tool provides an approach to the decision of prophylactic anticoagulation personalized to the individual’s needs and adaptable to dynamic changes in health status and risk profile. PMID:24336031

  2. An evolutionary behavioral model for decision making

    OpenAIRE

    Romero Lopez, Dr Oscar Javier

    2011-01-01

    For autonomous agents the problem of deciding what to do next becomes increasingly complex when acting in unpredictable and dynamic environments pursuing multiple and possibly conflicting goals. One of the most relevant behavior-based model that tries to deal with this problem is the one proposed by Maes, the Bbehavior Network model. This model proposes a set of behaviors as purposive perception-action units which are linked in a nonhierarchical network, and whose behavior selection process i...

  3. Decision analysis for the selection of tank waste retrieval technology

    International Nuclear Information System (INIS)

    DAVIS, FREDDIE J.; DEWEESE, GREGORY C.; PICKETT, WILLIAM W.

    2000-01-01

    The objective of this report is to supplement the C-104 Alternatives Generation and Analysis (AGA) by providing a decision analysis for the alternative technologies described therein. The decision analysis used the Multi-Attribute Utility Analysis (MUA) technique. To the extent possible information will come from the AGA. Where data are not available, elicitation of expert opinion or engineering judgment is used and reviewed by the authors of the AGA. A key element of this particular analysis is the consideration of varying perspectives of parties interested in or affected by the decision. The six alternatives discussed are: sluicing; sluicing with vehicle mounted transfer pump; borehole mining; vehicle with attached sluicing nozzle and pump; articulated arm with attached sluicing nozzle; and mechanical dry retrieval. These are evaluated using four attributes, namely: schedule, cost, environmental impact, and safety

  4. Do violations of the axioms of expected utility theory threaten decision analysis?

    Science.gov (United States)

    Nease, R F

    1996-01-01

    Research demonstrates that people violate the independence principle of expected utility theory, raising the question of whether expected utility theory is normative for medical decision making. The author provides three arguments that violations of the independence principle are less problematic than they might first appear. First, the independence principle follows from other more fundamental axioms whose appeal may be more readily apparent than that of the independence principle. Second, the axioms need not be descriptive to be normative, and they need not be attractive to all decision makers for expected utility theory to be useful for some. Finally, by providing a metaphor of decision analysis as a conversation between the actual decision maker and a model decision maker, the author argues that expected utility theory need not be purely normative for decision analysis to be useful. In short, violations of the independence principle do not necessarily represent direct violations of the axioms of expected utility theory; behavioral violations of the axioms of expected utility theory do not necessarily imply that decision analysis is not normative; and full normativeness is not necessary for decision analysis to generate valuable insights.

  5. An analysis of the buy-vs-lease decision.

    Science.gov (United States)

    Berlin, Jonathan W; Lexa, Frank J

    2006-02-01

    This article presents a financial model to analyze the buy-vs-lease decision. The model is constructed from the perspective of a lessee with an operating lease and uses the concept of net present value, which calculates the current value of predicted cash flows in the future. Predicted cash flows of an operating lease compared with buying are presented in the model, as is the after-tax borrowing rate, the appropriate discount rate used in a model of this type. The article also discusses nonfinancial factors that may influence the buy-vs-lease decision, including the need for flexibility in working capital and the anticipated technological obsolescence of equipment.

  6. [Analysis of the characteristics of the older adults with depression using data mining decision tree analysis].

    Science.gov (United States)

    Park, Myonghwa; Choi, Sora; Shin, A Mi; Koo, Chul Hoi

    2013-02-01

    The purpose of this study was to develop a prediction model for the characteristics of older adults with depression using the decision tree method. A large dataset from the 2008 Korean Elderly Survey was used and data of 14,970 elderly people were analyzed. Target variable was depression and 53 input variables were general characteristics, family & social relationship, economic status, health status, health behavior, functional status, leisure & social activity, quality of life, and living environment. Data were analyzed by decision tree analysis, a data mining technique using SPSS Window 19.0 and Clementine 12.0 programs. The decision trees were classified into five different rules to define the characteristics of older adults with depression. Classification & Regression Tree (C&RT) showed the best prediction with an accuracy of 80.81% among data mining models. Factors in the rules were life satisfaction, nutritional status, daily activity difficulty due to pain, functional limitation for basic or instrumental daily activities, number of chronic diseases and daily activity difficulty due to disease. The different rules classified by the decision tree model in this study should contribute as baseline data for discovering informative knowledge and developing interventions tailored to these individual characteristics.

  7. Decision modeling for analyzing fire action outcomes

    Science.gov (United States)

    Donald MacGregor; Armando Gonzalez-Caban

    2008-01-01

    A methodology for incident decomposition and reconstruction is developed based on the concept of an "event-frame model." The event-frame model characterizes a fire incident in terms of (a) environmental events that pertain to the fire and the fire context (e.g., fire behavior, weather, fuels) and (b) management events that represent responses to the fire...

  8. Decentralisation of Health Services in Fiji: A Decision Space Analysis.

    Science.gov (United States)

    Mohammed, Jalal; North, Nicola; Ashton, Toni

    2015-11-15

    Decentralisation aims to bring services closer to the community and has been advocated in the health sector to improve quality, access and equity, and to empower local agencies, increase innovation and efficiency and bring healthcare and decision-making as close as possible to where people live and work. Fiji has attempted two approaches to decentralisation. The current approach reflects a model of deconcentration of outpatient services from the tertiary level hospital to the peripheral health centres in the Suva subdivision. Using a modified decision space approach developed by Bossert, this study measures decision space created in five broad categories (finance, service organisation, human resources, access rules, and governance rules) within the decentralised services. Fiji's centrally managed historical-based allocation of financial resources and management of human resources resulted in no decision space for decentralised agents. Narrow decision space was created in the service organisation category where, with limited decision space created over access rules, Fiji has seen greater usage of its decentralised health centres. There remains limited decision space in governance. The current wave of decentralisation reveals that, whilst the workload has shifted from the tertiary hospital to the peripheral health centres, it has been accompanied by limited transfer of administrative authority, suggesting that Fiji's deconcentration reflects the transfer of workload only with decision-making in the five functional areas remaining largely centralised. As such, the benefits of decentralisation for users and providers are likely to be limited. © 2016 by Kerman University of Medical Sciences.

  9. Fuzzy rationality and parameter elicitation in decision analysis

    Science.gov (United States)

    Nikolova, Natalia D.; Tenekedjiev, Kiril I.

    2010-07-01

    It is widely recognised by decision analysts that real decision-makers always make estimates in an interval form. An overview of techniques to find an optimal alternative among such with imprecise and interval probabilities is presented. Scalarisation methods are outlined as most appropriate. A proper continuation of such techniques is fuzzy rational (FR) decision analysis. A detailed representation of the elicitation process influenced by fuzzy rationality is given. The interval character of probabilities leads to the introduction of ribbon functions, whose general form and special cases are compared with the p-boxes. As demonstrated, approximation of utilities in FR decision analysis does not depend on the probabilities, but the approximation of probabilities is dependent on preferences.

  10. Decision Analysis System for Selection of Appropriate Decontamination Technologies

    International Nuclear Information System (INIS)

    Ebadian, M.A.; Boudreaux, J.F.; Chinta, S.; Zanakis, S.H.

    1998-01-01

    The principal objective for designing Decision Analysis System for Decontamination (DASD) is to support DOE-EM's endeavor to employ the most efficient and effective technologies for treating radiologically contaminated surfaces while minimizing personnel and environmental risks. DASD will provide a tool for environmental decision makers to improve the quality, consistency, and efficacy of their technology selection decisions. The system will facilitate methodical comparisons between innovative and baseline decontamination technologies and aid in identifying the most suitable technologies for performing surface decontamination at DOE environmental restoration sites

  11. Fault trees for decision making in systems analysis

    International Nuclear Information System (INIS)

    Lambert, H.E.

    1975-01-01

    The application of fault tree analysis (FTA) to system safety and reliability is presented within the framework of system safety analysis. The concepts and techniques involved in manual and automated fault tree construction are described and their differences noted. The theory of mathematical reliability pertinent to FTA is presented with emphasis on engineering applications. An outline of the quantitative reliability techniques of the Reactor Safety Study is given. Concepts of probabilistic importance are presented within the fault tree framework and applied to the areas of system design, diagnosis and simulation. The computer code IMPORTANCE ranks basic events and cut sets according to a sensitivity analysis. A useful feature of the IMPORTANCE code is that it can accept relative failure data as input. The output of the IMPORTANCE code can assist an analyst in finding weaknesses in system design and operation, suggest the most optimal course of system upgrade, and determine the optimal location of sensors within a system. A general simulation model of system failure in terms of fault tree logic is described. The model is intended for efficient diagnosis of the causes of system failure in the event of a system breakdown. It can also be used to assist an operator in making decisions under a time constraint regarding the future course of operations. The model is well suited for computer implementation. New results incorporated in the simulation model include an algorithm to generate repair checklists on the basis of fault tree logic and a one-step-ahead optimization procedure that minimizes the expected time to diagnose system failure. (80 figures, 20 tables)

  12. Critical infrastructure protection decision support system decision model : overview and quick-start user's guide.

    Energy Technology Data Exchange (ETDEWEB)

    Samsa, M.; Van Kuiken, J.; Jusko, M.; Decision and Information Sciences

    2008-12-01

    The Critical Infrastructure Protection Decision Support System Decision Model (CIPDSS-DM) is a useful tool for comparing the effectiveness of alternative risk-mitigation strategies on the basis of CIPDSS consequence scenarios. The model is designed to assist analysts and policy makers in evaluating and selecting the most effective risk-mitigation strategies, as affected by the importance assigned to various impact measures and the likelihood of an incident. A typical CIPDSS-DM decision map plots the relative preference of alternative risk-mitigation options versus the annual probability of an undesired incident occurring once during the protective life of the investment, assumed to be 20 years. The model also enables other types of comparisons, including a decision map that isolates a selected impact variable and displays the relative preference for the options of interest--parameterized on the basis of the contribution of the isolated variable to total impact, as well as the likelihood of the incident. Satisfaction/regret analysis further assists the analyst or policy maker in evaluating the confidence with which one option can be selected over another.

  13. Models in environmental regulatory decision making

    National Research Council Canada - National Science Library

    Committee on Models in the Regulatory Decision Process, National Research Council

    2007-01-01

    .... Models help EPA explain environmental phenomena in settings where direct observations are limited or unavailable, and anticipate the effects of agency policies on the environment, human health and the economy...

  14. Decision analysis for cleanup strategies in an urban environment

    International Nuclear Information System (INIS)

    Sinkko, K.; Ikaeheimonen, T.K.

    2000-01-01

    The values entering the decisions on protective actions, as concerning the society, are multidimensional. People have strong feelings and beliefs about these values, some of which are not numerically quantified and do not exist in monetary form. The decision analysis is applied in planning the recovery operations to clean up an urban environment in the event of a hypothetical nuclear power plant accident assisting in rendering explicit and apparent all factors involved and evaluating their relative importance. (author)

  15. An empirical analysis of the corporate call decision

    International Nuclear Information System (INIS)

    Carlson, M.D.

    1998-01-01

    An economic study of the the behaviour of financial managers of utility companies was presented. The study examined whether or not an option pricing based model of the call decision does a better job of explaining callable preferred share prices and call decisions compared to other models. In this study, the Rust (1987) empirical technique was extended to include the use of information from preferred share prices in addition to the call decisions. Reasonable estimates were obtained from data of shares of the Pacific Gas and Electric Company (PGE) for the transaction costs associated with a call. It was concluded that the managers of the PGE clearly take into account the value of the option to delay the call when making their call decisions

  16. Computerization of the safeguards analysis decision process

    International Nuclear Information System (INIS)

    Ehinger, M.H.

    1990-01-01

    This paper reports that safeguards regulations are evolving to meet new demands for timeliness and sensitivity in detecting the loss or unauthorized use of sensitive nuclear materials. The opportunities to meet new rules, particularly in bulk processing plants, involve developing techniques which use modern, computerized process control and information systems. Using these computerized systems in the safeguards analysis involves all the challenges of the man-machine interface experienced in the typical process control application and adds new dimensions to accuracy requirements, data analysis, and alarm resolution in the regulatory environment

  17. Unicriterion Model: A Qualitative Decision Making Method That Promotes Ethics

    Directory of Open Access Journals (Sweden)

    Fernando Guilherme Silvano Lobo Pimentel

    2011-06-01

    Full Text Available Management decision making methods frequently adopt quantitativemodels of several criteria that bypass the question of whysome criteria are considered more important than others, whichmakes more difficult the task of delivering a transparent viewof preference structure priorities that might promote ethics andlearning and serve as a basis for future decisions. To tackle thisparticular shortcoming of usual methods, an alternative qualitativemethodology of aggregating preferences based on the rankingof criteria is proposed. Such an approach delivers a simpleand transparent model for the solution of each preference conflictfaced during the management decision making process. Themethod proceeds by breaking the decision problem into ‘two criteria– two alternatives’ scenarios, and translating the problem ofchoice between alternatives to a problem of choice between criteriawhenever appropriate. The unicriterion model method is illustratedby its application in a car purchase and a house purchasedecision problem.

  18. Ignorance- versus evidence-based decision making: a decision time analysis of the recognition heuristic.

    Science.gov (United States)

    Hilbig, Benjamin E; Pohl, Rüdiger F

    2009-09-01

    According to part of the adaptive toolbox notion of decision making known as the recognition heuristic (RH), the decision process in comparative judgments-and its duration-is determined by whether recognition discriminates between objects. By contrast, some recently proposed alternative models predict that choices largely depend on the amount of evidence speaking for each of the objects and that decision times thus depend on the evidential difference between objects, or the degree of conflict between options. This article presents 3 experiments that tested predictions derived from the RH against those from alternative models. All experiments used naturally recognized objects without teaching participants any information and thus provided optimal conditions for application of the RH. However, results supported the alternative, evidence-based models and often conflicted with the RH. Recognition was not the key determinant of decision times, whereas differences between objects with respect to (both positive and negative) evidence predicted effects well. In sum, alternative models that allow for the integration of different pieces of information may well provide a better account of comparative judgments. (c) 2009 APA, all rights reserved.

  19. Quantitative analysis of strategic and tactical purchasing decisions

    OpenAIRE

    Heijboer, G.J.

    2003-01-01

    Purchasing management is a relatively new scientific research field, partly due to the fact that purchasing has only recently been recognized as a factor of strategic importance to an organization. In this thesis, the author focuses on a selection of strategic and tactical purchasing decision problems. New quantitative models are developed for these decision problems using a range of mathematical techniques, thereby contributing to the further development of purchasing theory and its appliati...

  20. Clarity versus complexity: land-use modeling as a practical tool for decision-makers

    Science.gov (United States)

    Sohl, Terry L.; Claggett, Peter

    2013-01-01

    The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes. LULC modelers have become very adept at creating tools for modeling LULC change, but complicated models and lack of transparency limit their utility for decision-makers. The complicated nature of many LULC models also makes it impractical or even impossible to perform a rigorous analysis of modeling uncertainty. This paper provides a review of land-cover modeling approaches and the issues causes by the complicated nature of models, and provides suggestions to facilitate the increased use of LULC models by decision-makers and other stakeholders. The utility of LULC models themselves can be improved by 1) providing model code and documentation, 2) through the use of scenario frameworks to frame overall uncertainties, 3) improving methods for generalizing key LULC processes most important to stakeholders, and 4) adopting more rigorous standards for validating models and quantifying uncertainty. Communication with decision-makers and other stakeholders can be improved by increasing stakeholder participation in all stages of the modeling process, increasing the transparency of model structure and uncertainties, and developing user-friendly decision-support systems to bridge the link between LULC science and policy. By considering these options, LULC science will be better positioned to support decision-makers and increase real-world application of LULC modeling results.

  1. Development of a clinical decision model for thyroid nodules

    Directory of Open Access Journals (Sweden)

    Eberhardt John

    2009-08-01

    malignancy. Cross validation of the model created with Bayesian Network Analysis effectively predicted malignancy [AUC = 0.88 (95%CI: 0.82–0.94] in thyroid nodules. The positive and negative predictive values of the model are 83% (95%CI: 76%–91% and 79% (95%CI: 72%–86%, respectively. Conclusion An integrated predictive decision model using Bayesian inference incorporating readily obtainable thyroid nodule measures is clinically relevant, as it effectively predicts malignancy in thyroid nodules. This model warrants further validation testing in prospective clinical trials.

  2. Employing Conjoint Analysis in Making Compensation Decisions.

    Science.gov (United States)

    Kienast, Philip; And Others

    1983-01-01

    Describes a method employing conjoint analysis that generates utility/cost ratios for various elements of the compensation package. Its superiority to simple preference surveys is examined. Results of a study of the use of this method in fringe benefit planning in a large financial institution are reported. (Author/JAC)

  3. Application of decision analysis in antibiotic formulary choices.

    Science.gov (United States)

    Szymusiak-Mutnick, B; Mutnick, A H

    1994-01-01

    To introduce the reader to the fundamentals involved in using decision analysis as a tool in evaluating the associated costs and effectiveness of comparable therapeutic agents. Currently available literature citations were used to provide the reader with basic references whose purpose is to provide a step-by-step approach for using Decision Analysis in conducting a cost-effective comparison of three commonly used antibiotics. Data were gathered from a previously conducted retrospective chart review where the three antibiotics were used for either prophylactic, empiric, or documented infections. Although this study was limited by its retrospective nature, the reader can use the data to appreciate the fundamentals of decision analysis. The continually changing climate in healthcare and the added visibility of pharmacologic agents in the treatment and prevention of disease has increased pressure on pharmacy departments to provide therapeutic agents that are cost-effective. Decision analysis can be used to compare therapeutic agents, in terms of financial as well as clinical outcomes, in a structured fashion that all members of the health care team can understand. The application of Decision analysis is appropriate for many therapeutic agents, not just antibiotics.

  4. Modeling strategic investment decisions in spatial markets

    International Nuclear Information System (INIS)

    Lorenczik, Stefan; Malischek, Raimund

    2014-01-01

    Markets for natural resources and commodities are often oligopolistic. In these markets, production capacities are key for strategic interaction between the oligopolists. We analyze how different market structures influence oligopolistic capacity investments and thereby affect supply, prices and rents in spatial natural resource markets using mathematical programing models. The models comprise an investment period and a supply period in which players compete in quantities. We compare three models, one perfect competition and two Cournot models, in which the product is either traded through long-term contracts or on spot markets in the supply period. Tractability and practicality of the approach are demonstrated in an application to the international metallurgical coal market. Results may vary substantially between the different models. The metallurgical coal market has recently made progress in moving away from long-term contracts and more towards spot market-based trade. Based on our results, we conclude that this regime switch is likely to raise consumer rents but lower producer rents. The total welfare differs only negligibly.

  5. Modeling strategic investment decisions in spatial markets

    Energy Technology Data Exchange (ETDEWEB)

    Lorenczik, Stefan; Malischek, Raimund [Koeln Univ. (Germany). Energiewirtschaftliches Inst.; Trueby, Johannes [International Energy Agency, 75 - Paris (France)

    2014-04-15

    Markets for natural resources and commodities are often oligopolistic. In these markets, production capacities are key for strategic interaction between the oligopolists. We analyze how different market structures influence oligopolistic capacity investments and thereby affect supply, prices and rents in spatial natural resource markets using mathematical programing models. The models comprise an investment period and a supply period in which players compete in quantities. We compare three models, one perfect competition and two Cournot models, in which the product is either traded through long-term contracts or on spot markets in the supply period. Tractability and practicality of the approach are demonstrated in an application to the international metallurgical coal market. Results may vary substantially between the different models. The metallurgical coal market has recently made progress in moving away from long-term contracts and more towards spot market-based trade. Based on our results, we conclude that this regime switch is likely to raise consumer rents but lower producer rents. The total welfare differs only negligibly.

  6. Making Invasion models useful for decision makers; incorporating uncertainty, knowledge gaps, and decision-making preferences

    Science.gov (United States)

    Denys Yemshanov; Frank H Koch; Mark Ducey

    2015-01-01

    Uncertainty is inherent in model-based forecasts of ecological invasions. In this chapter, we explore how the perceptions of that uncertainty can be incorporated into the pest risk assessment process. Uncertainty changes a decision maker’s perceptions of risk; therefore, the direct incorporation of uncertainty may provide a more appropriate depiction of risk. Our...

  7. Impact of modellers' decisions on hydrological a priori predictions

    Science.gov (United States)

    Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.

    2014-06-01

    In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers - using the model of their choice - for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of

  8. Neuro-Based Artificial Intelligence Model for Loan Decisions

    OpenAIRE

    Shorouq F. Eletter; Saad G. Yaseen; Ghaleb A. Elrefae

    2010-01-01

    Problem statement: Despite the increase in consumer loans defaults and competition in the banking market, most of the Jordanian commercial banks are reluctant to use artificial intelligence software systems for supporting loan decisions. Approach: This study developed a proposed model that identifies artificial neural network as an enabling tool for evaluating credit applications to support loan decisions in the Jordanian Commercial banks. A multi-layer feed-forward neural network with backpr...

  9. Measuring and modeling behavioral decision dynamics in collective evacuation.

    Directory of Open Access Journals (Sweden)

    Jean M Carlson

    Full Text Available Identifying and quantifying factors influencing human decision making remains an outstanding challenge, impacting the performance and predictability of social and technological systems. In many cases, system failures are traced to human factors including congestion, overload, miscommunication, and delays. Here we report results of a behavioral network science experiment, targeting decision making in a natural disaster. In a controlled laboratory setting, our results quantify several key factors influencing individual evacuation decision making in a controlled laboratory setting. The experiment includes tensions between broadcast and peer-to-peer information, and contrasts the effects of temporal urgency associated with the imminence of the disaster and the effects of limited shelter capacity for evacuees. Based on empirical measurements of the cumulative rate of evacuations as a function of the instantaneous disaster likelihood, we develop a quantitative model for decision making that captures remarkably well the main features of observed collective behavior across many different scenarios. Moreover, this model captures the sensitivity of individual- and population-level decision behaviors to external pressures, and systematic deviations from the model provide meaningful estimates of variability in the collective response. Identification of robust methods for quantifying human decisions in the face of risk has implications for policy in disasters and other threat scenarios, specifically the development and testing of robust strategies for training and control of evacuations that account for human behavior and network topologies.

  10. Models in environmental regulatory decision making

    National Research Council Canada - National Science Library

    Committee on Models in the Regulatory Decision Process; National Research Council; Division on Earth and Life Studies; National Research Council

    2007-01-01

    .... The centerpiece of the book's recommended vision is a life-cycle approach to model evaluation which includes peer review, corroboration of results, and other activities. This will enhance the agency's ability to respond to requirements from a 2001 law on information quality and improve policy development and implementation.

  11. Vascular access choice in incident hemodialysis patients: a decision analysis.

    Science.gov (United States)

    Drew, David A; Lok, Charmaine E; Cohen, Joshua T; Wagner, Martin; Tangri, Navdeep; Weiner, Daniel E

    2015-01-01

    Hemodialysis vascular access recommendations promote arteriovenous (AV) fistulas first; however, it may not be the best approach for all hemodialysis patients, because likelihood of successful fistula placement, procedure-related and subsequent costs, and patient survival modify the optimal access choice. We performed a decision analysis evaluating AV fistula, AV graft, and central venous catheter (CVC) strategies for patients initiating hemodialysis with a CVC, a scenario occurring in over 70% of United States dialysis patients. A decision tree model was constructed to reflect progression from hemodialysis initiation. Patients were classified into one of three vascular access choices: maintain CVC, attempt fistula, or attempt graft. We explicitly modeled probabilities of primary and secondary patency for each access type, with success modified by age, sex, and diabetes. Access-specific mortality was incorporated using preexisting cohort data, including terms for age, sex, and diabetes. Costs were ascertained from the 2010 USRDS report and Medicare for procedure costs. An AV fistula attempt strategy was found to be superior to AV grafts and CVCs in regard to mortality and cost for the majority of patient characteristic combinations, especially younger men without diabetes. Women with diabetes and elderly men with diabetes had similar outcomes, regardless of access type. Overall, the advantages of an AV fistula attempt strategy lessened considerably among older patients, particularly women with diabetes, reflecting the effect of lower AV fistula success rates and lower life expectancy. These results suggest that vascular access-related outcomes may be optimized by considering individual patient characteristics. Copyright © 2015 by the American Society of Nephrology.

  12. Multiple criteria decision analysis for health technology assessment.

    Science.gov (United States)

    Thokala, Praveen; Duenas, Alejandra

    2012-12-01

    Multicriteria decision analysis (MCDA) has been suggested by some researchers as a method to capture the benefits beyond quality adjusted life-years in a transparent and consistent manner. The objectives of this article were to analyze the possible application of MCDA approaches in health technology assessment and to describe their relative advantages and disadvantages. This article begins with an introduction to the most common types of MCDA models and a critical review of state-of-the-art methods for incorporating multiple criteria in health technology assessment. An overview of MCDA is provided and is compared against the current UK National Institute for Health and Clinical Excellence health technology appraisal process. A generic MCDA modeling approach is described, and the different MCDA modeling approaches are applied to a hypothetical case study. A comparison of the different MCDA approaches is provided, and the generic issues that need consideration before the application of MCDA in health technology assessment are examined. There are general practical issues that might arise from using an MCDA approach, and it is suggested that appropriate care be taken to ensure the success of MCDA techniques in the appraisal process. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  13. TESTING MULTI-CRITERIA DECISION ANALYSIS FOR MORE TRANSPARENT RESOURCE-ALLOCATION DECISION MAKING IN COLOMBIA.

    Science.gov (United States)

    Castro Jaramillo, Hector Eduardo; Goetghebeur, Mireille; Moreno-Mattar, Ornella

    2016-01-01

    In 2012, Colombia experienced an important institutional transformation after the establishment of the Health Technology Assessment Institute (IETS), the disbandment of the Regulatory Commission for Health and the reassignment of reimbursement decision-making powers to the Ministry of Health and Social Protection (MoHSP). These dynamic changes provided the opportunity to test Multi-Criteria Decision Analysis (MCDA) for systematic and more transparent resource-allocation decision-making. During 2012 and 2013, the MCDA framework Evidence and Value: Impact on Decision Making (EVIDEM) was tested in Colombia. This consisted of a preparatory stage in which the investigators conducted literature searches and produced HTA reports for four interventions of interest, followed by a panel session with decision makers. This method was contrasted with a current approach used in Colombia for updating the publicly financed benefits package (POS), where narrative health technology assessment (HTA) reports are presented alongside comprehensive budget impact analyses (BIAs). Disease severity, size of population, and efficacy ranked at the top among fifteen preselected relevant criteria. MCDA estimates of technologies of interest ranged between 71 to 90 percent of maximum value. The ranking of technologies was sensitive to the methods used. Participants considered that a two-step approach including an MCDA template, complemented by a detailed BIA would be the best approach to assist decision-making in this context. Participants agreed that systematic priority setting should take place in Colombia. This work may serve as the basis to the MoHSP on its interest of setting up a systematic and more transparent process for resource-allocation decision-making.

  14. Economic modeling for life extension decision making

    International Nuclear Information System (INIS)

    Farber, M.A.; Harrison, D.L.; Carlson, D.D.

    1986-01-01

    This paper presents a methodology for the economic and financial analysis of nuclear plant life extension under uncertainty and demonstrates its use in a case analysis. While the economic and financial evaluation of life extension does not require new analytical tools, such studies should be based on the following three premises. First, the methodology should examine effects at the level of the company or utility system, because the most important economic implications of life extension relate to the altered generation system expansion plan. Second, it should focus on the implications of uncertainty in order to understand the factors that most affect life extension benefits and identify risk management efforts. Third, the methodology should address multiple objectives, at a minimum, both economic and financial objectives

  15. Multi-criteria decision analysis for use in transport decision making

    DEFF Research Database (Denmark)

    the recent years that besides the social costs and benefits associated with transport other impacts that are more difficult to monetise should also have influence on the decision making process. This is in many developed countries realised in the transport planning, which takes into account a wide range......, however, commonly agreed that the final decision making concerning transport infrastructure projects in many cases will depend on other aspects besides the monetary ones assessed in a socio-economic analysis. Nevertheless, an assessment framework such as the Danish one (DMT, 2003) does not provide any...... specific guidelines on how to include the strategic impacts; it merely suggests describing the impacts verbally and keeping them in mind during the decision process. A coherent, well-structured, flexible, straight forward evaluation method, taking into account all the requirements of a transport...

  16. Models of Economic Analysis

    OpenAIRE

    Adrian Ioana; Tiberiu Socaciu

    2013-01-01

    The article presents specific aspects of management and models for economic analysis. Thus, we present the main types of economic analysis: statistical analysis, dynamic analysis, static analysis, mathematical analysis, psychological analysis. Also we present the main object of the analysis: the technological activity analysis of a company, the analysis of the production costs, the economic activity analysis of a company, the analysis of equipment, the analysis of labor productivity, the anal...

  17. Perceptual decision neurosciences: a model-based review

    NARCIS (Netherlands)

    Mulder, M.J.; van Maanen, L.; Forstmann, B.U.

    2014-01-01

    In this review we summarize findings published over the past 10 years focusing on the neural correlates of perceptual decision-making. Importantly, this review highlights only studies that employ a model-based approach, i.e., they use quantitative cognitive models in combination with neuroscientific

  18. Decision support for natural resource management; models and evaluation methods

    NARCIS (Netherlands)

    Wessels, J.; Makowski, M.; Nakayama, H.

    2001-01-01

    When managing natural resources or agrobusinesses, one always has to deal with autonomous processes. These autonomous processes play a core role in designing model-based decision support systems. This chapter tries to give insight into the question of which types of models might be used in which

  19. A Utility Model for Teaching Load Decisions in Academic Departments.

    Science.gov (United States)

    Massey, William F.; Zemsky, Robert

    1997-01-01

    Presents a utility model for academic department decision making and describes the structural specifications for analyzing it. The model confirms the class-size utility asymmetry predicted by the authors' academic rachet theory, but shows that marginal utility associated with college teaching loads is always negative. Curricular structure and…

  20. Model based decision support for planning of road maintenance

    NARCIS (Netherlands)

    van Harten, Aart; Worm, J.M.; Worm, J.M.

    1996-01-01

    In this article we describe a Decision Support Model, based on Operational Research methods, for the multi-period planning of maintenance of bituminous pavements. This model is a tool for the road manager to assist in generating an optimal maintenance plan for a road. Optimal means: minimising the

  1. Benefit-Risk Analysis for Decision-Making: An Approach.

    Science.gov (United States)

    Raju, G K; Gurumurthi, K; Domike, R

    2016-12-01

    The analysis of benefit and risk is an important aspect of decision-making throughout the drug lifecycle. In this work, the use of a benefit-risk analysis approach to support decision-making was explored. The proposed approach builds on the qualitative US Food and Drug Administration (FDA) approach to include a more explicit analysis based on international standards and guidance that enables aggregation and comparison of benefit and risk on a common basis and a lifecycle focus. The approach is demonstrated on six decisions over the lifecycle (e.g., accelerated approval, withdrawal, and traditional approval) using two case studies: natalizumab for multiple sclerosis (MS) and bedaquiline for multidrug-resistant tuberculosis (MDR-TB). © 2016 American Society for Clinical Pharmacology and Therapeutics.

  2. Closed-Loop Analysis of Soft Decisions for Serial Links

    Science.gov (United States)

    Lansdowne, Chatwin A.; Steele, Glen F.; Zucha, Joan P.; Schlesinger, Adam M.

    2013-01-01

    We describe the benefit of using closed-loop measurements for a radio receiver paired with a counterpart transmitter. We show that real-time analysis of the soft decision output of a receiver can provide rich and relevant insight far beyond the traditional hard-decision bit error rate (BER) test statistic. We describe a Soft Decision Analyzer (SDA) implementation for closed-loop measurements on single- or dual- (orthogonal) channel serial data communication links. The analyzer has been used to identify, quantify, and prioritize contributors to implementation loss in live-time during the development of software defined radios. This test technique gains importance as modern receivers are providing soft decision symbol synchronization as radio links are challenged to push more data and more protocol overhead through noisier channels, and software-defined radios (SDRs) use error-correction codes that approach Shannon's theoretical limit of performance.

  3. A Decision-Making Model of Social Shopping in Franchising: Assessing Collaboration Strategies

    OpenAIRE

    In Lee; Choong-Kwon Lee; Sangjin Yoo; Moo-Jin Choi

    2015-01-01

    Our paper develops a decision-making model of social shopping in franchising to understand impacts of various collaboration strategies on profits of a social intermediary, a franchisor, and a franchisee. Three decision variables are considered to make a daily deal promotion in a manner that results in optimal profits: the social intermediary's advertising expense, the franchisee's service quality expense, and the franchisor's financial assistance to the franchisee. The analysis shows that whi...

  4. Agricultural climate impacts assessment for economic modeling and decision support

    Science.gov (United States)

    Thomson, A. M.; Izaurralde, R. C.; Beach, R.; Zhang, X.; Zhao, K.; Monier, E.

    2013-12-01

    A range of approaches can be used in the application of climate change projections to agricultural impacts assessment. Climate projections can be used directly to drive crop models, which in turn can be used to provide inputs for agricultural economic or integrated assessment models. These model applications, and the transfer of information between models, must be guided by the state of the science. But the methodology must also account for the specific needs of stakeholders and the intended use of model results beyond pure scientific inquiry, including meeting the requirements of agencies responsible for designing and assessing policies, programs, and regulations. Here we present methodology and results of two climate impacts studies that applied climate model projections from CMIP3 and from the EPA Climate Impacts and Risk Analysis (CIRA) project in a crop model (EPIC - Environmental Policy Indicator Climate) in order to generate estimates of changes in crop productivity for use in an agricultural economic model for the United States (FASOM - Forest and Agricultural Sector Optimization Model). The FASOM model is a forward-looking dynamic model of the US forest and agricultural sector used to assess market responses to changing productivity of alternative land uses. The first study, focused on climate change impacts on the UDSA crop insurance program, was designed to use available daily climate projections from the CMIP3 archive. The decision to focus on daily data for this application limited the climate model and time period selection significantly; however for the intended purpose of assessing impacts on crop insurance payments, consideration of extreme event frequency was critical for assessing periodic crop failures. In a second, coordinated impacts study designed to assess the relative difference in climate impacts under a no-mitigation policy and different future climate mitigation scenarios, the stakeholder specifically requested an assessment of a

  5. Endogenous Risks and Learning in Climate Change Decision Analysis

    International Nuclear Information System (INIS)

    O'Neill, B.C.; Ermoliev, Y.; Ermolieva, T.

    2005-01-01

    We analyze the effects of risks and learning on climate change decisions. A two-stage, dynamic, climate change stabilization problem is formulated. The explicit incorporation of ex-post learning induces risk aversion among ex-ante decisions, which is characterized in linear models by VaR- (Value at Risk) and CVaR-type risk (Conditional Value at Risk) measures. Combined with explicit introduction of 'safety' constraints, it creates a 'hit-or-miss' type decision making situation and shows that, even in linear models, learning may lead to either less or more restrictive ex-ante emission reductions. We analyze stylized elements of the model in order to identify the key factors driving outcomes, in particular, the critical role of quantiles of probability distributions characterizing key uncertainties

  6. Beyond pain: modeling decision-making deficits in chronic pain

    Science.gov (United States)

    Hess, Leonardo Emanuel; Haimovici, Ariel; Muñoz, Miguel Angel; Montoya, Pedro

    2014-01-01

    Risky decision-making seems to be markedly disrupted in patients with chronic pain, probably due to the high cost that impose pain and negative mood on executive control functions. Patients’ behavioral performance on decision-making tasks such as the Iowa Gambling Task (IGT) is characterized by selecting cards more frequently from disadvantageous than from advantageous decks, and by switching often between competing responses in comparison with healthy controls (HCs). In the present study, we developed a simple heuristic model to simulate individuals’ choice behavior by varying the level of decision randomness and the importance given to gains and losses. The findings revealed that the model was able to differentiate the behavioral performance of patients with chronic pain and HCs at the group, as well as at the individual level. The best fit of the model in patients with chronic pain was yielded when decisions were not based on previous choices and when gains were considered more relevant than losses. By contrast, the best account of the available data in HCs was obtained when decisions were based on previous experiences and losses loomed larger than gains. In conclusion, our model seems to provide useful information to measure each individual participant extensively, and to deal with the data on a participant-by-participant basis. PMID:25136301

  7. Beyond pain: modeling decision-making deficits in chronic pain

    Directory of Open Access Journals (Sweden)

    Leonardo Emanuel Hess

    2014-08-01

    Full Text Available Risky decision-making seems to be markedly disrupted in patients with chronic pain, probably due to the high cost that impose pain and negative mood on executive control functions. Patients’ behavioral performance on decision-making tasks such as the Iowa Gambling Task (IGT is characterized by selecting cards more frequently from disadvantageous than from advantageous decks, and by switching often between competing responses in comparison with healthy controls. In the present study, we developed a simple heuristic model to simulate individuals’ choice behavior by varying the level of decision randomness and the importance given to gains and losses. The findings revealed that the model was able to differentiate the behavioral performance of patients with chronic pain and healthy controls at the group, as well as at the individual level. The best fit of the model in patients with chronic pain was yielded when decisions were not based on previous choices and when gains were considered more relevant than losses. By contrast, the best account of the available data in healthy controls was obtained when decisions were based on previous experiences and losses loomed larger than gains. In conclusion, our model seems to provide useful information to measure each individual participant extensively, and to deal with the data on a participant-by-participant basis.

  8. Beyond pain: modeling decision-making deficits in chronic pain.

    Science.gov (United States)

    Hess, Leonardo Emanuel; Haimovici, Ariel; Muñoz, Miguel Angel; Montoya, Pedro

    2014-01-01

    Risky decision-making seems to be markedly disrupted in patients with chronic pain, probably due to the high cost that impose pain and negative mood on executive control functions. Patients' behavioral performance on decision-making tasks such as the Iowa Gambling Task (IGT) is characterized by selecting cards more frequently from disadvantageous than from advantageous decks, and by switching often between competing responses in comparison with healthy controls (HCs). In the present study, we developed a simple heuristic model to simulate individuals' choice behavior by varying the level of decision randomness and the importance given to gains and losses. The findings revealed that the model was able to differentiate the behavioral performance of patients with chronic pain and HCs at the group, as well as at the individual level. The best fit of the model in patients with chronic pain was yielded when decisions were not based on previous choices and when gains were considered more relevant than losses. By contrast, the best account of the available data in HCs was obtained when decisions were based on previous experiences and losses loomed larger than gains. In conclusion, our model seems to provide useful information to measure each individual participant extensively, and to deal with the data on a participant-by-participant basis.

  9. A novel computer based expert decision making model for prostate cancer disease management.

    Science.gov (United States)

    Richman, Martin B; Forman, Ernest H; Bayazit, Yildirim; Einstein, Douglas B; Resnick, Martin I; Stovsky, Mark D

    2005-12-01

    We propose a strategic, computer based, prostate cancer decision making model based on the analytic hierarchy process. We developed a model that improves physician-patient joint decision making and enhances the treatment selection process by making this critical decision rational and evidence based. Two groups (patient and physician-expert) completed a clinical study comparing an initial disease management choice with the highest ranked option generated by the computer model. Participants made pairwise comparisons to derive priorities for the objectives and subobjectives related to the disease management decision. The weighted comparisons were then applied to treatment options to yield prioritized rank lists that reflect the likelihood that a given alternative will achieve the participant treatment goal. Aggregate data were evaluated by inconsistency ratio analysis and sensitivity analysis, which assessed the influence of individual objectives and subobjectives on the final rank list of treatment options. Inconsistency ratios less than 0.05 were reliably generated, indicating that judgments made within the model were mathematically rational. The aggregate prioritized list of treatment options was tabulated for the patient and physician groups with similar outcomes for the 2 groups. Analysis of the major defining objectives in the treatment selection decision demonstrated the same rank order for the patient and physician groups with cure, survival and quality of life being more important than controlling cancer, preventing major complications of treatment, preventing blood transfusion complications and limiting treatment cost. Analysis of subobjectives, including quality of life and sexual dysfunction, produced similar priority rankings for the patient and physician groups. Concordance between initial treatment choice and the highest weighted model option differed between the groups with the patient group having 59% concordance and the physician group having only 42

  10. What role can simulation model predictions play in environmental decisions: carbon dioxide as an example

    International Nuclear Information System (INIS)

    Emanuel, W.R.

    1979-01-01

    Frequently, when an environmental issue requiring quantitative analysis surfaces, the development of a model synthesizing all aspects of the problem and applicable at each stage of the decision process is proposed. A more desirable alternative is to generate models specifically designed to meet the requirements of each level in decision making and which can be adapted in response to the changing status of the environmental issue. Various models of the global carbon cycle constructed to predict levels of CO 2 in the atmosphere as a result of man's activities are described to illustrate this point. In summary, the progression of models developed to analyze the global carbon cycle in resolving the CO 2 /climate issue indicates the changing character of models depending on the immediate role they play in environmental decision making. The dominant and successful role served by models in the carbon cycle problem points to the desirability of this flexible approach

  11. Integration Of Externalized Decision Models In The Definition Of Workflows For Digital Pathology

    Directory of Open Access Journals (Sweden)

    J. van Leeuwen

    2016-06-01

    We proposed a workflow solution enabling the representation of decision models as externalized executable tasks in the process definition. Our approach separates the task implementations from the workflow model, ensuring scalability and allowing for the inclusion of complex decision logic in the workflow execution. In we depict a simplified model of a pathology diagnosis workflow (starting with the digitization of the slides, represented according to the BPMN modeling conventions. The example shows a workflow sequence that automatically orders a HER2 FISH when IHC is borderline according to defined customizable thresholds. The process model integrates an image analysis algorithm that scores images. Based on the score and the thresholds the decision model evaluates the condition and recommends the pre-ordering of an additional test when the score falls between the two thresholds. This leads to faster diagnosis and allows balancing the costs of an additional test versus the overhead of the pathologist by choosing the values of the thresholds.  

  12. Consumer's Online Shopping Influence Factors and Decision-Making Model

    Science.gov (United States)

    Yan, Xiangbin; Dai, Shiliang

    Previous research on online consumer behavior has mostly been confined to the perceived risk which is used to explain those barriers for purchasing online. However, perceived benefit is another important factor which influences consumers’ decision when shopping online. As a result, an integrated consumer online shopping decision-making model is developed which contains three elements—Consumer, Product, and Web Site. This model proposed relative factors which influence the consumers’ intention during the online shopping progress, and divided them into two different dimensions—mentally level and material level. We tested those factors with surveys, from both online volunteers and offline paper surveys with more than 200 samples. With the help of SEM, the experimental results show that the proposed model and method can be used to analyze consumer’s online shopping decision-making process effectively.

  13. The Pedagogical Reflection Model - an educational perspective on clinical decisions

    DEFF Research Database (Denmark)

    Voergaard Poulsen, Bettina; Vibholm Persson, Stine; Skriver, Mette

    Clinical decision-making is important in patient-centred nursing, which is known in nursing education and research (1) The Pedagogical Reflection Model (PRM) can provide a framework that supports students’ decision-making in patient-specific situations. PRM is based on the assumption that clinical......) The aims of this study were to explore how nurse students and clinical supervisors use PRM as method to reflect before, during and after PRM guidance in relation to clinical decisions in the first year of clinical practice...... decision-making needs to take into account; 1) clinical experiences, 2) the perspective of the patient, 3) clinical observations and investigations, 4) knowledge about patients experiences of being a patient and ill, 5) medical knowledge about diseases, and 6) the organizational framework (2,3,4)(Figure 1...

  14. Use of decision analysis techniques to determine Hanford cleanup priorities

    International Nuclear Information System (INIS)

    Fassbender, L.; Gregory, R.; Winterfeldt, D. von; John, R.

    1992-01-01

    In January 1991, the U.S. Department of Energy (DOE) Richland Field Office, Westinghouse Hanford Company, and the Pacific Northwest Laboratory initiated the Hanford Integrated Planning Process (HIPP) to ensure that technically sound and publicly acceptable decisions are made that support the environmental cleanup mission at Hanford. One of the HIPP's key roles is to develop an understanding of the science and technology (S and T) requirements to support the cleanup mission. This includes conducting an annual systematic assessment of the S and T needs at Hanford to support a comprehensive technology development program and a complementary scientific research program. Basic to success is a planning and assessment methodology that is defensible from a technical perspective and acceptable to the various Hanford stakeholders. Decision analysis techniques were used to help identify and prioritize problems and S and T needs at Hanford. The approach used structured elicitations to bring many Hanford stakeholders into the process. Decision analysis, which is based on the axioms and methods of utility and probability theory, is especially useful in problems characterized by uncertainties and multiple objectives. Decision analysis addresses uncertainties by laying out a logical sequence of decisions, events, and consequences and by quantifying event and consequence probabilities on the basis of expert judgments

  15. Decision-Making Theories and Models: A Discussion of Rational and Psychological Decision-Making Theories and Models: The Search for a Cultural-Ethical Decision-Making Model

    OpenAIRE

    Oliveira, Arnaldo

    2007-01-01

    This paper examines rational and psychological decision-making models. Descriptive and normative methodologies such as attribution theory, schema theory, prospect theory, ambiguity model, game theory, and expected utility theory are discussed. The definition of culture is reviewed, and the relationship between culture and decision making is also highlighted as many organizations use a cultural-ethical decision-making model.

  16. Making Good Decisions in Healthcare with Multi-Criteria Decision Analysis: The Use, Current Research and Future Development of MCDA.

    Science.gov (United States)

    Mühlbacher, Axel C; Kaczynski, Anika

    2016-02-01

    Healthcare decision making is usually characterized by a low degree of transparency. The demand for transparent decision processes can be fulfilled only when assessment, appraisal and decisions about health technologies are performed under a systematic construct of benefit assessment. The benefit of an intervention is often multidimensional and, thus, must be represented by several decision criteria. Complex decision problems require an assessment and appraisal of various criteria; therefore, a decision process that systematically identifies the best available alternative and enables an optimal and transparent decision is needed. For that reason, decision criteria must be weighted and goal achievement must be scored for all alternatives. Methods of multi-criteria decision analysis (MCDA) are available to analyse and appraise multiple clinical endpoints and structure complex decision problems in healthcare decision making. By means of MCDA, value judgments, priorities and preferences of patients, insurees and experts can be integrated systematically and transparently into the decision-making process. This article describes the MCDA framework and identifies potential areas where MCDA can be of use (e.g. approval, guidelines and reimbursement/pricing of health technologies). A literature search was performed to identify current research in healthcare. The results showed that healthcare decision making is addressing the problem of multiple decision criteria and is focusing on the future development and use of techniques to weight and score different decision criteria. This article emphasizes the use and future benefit of MCDA.

  17. Decision Analysis of Advertising and Price for Bilateral Competing Supply Chain

    Directory of Open Access Journals (Sweden)

    Cheng-Tang Zhang

    2013-01-01

    Full Text Available The outcome of centralized equilibrium, prisoner's dilemma equilibrium, and decentralized equilibrium under different decision models has been provided with regards to bilateral competing supply chain system, either side of which is composed of one manufacturer and one retailer. Theoretical analysis indicates a positive correlation between price and one's own advertising investment level and a negative correlation between price and the opponent's advertising investment level. Through analysis of numerical examples, the results reveal a first mover advantage that leads to prisoner's dilemma in the system as well as the impact that price and advertising competition intensity has on the supply chain's choice of decision model.

  18. Ranking of Business Process Simulation Software Tools with DEX/QQ Hierarchical Decision Model.

    Science.gov (United States)

    Damij, Nadja; Boškoski, Pavle; Bohanec, Marko; Mileva Boshkoska, Biljana

    2016-01-01

    The omnipresent need for optimisation requires constant improvements of companies' business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and "what-if" scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results.

  19. Modelling and simulation-based acquisition decision support: present & future

    CSIR Research Space (South Africa)

    Naidoo, S

    2009-10-01

    Full Text Available stream_source_info Naidoo1_2009.pdf.txt stream_content_type text/plain stream_size 24551 Content-Encoding UTF-8 stream_name Naidoo1_2009.pdf.txt Content-Type text/plain; charset=UTF-8 1 Modelling & Simulation...-Based Acquisition Decision Support: Present & Future Shahen Naidoo Abstract The Ground Based Air Defence System (GBADS) Programme, of the South African Army has been applying modelling and simulation (M&S) to provide acquisition decision and doctrine...

  20. A Mining Algorithm for Extracting Decision Process Data Models

    Directory of Open Access Journals (Sweden)

    Cristina-Claudia DOLEAN

    2011-01-01

    Full Text Available The paper introduces an algorithm that mines logs of user interaction with simulation software. It outputs a model that explicitly shows the data perspective of the decision process, namely the Decision Data Model (DDM. In the first part of the paper we focus on how the DDM is extracted by our mining algorithm. We introduce it as pseudo-code and, then, provide explanations and examples of how it actually works. In the second part of the paper, we use a series of small case studies to prove the robustness of the mining algorithm and how it deals with the most common patterns we found in real logs.

  1. Building a maintenance policy through a multi-criterion decision-making model

    Science.gov (United States)

    Faghihinia, Elahe; Mollaverdi, Naser

    2012-08-01

    A major competitive advantage of production and service systems is establishing a proper maintenance policy. Therefore, maintenance managers should make maintenance decisions that best fit their systems. Multi-criterion decision-making methods can take into account a number of aspects associated with the competitiveness factors of a system. This paper presents a multi-criterion decision-aided maintenance model with three criteria that have more influence on decision making: reliability, maintenance cost, and maintenance downtime. The Bayesian approach has been applied to confront maintenance failure data shortage. Therefore, the model seeks to make the best compromise between these three criteria and establish replacement intervals using Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE II), integrating the Bayesian approach with regard to the preference of the decision maker to the problem. Finally, using a numerical application, the model has been illustrated, and for a visual realization and an illustrative sensitivity analysis, PROMETHEE GAIA (the visual interactive module) has been used. Use of PROMETHEE II and PROMETHEE GAIA has been made with Decision Lab software. A sensitivity analysis has been made to verify the robustness of certain parameters of the model.

  2. Deciding to Come Out to Parents: Toward a Model of Sexual Orientation Disclosure Decisions.

    Science.gov (United States)

    Grafsky, Erika L

    2017-08-16

    The purpose of this study was to conduct research to understand nonheterosexual youths' decision to disclose their sexual orientation information to their parents. The sample for this study includes 22 youth between the ages of 14 and 21. Constructivist grounded theory guided the qualitative methodology and data analysis. The findings from this study posit an emerging model of sexual orientation disclosure decisions comprised of four interrelated factors that influence the decision to disclose or not disclose, as well as a description of the mechanism through which disclosure either does or does not occur. Clinical implications and recommendations for further research are provided. © 2017 Family Process Institute.

  3. A decision analysis of an exploratory studies facility

    International Nuclear Information System (INIS)

    Merkhofer, M.W.; Gnirk, P.

    1992-01-01

    This paper reports that an Exploratory Studied Facility (ESF) is planned to support the characterization of a potential site for a high-level nuclear waste repository at Yucca Mountain, NV. The selection of a design for the ESF is a critical characterization decision because the ESF design may affect the accuracy of characterization testing an constrains subsequent repository design. To assist the design process, a comparative evaluation was conducted to rank 34 alternative ESF-repository designs. The evaluation relied on techniques from formal decision analysis, including decision trees and multiattribute utility analysis (MUA). The results helped to identify favorable design features and enabled the Department of Energy to adopt an improved ESF design

  4. Using real options analysis to support strategic management decisions

    Science.gov (United States)

    Kabaivanov, Stanimir; Markovska, Veneta; Milev, Mariyan

    2013-12-01

    Decision making is a complex process that requires taking into consideration multiple heterogeneous sources of uncertainty. Standard valuation and financial analysis techniques often fail to properly account for all these sources of risk as well as for all sources of additional flexibility. In this paper we explore applications of a modified binomial tree method for real options analysis (ROA) in an effort to improve decision making process. Usual cases of use of real options are analyzed with elaborate study on the applications and advantages that company management can derive from their application. A numeric results based on extending simple binomial tree approach for multiple sources of uncertainty are provided to demonstrate the improvement effects on management decisions.

  5. Comprehensible knowledge model creation for cancer treatment decision making.

    Science.gov (United States)

    Afzal, Muhammad; Hussain, Maqbool; Ali Khan, Wajahat; Ali, Taqdir; Lee, Sungyoung; Huh, Eui-Nam; Farooq Ahmad, Hafiz; Jamshed, Arif; Iqbal, Hassan; Irfan, Muhammad; Abbas Hydari, Manzar

    2017-03-01

    A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Prediction of adverse drug reactions using decision tree modeling.

    Science.gov (United States)

    Hammann, F; Gutmann, H; Vogt, N; Helma, C; Drewe, J

    2010-07-01

    Drug safety is of great importance to public health. The detrimental effects of drugs not only limit their application but also cause suffering in individual patients and evoke distrust of pharmacotherapy. For the purpose of identifying drugs that could be suspected of causing adverse reactions, we present a structure-activity relationship analysis of adverse drug reactions (ADRs) in the central nervous system (CNS), liver, and kidney, and also of allergic reactions, for a broad variety of drugs (n = 507) from the Swiss drug registry. Using decision tree induction, a machine learning method, we determined the chemical, physical, and structural properties of compounds that predispose them to causing ADRs. The models had high predictive accuracies (78.9-90.2%) for allergic, renal, CNS, and hepatic ADRs. We show the feasibility of predicting complex end-organ effects using simple models that involve no expensive computations and that can be used (i) in the selection of the compound during the drug discovery stage, (ii) to understand how drugs interact with the target organ systems, and (iii) for generating alerts in postmarketing drug surveillance and pharmacovigilance.

  7. Dual processing model of medical decision-making

    Science.gov (United States)

    2012-01-01

    Background Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. Methods We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. Results We show that physician’s beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker’s threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. Conclusions We have developed the first dual processing model of medical decision-making that has potential to enrich the current medical

  8. Dual processing model of medical decision-making.

    Science.gov (United States)

    Djulbegovic, Benjamin; Hozo, Iztok; Beckstead, Jason; Tsalatsanis, Athanasios; Pauker, Stephen G

    2012-09-03

    Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. We show that physician's beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker's threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. We have developed the first dual processing model of medical decision-making that has potential to enrich the current medical decision-making field, which is still to the

  9. Dual processing model of medical decision-making

    Directory of Open Access Journals (Sweden)

    Djulbegovic Benjamin

    2012-09-01

    Full Text Available Abstract Background Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I and/or an analytical, deliberative (system II processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. Methods We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. Results We show that physician’s beliefs about whether to treat at higher (lower probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker’s threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. Conclusions We have developed the first dual processing model of medical decision-making that has potential to

  10. Decision making in water resource planning: Models and computer graphics

    Energy Technology Data Exchange (ETDEWEB)

    Fedra, K; Carlsen, A J [ed.

    1987-01-01

    This paper describes some basic concepts of simulation-based decision support systems for water resources management and the role of symbolic, graphics-based user interfaces. Designed to allow direct and easy access to advanced methods of analysis and decision support for a broad and heterogeneous group of users, these systems combine data base management, system simulation, operations research techniques such as optimization, interactive data analysis, elements of advanced decision technology, and artificial intelligence, with a friendly and conversational, symbolic display oriented user interface. Important features of the interface are the use of several parallel or alternative styles of interaction and display, indlucing colour graphics and natural language. Combining quantitative numerical methods with qualitative and heuristic approaches, and giving the user direct and interactive control over the systems function, human knowledge, experience and judgement are integrated with formal approaches into a tightly coupled man-machine system through an intelligent and easily accessible user interface. 4 drawings, 42 references.

  11. Application of decision tree model for the ground subsidence hazard mapping near abandoned underground coal mines.

    Science.gov (United States)

    Lee, Saro; Park, Inhye

    2013-09-30

    Subsidence of ground caused by underground mines poses hazards to human life and property. This study analyzed the hazard to ground subsidence using factors that can affect ground subsidence and a decision tree approach in a geographic information system (GIS). The study area was Taebaek, Gangwon-do, Korea, where many abandoned underground coal mines exist. Spatial data, topography, geology, and various ground-engineering data for the subsidence area were collected and compiled in a database for mapping ground-subsidence hazard (GSH). The subsidence area was randomly split 50/50 for training and validation of the models. A data-mining classification technique was applied to the GSH mapping, and decision trees were constructed using the chi-squared automatic interaction detector (CHAID) and the quick, unbiased, and efficient statistical tree (QUEST) algorithms. The frequency ratio model was also applied to the GSH mapping for comparing with probabilistic model. The resulting GSH maps were validated using area-under-the-curve (AUC) analysis with the subsidence area data that had not been used for training the model. The highest accuracy was achieved by the decision tree model using CHAID algorithm (94.01%) comparing with QUEST algorithms (90.37%) and frequency ratio model (86.70%). These accuracies are higher than previously reported results for decision tree. Decision tree methods can therefore be used efficiently for GSH analysis and might be widely used for prediction of various spatial events. Copyright © 2013. Published by Elsevier Ltd.

  12. 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.

  13. A Decision Tool that Combines Discrete Event Software Process Models with System Dynamics Pieces for Software Development Cost Estimation and Analysis

    Science.gov (United States)

    Mizell, Carolyn Barrett; Malone, Linda

    2007-01-01

    The development process for a large software development project is very complex and dependent on many variables that are dynamic and interrelated. Factors such as size, productivity and defect injection rates will have substantial impact on the project in terms of cost and schedule. These factors can be affected by the intricacies of the process itself as well as human behavior because the process is very labor intensive. The complex nature of the development process can be investigated with software development process models that utilize discrete event simulation to analyze the effects of process changes. The organizational environment and its effects on the workforce can be analyzed with system dynamics that utilizes continuous simulation. Each has unique strengths and the benefits of both types can be exploited by combining a system dynamics model and a discrete event process model. This paper will demonstrate how the two types of models can be combined to investigate the impacts of human resource interactions on productivity and ultimately on cost and schedule.

  14. The decision book fifty models for strategic thinking

    CERN Document Server

    Krogerus, Mikael

    2011-01-01

    Most of us face the same questions every day: What do I want? And how can I get it? How can I live more happily and work more efficiently? A worldwide bestseller, The Decision Book distils into a single volume the fifty best decision-making models used on MBA courses and elsewhere that will help you tackle these important questions - from the well known (the Eisenhower matrix for time management) to the less familiar but equally useful (the Swiss Cheese model). It will even show you how to remember everything you will have learned by the end of it. Stylish and compact, this little black book is a powerful asset. Whether you need to plot a presentation, assess someone's business idea or get to know yourself better, this unique guide will help you simplify any problem and take steps towards the right decision.

  15. Decision-based model development for nuclear material theft, smuggling, and illicit use

    International Nuclear Information System (INIS)

    Scott, B.

    2002-01-01

    Full text: Nuclear material is vulnerable to a range of theft, sabotage, smuggling and illicit use scenarios. These scenarios are dependent on the choices of individuals and organizations involved in these activities. These choices, in turn; are dependent on the perceived payoff vectors of the involved players. These payoff vectors can include monetary gain, ability to avoid detection, penalties for detection, difficulty of accomplishment, resource constraints, infrastructure support, etc. Threat scenarios can be developed from these individual choices, and the set of worst-case threat scenarios can be compiled into a threat definition. The implementation of physical protection controls is dependent on the developed threat scenarios. The analysis of the composition of the postulated threat can be based on the analysis of the postulated decisions of the individuals and organizations involved on theft, smuggling, and illicit use. This paper proposes a model to systematically analyze the significant decision points that an individual or organization addresses as result of its goals. The model's dependence on assumptions is discussed. Using these assumptions, a model is developed that assigns probabilities to a set of decisions performed by the individuals involved in theft/smuggling. The individual and organisation's decisions are based on the perceived cost/benefit of the decisions and the resource constraints. Methods for functionally obtaining decision probabilities from perceived cost/benefit are proposed. The treatment of high-consequence/low-probability events is discussed in terms of analysis of precursor events, and the use of sensitivity analysis is discussed. An example of a simplified model for nuclear material theft, smuggling, and illicit use is presented, and the results of this simplified model are evaluated. By attempting to model the potential distribution of nuclear material theft/smuggling events, this model increases the analytical tools available

  16. Safety analysis in support of regulatory decision marking

    International Nuclear Information System (INIS)

    Pomier Baez, L.; Troncoso Fleitas, M.; Valhuerdi Debesa, C.; Valle Cepero, R.; Hernandez, J.L.

    1996-01-01

    Features of different safety analysis techniques by means of calculation thermohydraulic a probabilistic and severe accidents used in the safety assessment, as well as the development of these techniques in Cuba and their use in support of regulatory decision making are presented

  17. Assessment of major nuclear technologies with decision and risk analysis

    International Nuclear Information System (INIS)

    Winterfeldt, D. von

    1995-01-01

    Selecting technologies for major nuclear programs involves several complexities, including multiple stakeholders, multiple conflicting objectives, uncertainties, and risk. In addition, the programmatic risks related to the schedule, cost, and performance of these technologies often become major issues in the selection process. This paper describes a decision analysis approach for addressing these complexities in a logical manner

  18. Multi-criteria decision analysis integrated with GIS for radio ...

    African Journals Online (AJOL)

    Multi-criteria decision analysis integrated with GIS for radio astronomical observatory site selection in peninsular of Malaysia. R Umar, Z.Z. Abidin, Z.A. Ibrahim, M.K.A. Kamarudin, S.N. Hazmin, A Endut, H Juahir ...

  19. Decision analysis and rational countermeasures in radiation protection

    International Nuclear Information System (INIS)

    Sinkko, K.

    1991-09-01

    During the past few years several international organizations (ICRP, IAEA, OECD/NEA), in revising their radiation protection principles, have emphasized the importance of the rationalization and planning of intervention after a nuclear accident. An accident itself and the introduction of protective action entails risks to the people affected, monetary costs and social disruption. Thus protective actions, often including objectives which are difficult to control simultaneously, cannot be undertaken without careful contemplation and consideration of the essential consequences of decisions. Often during an accident there is not enough time for careful consideration. Decision analysis is an analyzing and thought guiding method for the definition of objectives and comparison of options. It is an appropriate methodology assisting in rendering explicit and apparent all factors involved and evaluating their relative importance. The planning of intervention with the help of decision analysis is portion of the preparation for accident situations. In this report one of the techniques of decision analysis, multi-attribute utility analysis, is presented, as concerns its application in planning protective actions in the event of radiation accidents. (orig.)

  20. Decision analysis of Hanford underground storage tank waste retrieval systems

    International Nuclear Information System (INIS)

    Merkhofer, M.W.; Bitz, D.A.; Berry, D.L.; Jardine, L.J.

    1994-05-01

    A decision analysis approach has been proposed for planning the retrieval of hazardous, radioactive, and mixed wastes from underground storage tanks. This paper describes the proposed approach and illustrates its application to the single-shell storage tanks (SSTs) at Hanford, Washington

  1. Development of a decision analytic model to support decision making and risk communication about thrombolytic treatment.

    Science.gov (United States)

    McMeekin, Peter; Flynn, Darren; Ford, Gary A; Rodgers, Helen; Gray, Jo; Thomson, Richard G

    2015-11-11

    Individualised prediction of outcomes can support clinical and shared decision making. This paper describes the building of such a model to predict outcomes with and without intravenous thrombolysis treatment following ischaemic stroke. A decision analytic model (DAM) was constructed to establish the likely balance of benefits and risks of treating acute ischaemic stroke with thrombolysis. Probability of independence, (modified Rankin score mRS ≤ 2), dependence (mRS 3 to 5) and death at three months post-stroke was based on a calibrated version of the Stroke-Thrombolytic Predictive Instrument using data from routinely treated stroke patients in the Safe Implementation of Treatments in Stroke (SITS-UK) registry. Predictions in untreated patients were validated using data from the Virtual International Stroke Trials Archive (VISTA). The probability of symptomatic intracerebral haemorrhage in treated patients was incorporated using a scoring model from Safe Implementation of Thrombolysis in Stroke-Monitoring Study (SITS-MOST) data. The model predicts probabilities of haemorrhage, death, independence and dependence at 3-months, with and without thrombolysis, as a function of 13 patient characteristics. Calibration (and inclusion of additional predictors) of the Stroke-Thrombolytic Predictive Instrument (S-TPI) addressed issues of under and over prediction. Validation with VISTA data confirmed that assumptions about treatment effect were just. The C-statistics for independence and death in treated patients in the DAM were 0.793 and 0.771 respectively, and 0.776 for independence in untreated patients from VISTA. We have produced a DAM that provides an estimation of the likely benefits and risks of thrombolysis for individual patients, which has subsequently been embedded in a computerised decision aid to support better decision-making and informed consent.

  2. Multi-criteria decision model for retrofitting existing buildings

    Directory of Open Access Journals (Sweden)

    M. D. Bostenaru Dan

    2004-01-01

    Full Text Available Decision is an element in the risk management process. In this paper the way how science can help in decision making and implementation for retrofitting buildings in earthquake prone urban areas is investigated. In such interventions actors from various spheres are involved. Their interests range among minimising the intervention for maximal preservation or increasing it for seismic safety. Research was conducted to see how to facilitate collaboration between these actors. A particular attention was given to the role of time in actors' preferences. For this reason, on decision level, both the processural and the personal dimension of risk management, the later seen as a task, were considered. A systematic approach was employed to determine the functional structure of a participative decision model. Three layers on which actors implied in this multi-criteria decision problem interact were identified: town, building and element. So-called 'retrofit elements' are characteristic bearers in the architectural survey, engineering simulations, costs estimation and define the realms perceived by the inhabitants. This way they represent an interaction basis for the interest groups considered in a deeper study. Such orientation means for actors' interaction were designed on other levels of intervention as well. Finally, an 'experiment' for the implementation of the decision model is presented: a strategic plan for an urban intervention towards reduction of earthquake hazard impact through retrofitting. A systematic approach proves thus to be a very good communication basis among the participants in the seismic risk management process. Nevertheless, it can only be applied in later phases (decision, implementation, control only, since it serves verifying and improving solution and not developing the concept. The 'retrofit elements' are a typical example of the detailing degree reached in the retrofit design plans in these phases.

  3. Multi-criteria decision model for retrofitting existing buildings

    Science.gov (United States)

    Bostenaru Dan, M. D.

    2004-08-01

    Decision is an element in the risk management process. In this paper the way how science can help in decision making and implementation for retrofitting buildings in earthquake prone urban areas is investigated. In such interventions actors from various spheres are involved. Their interests range among minimising the intervention for maximal preservation or increasing it for seismic safety. Research was conducted to see how to facilitate collaboration between these actors. A particular attention was given to the role of time in actors' preferences. For this reason, on decision level, both the processural and the personal dimension of risk management, the later seen as a task, were considered. A systematic approach was employed to determine the functional structure of a participative decision model. Three layers on which actors implied in this multi-criteria decision problem interact were identified: town, building and element. So-called 'retrofit elements' are characteristic bearers in the architectural survey, engineering simulations, costs estimation and define the realms perceived by the inhabitants. This way they represent an interaction basis for the interest groups considered in a deeper study. Such orientation means for actors' interaction were designed on other levels of intervention as well. Finally, an 'experiment' for the implementation of the decision model is presented: a strategic plan for an urban intervention towards reduction of earthquake hazard impact through retrofitting. A systematic approach proves thus to be a very good communication basis among the participants in the seismic risk management process. Nevertheless, it can only be applied in later phases (decision, implementation, control) only, since it serves verifying and improving solution and not developing the concept. The 'retrofit elements' are a typical example of the detailing degree reached in the retrofit design plans in these phases.

  4. The potential for meta-analysis to support decision analysis in ecology.

    Science.gov (United States)

    Mengersen, Kerrie; MacNeil, M Aaron; Caley, M Julian

    2015-06-01

    Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable expectations that benefits would be derived from doing so. Meta-analysis combines information from multiple studies to provide more accurate parameter estimates and to reduce the uncertainty surrounding them. Decision analysis involves selecting among alternative choices using statistical information that helps to shed light on the uncertainties involved. By linking meta-analysis to decision analysis, improved decisions can be made, with quantification of the costs and benefits of alternate decisions supported by a greater density of information. Here, we briefly review concepts of both meta-analysis and decision analysis, illustrating the natural linkage between them and the benefits from explicitly linking one to the other. We discuss some examples in which this linkage has been exploited in the medical arena and how improvements in precision and reduction of structural uncertainty inherent in a meta-analysis can provide substantive improvements to decision analysis outcomes by reducing uncertainty in expected loss and maximising information from across studies. We then argue that these significant benefits could be translated to ecology, in particular to the problem of making optimal ecological decisions in the face of uncertainty. Copyright © 2013 John Wiley & Sons, Ltd.

  5. Overcoming barriers to development of cooperative medical decision support models.

    Science.gov (United States)

    Hudson, Donna L; Cohen, Maurice E

    2012-01-01

    Attempts to automate the medical decision making process have been underway for the at least fifty years, beginning with data-based approaches that relied chiefly on statistically-based methods. Approaches expanded to include knowledge-based systems, both linear and non-linear neural networks, agent-based systems, and hybrid methods. While some of these models produced excellent results none have been used extensively in medical practice. In order to move these methods forward into practical use, a number of obstacles must be overcome, including validation of existing systems on large data sets, development of methods for including new knowledge as it becomes available, construction of a broad range of decision models, and development of non-intrusive methods that allow the physician to use these decision aids in conjunction with, not instead of, his or her own medical knowledge. None of these four requirements will come easily. A cooperative effort among researchers, including practicing MDs, is vital, particularly as more information on diseases and their contributing factors continues to expand resulting in more parameters than the human decision maker can process effectively. In this article some of the basic structures that are necessary to facilitate the use of an automated decision support system are discussed, along with potential methods for overcoming existing barriers.

  6. Modelling human emotions for tactical decision-making games

    NARCIS (Netherlands)

    Visschedijk, G.; Lazonder, Adrianus W.; van der Hulst, A.; Vink, N.; Leemkuil, Hendrik H.

    2013-01-01

    The training of tactical decision making increasingly occurs through serious computer games. A challenging aspect of designing such games is the modelling of human emotions. Two studies were performed to investigate the relation between fidelity and human emotion recognition in virtual human

  7. Modelling human emotions for tactical decision-making games

    NARCIS (Netherlands)

    Visschedijk, G.C.; Lazonder, A.W.; Hulst, A.H. van der; Vink, N.; Leemkuil, H.

    2013-01-01

    The training of tactical decision making increasingly occurs through serious computer games. A challenging aspect of designing such games is the modelling of human emotions. Two studieswere performed to investigate the relation between fidelity and human emotion recognition in virtual human

  8. Modelling Human Emotions for Tactical Decision-Making Games

    Science.gov (United States)

    Visschedijk, Gillian C.; Lazonder, Ard W.; van der Hulst, Anja; Vink, Nathalie; Leemkuil, Henny

    2013-01-01

    The training of tactical decision making increasingly occurs through serious computer games. A challenging aspect of designing such games is the modelling of human emotions. Two studies were performed to investigate the relation between fidelity and human emotion recognition in virtual human characters. Study 1 compared five versions of a virtual…

  9. A Behavioral Decision Making Modeling Approach Towards Hedging Services

    NARCIS (Netherlands)

    Pennings, J.M.E.; Candel, M.J.J.M.; Egelkraut, T.M.

    2003-01-01

    This paper takes a behavioral approach toward the market for hedging services. A behavioral decision-making model is developed that provides insight into how and why owner-managers decide the way they do regarding hedging services. Insight into those choice processes reveals information needed by

  10. Making Risk Models Operational for Situational Awareness and Decision Support

    International Nuclear Information System (INIS)

    Paulson, P.R.; Coles, G.; Shoemaker, S.

    2012-01-01

    We present CARIM, a decision support tool to aid in the evaluation of plans for converting control systems to digital instruments. The model provides the capability to optimize planning and resource allocation to reduce risk from multiple safety and economic perspectives. (author)

  11. Approach to decision modeling for an ignition test reactor

    International Nuclear Information System (INIS)

    Howland, H.R.; Varljen, T.C.

    1977-01-01

    A comparison matrix decision model is applied to candidates for a D-T ignition tokamak (TNS), including assessment of semi-quantifiable or judgemental factors as well as quantitative ones. The results show that TNS is mission-sensitive with a choice implied between near-term achievability and reactor technology

  12. The limitations of applying rational decision-making models to ...

    African Journals Online (AJOL)

    The aim of this paper is to show the limitations of rational decision-making models as applied to child spacing and more specifically to the use of modern methods of contraception. In the light of factors known to influence low uptake of child spacing services in other African countries, suggestions are made to explain the ...

  13. Derivation of Monotone Decision Models from Non-Monotone Data

    NARCIS (Netherlands)

    Daniëls, H.A.M.; Velikova, M.V.

    2003-01-01

    The objective of data mining is the extraction of knowledge from databases. In practice, one often encounters difficulties with models that are constructed purely by search, without incorporation of knowledge about the domain of application.In economic decision making such as credit loan approval or

  14. A safety decision analysis for Saudi Arabian nuclear research facility

    International Nuclear Information System (INIS)

    Abulfaraj, W.H.; Abdul-Fattah, A.F.

    1985-01-01

    Establishment of a nuclear research facility should be the first step in planning for introducing the nuclear energy to Saudi Arabia. The fuzzy set decision theory is selected among different decision theories to be applied for this analysis. Four research reactors from USA are selected for the present study. The IFDA computer code, based on the fuzzy set theory is applied. Results reveal that the FNR reactor is the best alternative for the case of Saudi Arabian nuclear research facility, and MITR is the second best. 17 refs

  15. Translational Models of Gambling-Related Decision-Making.

    Science.gov (United States)

    Winstanley, Catharine A; Clark, Luke

    Gambling is a harmless, recreational pastime that is ubiquitous across cultures. However, for some, gambling becomes a maladaptive and compulsive, and this syndrome is conceptualized as a behavioural addiction. Laboratory models that capture the key cognitive processes involved in gambling behaviour, and that can be translated across species, have the potential to make an important contribution to both decision neuroscience and the study of addictive disorders. The Iowa gambling task has been widely used to assess human decision-making under uncertainty, and this paradigm can be successfully modelled in rodents. Similar neurobiological processes underpin choice behaviour in humans and rats, and thus, a preference for the disadvantageous "high-risk, high-reward" options may reflect meaningful vulnerability for mental health problems. However, the choice behaviour operationalized by these tasks does not necessarily approximate the vulnerability to gambling disorder (GD) per se. We consider a number of psychological challenges that apply to modelling gambling in a translational way, and evaluate the success of the existing models. Heterogeneity in the structure of gambling games, as well as in the motivations of individuals with GD, is highlighted. The potential issues with extrapolating too directly from established animal models of drug dependency are discussed, as are the inherent difficulties in validating animal models of GD in the absence of any approved treatments for GD. Further advances in modelling the cognitive biases endemic in human decision-making, which appear to be exacerbated in GD, may be a promising line of research.

  16. Rigorously testing multialternative decision field theory against random utility models.

    Science.gov (United States)

    Berkowitsch, Nicolas A J; Scheibehenne, Benjamin; Rieskamp, Jörg

    2014-06-01

    Cognitive models of decision making aim to explain the process underlying observed choices. Here, we test a sequential sampling model of decision making, multialternative decision field theory (MDFT; Roe, Busemeyer, & Townsend, 2001), on empirical grounds and compare it against 2 established random utility models of choice: the probit and the logit model. Using a within-subject experimental design, participants in 2 studies repeatedly choose among sets of options (consumer products) described on several attributes. The results of Study 1 showed that all models predicted participants' choices equally well. In Study 2, in which the choice sets were explicitly designed to distinguish the models, MDFT had an advantage in predicting the observed choices. Study 2 further revealed the occurrence of multiple context effects within single participants, indicating an interdependent evaluation of choice options and correlations between different context effects. In sum, the results indicate that sequential sampling models can provide relevant insights into the cognitive process underlying preferential choices and thus can lead to better choice predictions. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  17. A Dynamic Model for Decision Making During Memory Retrieval

    Science.gov (United States)

    2015-10-26

    a  knowledge  task  (pseudo-­‐ lexical  decision),  a  perceptual  task  (perceptual  identification),  and  an  episodic... lexical decision), a perceptual task (perceptual identification), and an episodic recognition task (recognition memory for occurrence of a test item...Topics in Cognitive Science, 4(1), 135-150. Cox, G. E., Kachergis, G., and Shiffrin, R. M. (2012). Gaussian process regression for trajectory analysis . In

  18. A public health decision support system model using reasoning methods.

    Science.gov (United States)

    Mera, Maritza; González, Carolina; Blobel, Bernd

    2015-01-01

    Public health programs must be based on the real health needs of the population. However, the design of efficient and effective public health programs is subject to availability of information that can allow users to identify, at the right time, the health issues that require special attention. The objective of this paper is to propose a case-based reasoning model for the support of decision-making in public health. The model integrates a decision-making process and case-based reasoning, reusing past experiences for promptly identifying new population health priorities. A prototype implementation of the model was performed, deploying the case-based reasoning framework jColibri. The proposed model contributes to solve problems found today when designing public health programs in Colombia. Current programs are developed under uncertain environments, as the underlying analyses are carried out on the basis of outdated and unreliable data.

  19. Modelling and development of an analysis and decision component for a user dependent impact of efficiency; Modellierung und Entwicklung einer Analyse- und Entscheidungskomponente fuer nutzerabhaengige Effizienzbeeinflussung

    Energy Technology Data Exchange (ETDEWEB)

    Jahn, Franziska [Westsaechsische Hochschule Zwickau (Germany)

    2010-07-01

    The contribution under consideration reports on a solution of the software-based expansion of an existing Smart Home System (Gira FacilityServer) for the user-dependent influence on efficiency. The first section of this contribution describes the reasons for such a system and explains at which position the Gira FacilityServer is to be expanded. Then the necessary individual operations and applied methods are illustrated which preferably are prerequisite for modeling and developing of such a system. The third section presents the current results from the concept to the software technological realization with regard to the project progress. Afterwards, the specific project results are summarized, The sustainability of these projectresults are considered.

  20. Make or buy decision model with multi-stage manufacturing process and supplier imperfect quality

    Science.gov (United States)

    Pratama, Mega Aria; Rosyidi, Cucuk Nur

    2017-11-01

    This research develops an make or buy decision model considering supplier imperfect quality. This model can be used to help companies make the right decision in case of make or buy component with the best quality and the least cost in multistage manufacturing process. The imperfect quality is one of the cost component that must be minimizing in this model. Component with imperfect quality, not necessarily defective. It still can be rework and used for assembly. This research also provide a numerical example and sensitivity analysis to show how the model work. We use simulation and help by crystal ball to solve the numerical problem. The sensitivity analysis result show that percentage of imperfect generally not affect to the model significantly, and the model is not sensitive to changes in these parameters. This is because the imperfect cost are smaller than overall total cost components.

  1. A decision-making process model of young online shoppers.

    Science.gov (United States)

    Lin, Chin-Feng; Wang, Hui-Fang

    2008-12-01

    Based on the concepts of brand equity, means-end chain, and Web site trust, this study proposes a novel model called the consumption decision-making process of adolescents (CDMPA) to understand adolescents' Internet consumption habits and behavioral intention toward particular sporting goods. The findings of the CDMPA model can help marketers understand adolescents' consumption preferences and habits for developing effective Internet marketing strategies.

  2. Microseismic Monitoring Design Optimization Based on Multiple Criteria Decision Analysis

    Science.gov (United States)

    Kovaleva, Y.; Tamimi, N.; Ostadhassan, M.

    2017-12-01

    Borehole microseismic monitoring of hydraulic fracture treatments of unconventional reservoirs is a widely used method in the oil and gas industry. Sometimes, the quality of the acquired microseismic data is poor. One of the reasons for poor data quality is poor survey design. We attempt to provide a comprehensive and thorough workflow, using multiple criteria decision analysis (MCDA), to optimize planning micriseismic monitoring. So far, microseismic monitoring has been used extensively as a powerful tool for determining fracture parameters that affect the influx of formation fluids into the wellbore. The factors that affect the quality of microseismic data and their final results include average distance between microseismic events and receivers, complexity of the recorded wavefield, signal-to-noise ratio, data aperture, etc. These criteria often conflict with each other. In a typical microseismic monitoring, those factors should be considered to choose the best monitoring well(s), optimum number of required geophones, and their depth. We use MDCA to address these design challenges and develop a method that offers an optimized design out of all possible combinations to produce the best data acquisition results. We believe that this will be the first research to include the above-mentioned factors in a 3D model. Such a tool would assist companies and practicing engineers in choosing the best design parameters for future microseismic projects.

  3. A decision modeling for phasor measurement unit location selection in smart grid systems

    Science.gov (United States)

    Lee, Seung Yup

    As a key technology for enhancing the smart grid system, Phasor Measurement Unit (PMU) provides synchronized phasor measurements of voltages and currents of wide-area electric power grid. With various benefits from its application, one of the critical issues in utilizing PMUs is the optimal site selection of units. The main aim of this research is to develop a decision support system, which can be used in resource allocation task for smart grid system analysis. As an effort to suggest a robust decision model and standardize the decision modeling process, a harmonized modeling framework, which considers operational circumstances of component, is proposed in connection with a deterministic approach utilizing integer programming. With the results obtained from the optimal PMU placement problem, the advantages and potential that the harmonized modeling process possesses are assessed and discussed.

  4. Decision-making in rectal and colorectal cancer: systematic review and qualitative analysis of surgeons' preferences.

    Science.gov (United States)

    Broc, Guillaume; Gana, Kamel; Denost, Quentin; Quintard, Bruno

    2017-04-01

    Surgeons are experiencing difficulties implementing recommendations not only owing to incomplete, confusing or conflicting information but also to the increasing involvement of patients in decisions relating to their health. This study sought to establish which common factors including heuristic factors guide surgeons' decision-making in colon and rectal cancers. We conducted a systematic literature review of surgeons' decision-making factors related to colon and rectal cancer treatment. Eleven of 349 identified publications were eligible for data analyses. Using the IRaMuTeQ (Interface of R for the Multidimensional Analyses of Texts and Questionnaire), we carried out a qualitative analysis of the significant factors collected in the studies reviewed. Several validation procedures were applied to control the robustness of the findings. Five categories of factors (i.e. patient, surgeon, treatment, tumor and organizational cues) were found to influence surgeons' decision-making. Specifically, all decision criteria including biomedical (e.g. tumor information) and heuristic (e.g. surgeons' dispositional factors) criteria converged towards the factor 'age of patient' in the similarity analysis. In the light of the results, we propose an explanatory model showing the impact of heuristic criteria on medical issues (i.e. diagnosis, prognosis, treatment features, etc.) and thus on decision-making. Finally, the psychosocial complexity involved in decision-making is discussed and a medico-psycho-social grid for use in multidisciplinary meetings is proposed.

  5. Using the Situated Clinical Decision-Making framework to guide analysis of nurses' clinical decision-making.

    Science.gov (United States)

    Gillespie, Mary

    2010-11-01

    Nurses' clinical decision-making is a complex process that holds potential to influence the quality of care provided and patient outcomes. The evolution of nurses' decision-making that occurs with experience has been well documented. In addition, literature includes numerous strategies and approaches purported to support development of nurses' clinical decision-making. There has been, however, significantly less attention given to the process of assessing nurses' clinical decision-making and novice clinical educators are often challenged with knowing how to best support nurses and nursing students in developing their clinical decision-making capacity. The Situated Clinical Decision-Making framework is presented for use by clinical educators: it provides a structured approach to analyzing nursing students' and novice nurses' decision-making in clinical nursing practice, assists educators in identifying specific issues within nurses' clinical decision-making, and guides selection of relevant strategies to support development of clinical decision-making. A series of questions is offered as a guide for clinical educators when assessing nurses' clinical decision-making. The discussion presents key considerations related to analysis of various decision-making components, including common sources of challenge and errors that may occur within nurses' clinical decision-making. An exemplar illustrates use of the framework and guiding questions. Implications of this approach for selection of strategies that support development of clinical decision-making are highlighted. Copyright © 2010 Elsevier Ltd. All rights reserved.

  6. Immunizing Children: A Qualitative Analysis of Future Parental Decision Making.

    Science.gov (United States)

    Espeleta, Hannah C; Beasley, Lana O; Ridings, Leigh E; Smith, Tyler J; Shields, Jennifer D

    2017-10-01

    Vaccinations are considered one of public health's greatest accomplishments. Despite evidence for vaccine effectiveness, uptake levels are still well below the Centers for Disease Control and Prevention's guidelines. The immunization decision-making process for parents is complex and depends on factors associated with knowledge and experiences. This qualitative study sought to expand on a previous decision-making model for immunizations by examining how individuals receive vaccination information, determining the role of experience in influencing decisions, and understanding how young adults might locate vaccination information in the future. Three focus groups were conducted with 29 undergraduate students without children. Results suggest that young adults exhibit an awareness of information regarding vaccine use and effectiveness, value doctor opinions and recommendations, and desire more robust research on vaccinations. Implications of these results include the importance of (1) disseminating vaccination education to young adults, (2) enhancing consistency/trust between medical professionals and youth, and (3) expanding public policy to increase vaccine uptake.

  7. Modelling Financial-Accounting Decisions by Means of OLAP Tools

    Directory of Open Access Journals (Sweden)

    Diana Elena CODREAN

    2011-03-01

    Full Text Available At present, one can say that a company’s good running largely depends on the information quantity and quality it relies on when making decisions. The information needed to underlie decisions and be obtained due to the existence of a high-performing information system which makes it possible for the data to be shown quickly, synthetically and truly, also providing the opportunity for complex analyses and predictions. In such circumstances, computerized accounting systems, too, have grown their complexity by means of data analyzing information solutions such as OLAP and Data Mining which help perform a multidimensional analysis of financial-accounting data, potential frauds can be detected and data hidden information can be revealed, trends for certain indicators can be set up, therefore ensuring useful information to a company’s decision making.

  8. Multivariate analysis of flow cytometric data using decision trees.

    Science.gov (United States)

    Simon, Svenja; Guthke, Reinhard; Kamradt, Thomas; Frey, Oliver

    2012-01-01

    Characterization of the response of the host immune system is important in understanding the bidirectional interactions between the host and microbial pathogens. For research on the host site, flow cytometry has become one of the major tools in immunology. Advances in technology and reagents allow now the simultaneous assessment of multiple markers on a single cell level generating multidimensional data sets that require multivariate statistical analysis. We explored the explanatory power of the supervised machine learning method called "induction of decision trees" in flow cytometric data. In order to examine whether the production of a certain cytokine is depended on other cytokines, datasets from intracellular staining for six cytokines with complex patterns of co-expression were analyzed by induction of decision trees. After weighting the data according to their class probabilities, we created a total of 13,392 different decision trees for each given cytokine with different parameter settings. For a more realistic estimation of the decision trees' quality, we used stratified fivefold cross validation and chose the "best" tree according to a combination of different quality criteria. While some of the decision trees reflected previously known co-expression patterns, we found that the expression of some cytokines was not only dependent on the co-expression of others per se, but was also dependent on the intensity of expression. Thus, for the first time we successfully used induction of decision trees for the analysis of high dimensional flow cytometric data and demonstrated the feasibility of this method to reveal structural patterns in such data sets.

  9. Decision Making in Nursing Practice: A Concept Analysis.

    Science.gov (United States)

    Johansen, Mary L; O'Brien, Janice L

    2016-01-01

    The study aims to gain an understanding of the concept of decision making as it relates to the nurse practice environment. Rodgers' evolutionary method on concept analysis was used as a framework for the study of the concept. Articles from 1952 to 2014 were reviewed from PsycINFO, Medline, Cumulative Index to Nursing and Allied Health Literature (CINAHL), JSTOR, PubMed, and Science Direct. Findings suggest that decision making in the nurse practice environment is a complex process, integral to the nursing profession. The definition of decision making, and the attributes, antecedents, and consequences, are discussed. Contextual factors that influence the process are also discussed. An exemplar is presented to illustrate the concept. Decision making in the nurse practice environment is a dynamic conceptual process that may affect patient outcomes. Nurses need to call upon ways of knowing to make sound decisions and should be self-reflective in order to develop the process further in the professional arena. The need for further research is discussed. © 2015 Wiley Periodicals, Inc.

  10. Using plural modeling for predicting decisions made by adaptive adversaries

    International Nuclear Information System (INIS)

    Buede, Dennis M.; Mahoney, Suzanne; Ezell, Barry; Lathrop, John

    2012-01-01

    Incorporating an appropriate representation of the likelihood of terrorist decision outcomes into risk assessments associated with weapons of mass destruction attacks has been a significant problem for countries around the world. Developing these likelihoods gets at the heart of the most difficult predictive problems: human decision making, adaptive adversaries, and adversaries about which very little is known. A plural modeling approach is proposed that incorporates estimates of all critical uncertainties: who is the adversary and what skills and resources are available to him, what information is known to the adversary and what perceptions of the important facts are held by this group or individual, what does the adversary know about the countermeasure actions taken by the government in question, what are the adversary's objectives and the priorities of those objectives, what would trigger the adversary to start an attack and what kind of success does the adversary desire, how realistic is the adversary in estimating the success of an attack, how does the adversary make a decision and what type of model best predicts this decision-making process. A computational framework is defined to aggregate the predictions from a suite of models, based on this broad array of uncertainties. A validation approach is described that deals with a significant scarcity of data.

  11. A decision model for the risk management of hazardous processes

    International Nuclear Information System (INIS)

    Holmberg, J.E.

    1997-03-01

    A decision model for risk management of hazardous processes as an optimisation problem of a point process is formulated in the study. In the approach, the decisions made by the management are divided into three categories: (1) planned process lifetime, (2) selection of the design and, (3) operational decisions. These three controlling methods play quite different roles in the practical risk management, which is also reflected in our approach. The optimisation of the process lifetime is related to the licensing problem of the process. It provides a boundary condition for a feasible utility function that is used as the actual objective function, i.e., maximizing the process lifetime utility. By design modifications, the management can affect the inherent accident hazard rate of the process. This is usually a discrete optimisation task. The study particularly concentrates upon the optimisation of the operational strategies given a certain design and licensing time. This is done by a dynamic risk model (marked point process model) representing the stochastic process of events observable or unobservable to the decision maker. An optimal long term control variable guiding the selection of operational alternatives in short term problems is studied. The optimisation problem is solved by the stochastic quasi-gradient procedure. The approach is illustrated by a case study. (23 refs.)

  12. System for decision analysis support on complex waste management issues

    International Nuclear Information System (INIS)

    Shropshire, D.E.

    1997-01-01

    A software system called the Waste Flow Analysis has been developed and applied to complex environmental management processes for the United States Department of Energy (US DOE). The system can evaluate proposed methods of waste retrieval, treatment, storage, transportation, and disposal. Analysts can evaluate various scenarios to see the impacts to waste slows and schedules, costs, and health and safety risks. Decision analysis capabilities have been integrated into the system to help identify preferred alternatives based on a specific objectives may be to maximize the waste moved to final disposition during a given time period, minimize health risks, minimize costs, or combinations of objectives. The decision analysis capabilities can support evaluation of large and complex problems rapidly, and under conditions of variable uncertainty. The system is being used to evaluate environmental management strategies to safely disposition wastes in the next ten years and reduce the environmental legacy resulting from nuclear material production over the past forty years

  13. Procedural Personas for Player Decision Modeling and Procedural Content Generation

    DEFF Research Database (Denmark)

    Holmgård, Christoffer

    2016-01-01

    ." These methods for constructing procedural personas are then integrated with existing procedural content generation systems, acting as critics that shape the output of these systems, optimizing generated content for different personas and by extension, different kinds of players and their decision making styles......How can player models and artificially intelligent (AI) agents be useful in early-stage iterative game and simulation design? One answer may be as ways of generating synthetic play-test data, before a game or level has ever seen a player, or when the sampled amount of play test data is very low....... This thesis explores methods for creating low-complexity, easily interpretable, generative AI agents for use in game and simulation design. Based on insights from decision theory and behavioral economics, the thesis investigates how player decision making styles may be defined, operationalised, and measured...

  14. A judgment and decision-making model for plant behavior.

    Science.gov (United States)

    Karban, Richard; Orrock, John L

    2018-06-12

    Recently plant biologists have documented that plants, like animals, engage in many activities that can be considered as behaviors, although plant biologists currently lack a conceptual framework to understand these processes. Borrowing the well-established framework developed by psychologists, we propose that plant behaviors can be constructively modeled by identifying four distinct components: 1) a cue or stimulus that provides information, 2) a judgment whereby the plant perceives and processes this informative cue, 3) a decision whereby the plant chooses among several options based on their relative costs and benefits, and 4) action. Judgment for plants can be determined empirically by monitoring signaling associated with electrical, calcium, or hormonal fluxes. Decision-making can be evaluated empirically by monitoring gene expression or differential allocation of resources. We provide examples of the utility of this judgment and decision-making framework by considering cases in which plants either successfully or unsuccessfully induced resistance against attacking herbivores. Separating judgment from decision-making suggests new analytical paradigms (i.e., Bayesian methods for judgment and economic utility models for decision-making). Following this framework, we propose an experimental approach to plant behavior that explicitly manipulates the stimuli provided to plants, uses plants that vary in sensory abilities, and examines how environmental context affects plant responses. The concepts and approaches that follow from the judgment and decision-making framework can shape how we study and understand plant-herbivore interactions, biological invasions, plant responses to climate change, and the susceptibility of plants to evolutionary traps. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  15. Decision-case mix model for analyzing variation in cesarean rates.

    Science.gov (United States)

    Eldenburg, L; Waller, W S

    2001-01-01

    This article contributes a decision-case mix model for analyzing variation in c-section rates. Like recent contributions to the literature, the model systematically takes into account the effect of case mix. Going beyond past research, the model highlights differences in physician decision making in response to obstetric factors. Distinguishing the effects of physician decision making and case mix is important in understanding why c-section rates vary and in developing programs to effect change in physician behavior. The model was applied to a sample of deliveries at a hospital where physicians exhibited considerable variation in their c-section rates. Comparing groups with a low versus high rate, the authors' general conclusion is that the difference in physician decision tendencies (to perform a c-section), in response to specific obstetric factors, is at least as important as case mix in explaining variation in c-section rates. The exact effects of decision making versus case mix depend on how the model application defines the obstetric condition of interest and on the weighting of deliveries by their estimated "risk of Cesarean." The general conclusion is supported by an additional analysis that uses the model's elements to predict individual physicians' annual c-section rates.

  16. Sensitivity analysis for decision-making using the MORE method-A Pareto approach

    International Nuclear Information System (INIS)

    Ravalico, Jakin K.; Maier, Holger R.; Dandy, Graeme C.

    2009-01-01

    Integrated Assessment Modelling (IAM) incorporates knowledge from different disciplines to provide an overarching assessment of the impact of different management decisions. The complex nature of these models, which often include non-linearities and feedback loops, requires special attention for sensitivity analysis. This is especially true when the models are used to form the basis of management decisions, where it is important to assess how sensitive the decisions being made are to changes in model parameters. This research proposes an extension to the Management Option Rank Equivalence (MORE) method of sensitivity analysis; a new method of sensitivity analysis developed specifically for use in IAM and decision-making. The extension proposes using a multi-objective Pareto optimal search to locate minimum combined parameter changes that result in a change in the preferred management option. It is demonstrated through a case study of the Namoi River, where results show that the extension to MORE is able to provide sensitivity information for individual parameters that takes into account simultaneous variations in all parameters. Furthermore, the increased sensitivities to individual parameters that are discovered when joint parameter variation is taken into account shows the importance of ensuring that any sensitivity analysis accounts for these changes.

  17. SEDIMENT ANALYSIS NETWORK FOR DECISION SUPPORT (SANDS) LANDSAT GEOLOGICAL SURVEY OF AL (GSA) ANALYSIS V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The Sediment Analysis Network for Decision Support (SANDS) Landsat Geological Survey of AL (GSA) Analysis dataset analyzed changes in the coastal shoreline and...

  18. Characterizing the Buyer Decision Process: the ZMOT model in Chile’s technology sector

    Directory of Open Access Journals (Sweden)

    Manuel Escobar Farfán

    2017-06-01

    Full Text Available This study presents an updated application model that identifies the intervening factors in the buyer decision process. In traditional research, the consumer is said to confront two moments of truth before making the decision to buy: first, when encountering the gondola, and then again while experiencing the product. Nevertheless, innovations in information technology have modified this traditional view to include the “Zero Moment of Truth”, known as ZMOT, a name popularized by Google. This analysis is based on the concept of the Zero Moment of Truth which relates to the process that consumers live prior to the purchase decision in which they gather information about the product or service. This study is justified by the absence of research on the ZMOT concept in Chile. To determine the factors involved in the purchase decision, a quantitative methodology was used, through the application of a survey that analyzed three perspectives: the influencing factors during the purchase decision, the activities carried out during the ZMOT, and, finally, the actions carried out after the completion of the purchase and information that will serve for future buyers is gathered. With the data obtained, an exploratory factor analysis was carried out, generating a preliminary multi-dimensional model to describe the factors in the buyer decision process during the information and experience gathering phase known as ZMOT.

  19. Computer-based decision making in medicine : A model for surgery of colorectal liver metastases

    NARCIS (Netherlands)

    Langenhoff, B S; Krabbe, P F M; Ruers, T J M

    2007-01-01

    AIMS: Seeking the best available treatment for patients with colorectal liver metastases may be complex due to the interpretation of many variables. In this study conjoint analysis is used to develop a decision model to help clinicians selecting patients eligible for surgery of liver metastases.

  20. Which Cooperative Ownership Model Performs Better? A Financial-Decision Aid Approach

    NARCIS (Netherlands)

    Kalogeras, N.; Pennings, J.M.E.; Benos, T.; Doumpos, M.

    2013-01-01

    In this article the financial/ownership structures of agribusiness cooperatives are analyzed to examine whether new cooperative models perform better than the more traditional ones. The assessment procedure introduces a new financial decision-aid approach, which is based on data-analysis techniques

  1. A New Group Decision Model Based on Grey-Intuitionistic Fuzzy-ELECTRE and VIKOR for Contractor Assessment Problem

    Directory of Open Access Journals (Sweden)

    Hassan Hashemi

    2018-05-01

    Full Text Available This study introduces a new decision model with multi-criteria analysis by a group of decision makers (DMs with intuitionistic fuzzy sets (IFSs. The presented model depends on a new integration of IFSs theory, ELECTRE and VIKOR along with grey relational analysis (GRA. To portray uncertain real-life situations and take account of complex decision problem, multi-criteria group decision-making (MCGDM model by totally unknown importance are introduced with IF-setting. Hence, a weighting method depended on Entropy and IFSs, is developed to present the weights of DMs and evaluation factors. A new ranking approach is provided for prioritizing the alternatives. To indicate the applicability of the presented new decision model, an industrial application for assessing contractors in the construction industry is given and discussed from the recent literature.

  2. The ATLAS Analysis Model

    CERN Multimedia

    Amir Farbin

    The ATLAS Analysis Model is a continually developing vision of how to reconcile physics analysis requirements with the ATLAS offline software and computing model constraints. In the past year this vision has influenced the evolution of the ATLAS Event Data Model, the Athena software framework, and physics analysis tools. These developments, along with the October Analysis Model Workshop and the planning for CSC analyses have led to a rapid refinement of the ATLAS Analysis Model in the past few months. This article introduces some of the relevant issues and presents the current vision of the future ATLAS Analysis Model. Event Data Model The ATLAS Event Data Model (EDM) consists of several levels of details, each targeted for a specific set of tasks. For example the Event Summary Data (ESD) stores calorimeter cells and tracking system hits thereby permitting many calibration and alignment tasks, but will be only accessible at particular computing sites with potentially large latency. In contrast, the Analysis...

  3. MEETING IN CHICAGO: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND ENVIRONMENTAL RISK ASSESSMENT

    Science.gov (United States)

    Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

  4. SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING AND RISK ASSESSMENT (SLIDE PRESENTATION)

    Science.gov (United States)

    Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

  5. MEETING IN CZECH REPUBLIC: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND RISK ASSESSMENT

    Science.gov (United States)

    Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

  6. Beyond utilitarianism: a method for analyzing competing ethical principles in a decision analysis of liver transplantation.

    Science.gov (United States)

    Volk, Michael L; Lok, Anna S F; Ubel, Peter A; Vijan, Sandeep

    2008-01-01

    The utilitarian foundation of decision analysis limits its usefulness for many social policy decisions. In this study, the authors examine a method to incorporate competing ethical principles in a decision analysis of liver transplantation for a patient with acute liver failure (ALF). A Markov model was constructed to compare the benefit of transplantation for a patient with ALF versus the harm caused to other patients on the waiting list and to determine the lowest acceptable 5-y posttransplant survival for the ALF patient. The weighting of the ALF patient and other patients was then adjusted using a multiattribute variable incorporating utilitarianism, urgency, and other principles such as fair chances. In the base-case analysis, the strategy of transplanting the ALF patient resulted in a 0.8% increase in the risk of death and a utility loss of 7.8 quality-adjusted days of life for each of the other patients on the waiting list. These harms cumulatively outweighed the benefit of transplantation for an ALF patient having a posttransplant survival of less than 48% at 5 y. However, the threshold for an acceptable posttransplant survival for the ALF patient ranged from 25% to 56% at 5 y, depending on the ethical principles involved. The results of the decision analysis vary depending on the ethical perspective. This study demonstrates how competing ethical principles can be numerically incorporated in a decision analysis.

  7. Implementing parallel spreadsheet models for health policy decisions: The impact of unintentional errors on model projections.

    Science.gov (United States)

    Bailey, Stephanie L; Bono, Rose S; Nash, Denis; Kimmel, April D

    2018-01-01

    Spreadsheet software is increasingly used to implement systems science models informing health policy decisions, both in academia and in practice where technical capacity may be limited. However, spreadsheet models are prone to unintentional errors that may not always be identified using standard error-checking techniques. Our objective was to illustrate, through a methodologic case study analysis, the impact of unintentional errors on model projections by implementing parallel model versions. We leveraged a real-world need to revise an existing spreadsheet model designed to inform HIV policy. We developed three parallel versions of a previously validated spreadsheet-based model; versions differed by the spreadsheet cell-referencing approach (named single cells; column/row references; named matrices). For each version, we implemented three model revisions (re-entry into care; guideline-concordant treatment initiation; immediate treatment initiation). After standard error-checking, we identified unintentional errors by comparing model output across the three versions. Concordant model output across all versions was considered error-free. We calculated the impact of unintentional errors as the percentage difference in model projections between model versions with and without unintentional errors, using +/-5% difference to define a material error. We identified 58 original and 4,331 propagated unintentional errors across all model versions and revisions. Over 40% (24/58) of original unintentional errors occurred in the column/row reference model version; most (23/24) were due to incorrect cell references. Overall, >20% of model spreadsheet cells had material unintentional errors. When examining error impact along the HIV care continuum, the percentage difference between versions with and without unintentional errors ranged from +3% to +16% (named single cells), +26% to +76% (column/row reference), and 0% (named matrices). Standard error-checking techniques may not

  8. Decision tree analysis in subarachnoid hemorrhage: prediction of outcome parameters during the course of aneurysmal subarachnoid hemorrhage using decision tree analysis.

    Science.gov (United States)

    Hostettler, Isabel Charlotte; Muroi, Carl; Richter, Johannes Konstantin; Schmid, Josef; Neidert, Marian Christoph; Seule, Martin; Boss, Oliver; Pangalu, Athina; Germans, Menno Robbert; Keller, Emanuela

    2018-01-19

    OBJECTIVE The aim of this study was to create prediction models for outcome parameters by decision tree analysis based on clinical and laboratory data in patients with aneurysmal subarachnoid hemorrhage (aSAH). METHODS The database consisted of clinical and laboratory parameters of 548 patients with aSAH who were admitted to the Neurocritical Care Unit, University Hospital Zurich. To examine the model performance, the cohort was randomly divided into a derivation cohort (60% [n = 329]; training data set) and a validation cohort (40% [n = 219]; test data set). The classification and regression tree prediction algorithm was applied to predict death, functional outcome, and ventriculoperitoneal (VP) shunt dependency. Chi-square automatic interaction detection was applied to predict delayed cerebral infarction on days 1, 3, and 7. RESULTS The overall mortality was 18.4%. The accuracy of the decision tree models was good for survival on day 1 and favorable functional outcome at all time points, with a difference between the training and test data sets of decision trees enables exploration of dependent variables in the context of multiple changing influences over the course of an illness. The decision tree currently generated increases awareness of the early systemic stress response, which is seemingly pertinent for prognostication.

  9. PRAGMATIST MODEL OF DECISION-MAKING IN LAW: FROM THE INSTRUMENTAL MENTALISM TO THE COMMUNICATIVE INTERSUBJECTIVITY

    Directory of Open Access Journals (Sweden)

    Mário Cesar da Silva Andrade

    2015-12-01

    Full Text Available This paper aimed to evaluate the method of making rational decision derived from the philosophy of Kant as a foundation paradigma of public decisions and, more specifically, of legal decisions. Based on the communicative action theory of Jürgen Habermas, the question is  if  the  transcendental  model  of  decision-making  meets  the  democratic  demands. Methodologically, the qualitative research was based on doctrinal sources about the theme, promoting a legal and critical analysis. Habermas' communicative bias raises the hypothesis that Kant's transcendental method, which influenced so much the theory of justice and Law, entails the adoption of an objective posture by the decision maker, something incompatible with the need for broad participation and the intersubjectivity prescribed by democracy . It was concluded that the public decision-making process must overcome the transcendental, decisionistic  and  instrumental  models,  adopting  pragmatic  model,  which  is  more intersubjective and communicative, therefore more consistente with the participatory bias of democracy.

  10. The application of the heuristic-systematic processing model to treatment decision making about prostate cancer.

    Science.gov (United States)

    Steginga, Suzanne K; Occhipinti, Stefano

    2004-01-01

    The study investigated the utility of the Heuristic-Systematic Processing Model as a framework for the investigation of patient decision making. A total of 111 men recently diagnosed with localized prostate cancer were assessed using Verbal Protocol Analysis and self-report measures. Study variables included men's use of nonsystematic and systematic information processing, desire for involvement in decision making, and the individual differences of health locus of control, tolerance of ambiguity, and decision-related uncertainty. Most men (68%) preferred that decision making be shared equally between them and their doctor. Men's use of the expert opinion heuristic was related to men's verbal reports of decisional uncertainty and having a positive orientation to their doctor and medical care; a desire for greater involvement in decision making was predicted by a high internal locus of health control. Trends were observed for systematic information processing to increase when the heuristic strategy used was negatively affect laden and when men were uncertain about the probabilities for cure and side effects. There was a trend for decreased systematic processing when the expert opinion heuristic was used. Findings were consistent with the Heuristic-Systematic Processing Model and suggest that this model has utility for future research in applied decision making about health.

  11. Identifying the decision to be supported: a review of papers from environmental modelling and software

    Science.gov (United States)

    Sojda, Richard S.; Chen, Serena H.; El Sawah, Sondoss; Guillaume, Joseph H.A.; Jakeman, A.J.; Lautenbach, Sven; McIntosh, Brian S.; Rizzoli, A.E.; Seppelt, Ralf; Struss, Peter; Voinov, Alexey; Volk, Martin

    2012-01-01

    Two of the basic tenets of decision support system efforts are to help identify and structure the decisions to be supported, and to then provide analysis in how those decisions might be best made. One example from wetland management would be that wildlife biologists must decide when to draw down water levels to optimise aquatic invertebrates as food for breeding ducks. Once such a decision is identified, a system or tool to help them make that decision in the face of current and projected climate conditions could be developed. We examined a random sample of 100 papers published from 2001-2011 in Environmental Modelling and Software that used the phrase “decision support system” or “decision support tool”, and which are characteristic of different sectors. In our review, 41% of the systems and tools related to the water resources sector, 34% were related to agriculture, and 22% to the conservation of fish, wildlife, and protected area management. Only 60% of the papers were deemed to be reporting on DSS. This was based on the papers reviewed not having directly identified a specific decision to be supported. We also report on the techniques that were used to identify the decisions, such as formal survey, focus group, expert opinion, or sole judgment of the author(s). The primary underlying modelling system, e.g., expert system, agent based model, Bayesian belief network, geographical information system (GIS), and the like was categorised next. Finally, since decision support typically should target some aspect of unstructured decisions, we subjectively determined to what degree this was the case. In only 23% of the papers reviewed, did the system appear to tackle unstructured decisions. This knowledge should be useful in helping workers in the field develop more effective systems and tools, especially by being exposed to the approaches in different, but related, disciplines. We propose that a standard blueprint for reporting on DSS be developed for

  12. Warfighter decision making performance analysis as an investment priority driver

    Science.gov (United States)

    Thornley, David J.; Dean, David F.; Kirk, James C.

    2010-04-01

    Estimating the relative value of alternative tactics, techniques and procedures (TTP) and information systems requires measures of the costs and benefits of each, and methods for combining and comparing those measures. The NATO Code of Best Practice for Command and Control Assessment explains that decision making quality would ideally be best assessed on outcomes. Lessons learned in practice can be assessed statistically to support this, but experimentation with alternate measures in live conflict is undesirable. To this end, the development of practical experimentation to parameterize effective constructive simulation and analytic modelling for system utility prediction is desirable. The Land Battlespace Systems Department of Dstl has modeled human development of situational awareness to support constructive simulation by empirically discovering how evidence is weighed according to circumstance, personality, training and briefing. The human decision maker (DM) provides the backbone of the information processing activity associated with military engagements because of inherent uncertainty associated with combat operations. To develop methods for representing the process in order to assess equipment and non-technological interventions such as training and TTPs we are developing componentized or modularized timed analytic stochastic model components and instruments as part of a framework to support quantitative assessment of intelligence production and consumption methods in a human decision maker-centric mission space. In this paper, we formulate an abstraction of the human intelligence fusion process from the Defence Science and Technology Laboratory's (Dstl's) INCIDER model to include in our framework, and synthesize relevant cost and benefit characteristics.

  13. Using multicriteria decision analysis during drug development to predict reimbursement decisions.

    Science.gov (United States)

    Williams, Paul; Mauskopf, Josephine; Lebiecki, Jake; Kilburg, Anne

    2014-01-01

    Pharmaceutical companies design clinical development programs to generate the data that they believe will support reimbursement for the experimental compound. The objective of the study was to present a process for using multicriteria decision analysis (MCDA) by a pharmaceutical company to estimate the probability of a positive recommendation for reimbursement for a new drug given drug and environmental attributes. The MCDA process included 1) selection of decisions makers who were representative of those making reimbursement decisions in a specific country; 2) two pre-workshop questionnaires to identify the most important attributes and their relative importance for a positive recommendation for a new drug; 3) a 1-day workshop during which participants undertook three tasks: i) they agreed on a final list of decision attributes and their importance weights, ii) they developed level descriptions for these attributes and mapped each attribute level to a value function, and iii) they developed profiles for hypothetical products 'just likely to be reimbursed'; and 4) use of the data from the workshop to develop a prediction algorithm based on a logistic regression analysis. The MCDA process is illustrated using case studies for three countries, the United Kingdom, Germany, and Spain. The extent to which the prediction algorithms for each country captured the decision processes for the workshop participants in our case studies was tested using a post-meeting questionnaire that asked the participants to make recommendations for a set of hypothetical products. The data collected in the case study workshops resulted in a prediction algorithm: 1) for the United Kingdom, the probability of a positive recommendation for different ranges of cost-effectiveness ratios; 2) for Spain, the probability of a positive recommendation at the national and regional levels; and 3) for Germany, the probability of a determination of clinical benefit. The results from the post

  14. A dynamic dual process model of risky decision making.

    Science.gov (United States)

    Diederich, Adele; Trueblood, Jennifer S

    2018-03-01

    Many phenomena in judgment and decision making are often attributed to the interaction of 2 systems of reasoning. Although these so-called dual process theories can explain many types of behavior, they are rarely formalized as mathematical or computational models. Rather, dual process models are typically verbal theories, which are difficult to conclusively evaluate or test. In the cases in which formal (i.e., mathematical) dual process models have been proposed, they have not been quantitatively fit to experimental data and are often silent when it comes to the timing of the 2 systems. In the current article, we present a dynamic dual process model framework of risky decision making that provides an account of the timing and interaction of the 2 systems and can explain both choice and response-time data. We outline several predictions of the model, including how changes in the timing of the 2 systems as well as time pressure can influence behavior. The framework also allows us to explore different assumptions about how preferences are constructed by the 2 systems as well as the dynamic interaction of the 2 systems. In particular, we examine 3 different possible functional forms of the 2 systems and 2 possible ways the systems can interact (simultaneously or serially). We compare these dual process models with 2 single process models using risky decision making data from Guo, Trueblood, and Diederich (2017). Using this data, we find that 1 of the dual process models significantly outperforms the other models in accounting for both choices and response times. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  15. Using decision trees and their ensembles for analysis of NIR spectroscopic data

    DEFF Research Database (Denmark)

    Kucheryavskiy, Sergey V.

    and interpretation of the models. In this presentation, we are going to discuss an applicability of decision trees based methods (including gradient boosting) for solving classification and regression tasks with NIR spectra as predictors. We will cover such aspects as evaluation, optimization and validation......Advanced machine learning methods, like convolutional neural networks and decision trees, became extremely popular in the last decade. This, first of all, is directly related to the current boom in Big data analysis, where traditional statistical methods are not efficient. According to the kaggle.......com — the most popular online resource for Big data problems and solutions — methods based on decision trees and their ensembles are most widely used for solving the problems. It can be noted that the decision trees and convolutional neural networks are not very popular in Chemometrics. One of the reasons...

  16. Decision model incorporating utility theory and measurement of social values applied to nuclear waste management

    International Nuclear Information System (INIS)

    Litchfield, J.W.; Hansen, J.V.; Beck, L.C.

    1975-07-01

    A generalized computer-based decision analysis model was developed and tested. Several alternative concepts for ultimate disposal have already been developed; however, significant research is still required before any of these can be implemented. To make a choice based on technical estimates of the costs, short-term safety, long-term safety, and accident detection and recovery requires estimating the relative importance of each of these factors or attributes. These relative importance estimates primarily involve social values and therefore vary from one individual to the next. The approach used was to sample various public groups to determine the relative importance of each of the factors to the public. These estimates of importance weights were combined in a decision analysis model with estimates, furnished by technical experts, of the degree to which each alternative concept achieves each of the criteria. This model then integrates the two separate and unique sources of information and provides the decision maker with information as to the preferences and concerns of the public as well as the technical areas within each concept which need further research. The model can rank the alternatives using sampled public opinion and techno-economic data. This model provides a decision maker with a structured approach to subdividing complex alternatives into a set of more easily considered attributes, measuring the technical performance of each alternative relative to each attribute, estimating relevant social values, and assimilating quantitative information in a rational manner to estimate total value for each alternative. Because of the explicit nature of this decision analysis, the decision maker can select a specific alternative supported by clear documentation and justification for his assumptions and estimates. (U.S.)

  17. A System Dynamics Model for Integrated Decision Making ...

    Science.gov (United States)

    EPA’s Sustainable and Healthy Communities Research Program (SHC) is conducting transdisciplinary research to inform and empower decision-makers. EPA tools and approaches are being developed to enable communities to effectively weigh and integrate human health, socioeconomic, environmental, and ecological factors into their decisions to promote community sustainability. To help achieve this goal, EPA researchers have developed systems approaches to account for the linkages among resources, assets, and outcomes managed by a community. System dynamics (SD) is a member of the family of systems approaches and provides a framework for dynamic modeling that can assist with assessing and understanding complex issues across multiple dimensions. To test the utility of such tools when applied to a real-world situation, the EPA has developed a prototype SD model for community sustainability using the proposed Durham-Orange Light Rail Project (D-O LRP) as a case study.The EPA D-O LRP SD modeling team chose the proposed D-O LRP to demonstrate that an integrated modeling approach could represent the multitude of related cross-sectoral decisions that would be made and the cascading impacts that could result from a light rail transit system connecting Durham and Chapel Hill, NC. In keeping with the SHC vision described above, the proposal for the light rail is a starting point solution for the more intractable problems of population growth, unsustainable land use, environmenta

  18. Info-gap decision theory decisions under severe uncertainty

    CERN Document Server

    Ben-Haim, Yakov

    2006-01-01

    Everyone makes decisions, but not everyone is a decision analyst. A decision analyst uses quantitative models and computational methods to formulate decision algorithms, assess decision performance, identify and evaluate options, determine trade-offs and risks, evaluate strategies for investigation, and so on. This book is written for decision analysts. The term ""decision analyst"" covers an extremely broad range of practitioners. Virtually all engineers involved in design (of buildings, machines, processes, etc.) or analysis (of safety, reliability, feasibility, etc.) are decision analysts,

  19. A Product Development Decision Model for Cockpit Weather Information Systems

    Science.gov (United States)

    Sireli, Yesim; Kauffmann, Paul; Gupta, Surabhi; Kachroo, Pushkin

    2003-01-01

    There is a significant market demand for advanced cockpit weather information products. However, it is unclear how to identify the most promising technological options that provide the desired mix of consumer requirements by employing feasible technical systems at a price that achieves market success. This study develops a unique product development decision model that employs Quality Function Deployment (QFD) and Kano's model of consumer choice. This model is specifically designed for exploration and resolution of this and similar information technology related product development problems.

  20. A Product Development Decision Model for Cockpit Weather Information System

    Science.gov (United States)

    Sireli, Yesim; Kauffmann, Paul; Gupta, Surabhi; Kachroo, Pushkin; Johnson, Edward J., Jr. (Technical Monitor)

    2003-01-01

    There is a significant market demand for advanced cockpit weather information products. However, it is unclear how to identify the most promising technological options that provide the desired mix of consumer requirements by employing feasible technical systems at a price that achieves market success. This study develops a unique product development decision model that employs Quality Function Deployment (QFD) and Kano's model of consumer choice. This model is specifically designed for exploration and resolution of this and similar information technology related product development problems.