WorldWideScience

Sample records for modeling based decision

  1. 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)

  2. 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...

  3. 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...

  4. 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.

  5. 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

  6. 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

  7. 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...

  8. 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...

  9. 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

  10. 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

  11. 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 ...

  12. 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...

  13. Agent-Based Modeling of Consumer Decision making Process Based on Power Distance and Personality

    NARCIS (Netherlands)

    Roozmand, O.; Ghasem-Aghaee, N.; Hofstede, G.J.; Nematbakhsh, M.A.; Baraani, A.; Verwaart, T.

    2011-01-01

    Simulating consumer decision making processes involves different disciplines such as: sociology, social psychology, marketing, and computer science. In this paper, we propose an agent-based conceptual and computational model of consumer decision-making based on culture, personality and human needs.

  14. Accrual based accounting implementation: An approach for modelling major decisions

    OpenAIRE

    Ratno Agriyanto; Abdul Rohman; Dwi Ratmono; Imam Ghozali

    2016-01-01

    Over the last three decades the main issues of implementation of accrual based accounting government institutions in Indonesia. Implementation of accrual based accounting in government institutions amid debate about the usefulness of accounting information for decision-making. Empirical study shows that the accrual based of accounting information on a government institution is not used for decision making. The research objective was to determine the impact of the implementation of the accrual...

  15. 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...

  16. Accrual based accounting implementation: An approach for modelling major decisions

    Directory of Open Access Journals (Sweden)

    Ratno Agriyanto

    2016-12-01

    Full Text Available Over the last three decades the main issues of implementation of accrual based accounting government institutions in Indonesia. Implementation of accrual based accounting in government institutions amid debate about the usefulness of accounting information for decision-making. Empirical study shows that the accrual based of accounting information on a government institution is not used for decision making. The research objective was to determine the impact of the implementation of the accrual based accounting to the accrual basis of accounting information use for decision-making basis. We used the survey questionnaires. The data were processed by SEM using statistical software WarpPLS. The results showed that the implementation of the accrual based accounting in City Government Semarang has significantly positively associated with decision-making. Another important finding is the City Government officials of Semarang have personality, low tolerance of ambiguity is a negative effect on the relationship between the implementation of the accrual based accounting for decision making

  17. An agent-based model for integrated emotion regulation and contagion in socially affected decision making

    OpenAIRE

    Manzoor, A.; Treur, J.

    2015-01-01

    This paper addresses an agent-based computational social agent model for the integration of emotion regulation, emotion contagion and decision making in a social context. The model integrates emotion-related valuing, in order to analyse the role of emotions in socially affected decision making. The agent-based model is illustrated for the interaction between two persons. Simulation experiments for different kinds of scenarios help to understand how decisions can be affected by regulating the ...

  18. A Web-Based Model for Diabetes Education and Decision Support for the Home Care Nurse

    OpenAIRE

    Hill, Michelle; Kirby, Judy

    1998-01-01

    Diabetes education for the home care population requires expert knowledge to be available at the point-of-care, the patient's home. This poster displays a model for Web-based diabetes education and decision support for the home care nurse. The system utilizes the line of reasoning (LOR) model to organize and represent expert decision-making thought processes.

  19. An agent-based model for integrated emotion regulation and contagion in socially affected decision making

    NARCIS (Netherlands)

    Manzoor, A.; Treur, J.

    2015-01-01

    This paper addresses an agent-based computational social agent model for the integration of emotion regulation, emotion contagion and decision making in a social context. The model integrates emotion-related valuing, in order to analyse the role of emotions in socially affected decision making. The

  20. 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

  1. The Research of Clinical Decision Support System Based on Three-Layer Knowledge Base Model

    Directory of Open Access Journals (Sweden)

    Yicheng Jiang

    2017-01-01

    Full Text Available In many clinical decision support systems, a two-layer knowledge base model (disease-symptom of rule reasoning is used. This model often does not express knowledge very well since it simply infers disease from the presence of certain symptoms. In this study, we propose a three-layer knowledge base model (disease-symptom-property to utilize more useful information in inference. The system iteratively calculates the probability of patients who may suffer from diseases based on a multisymptom naive Bayes algorithm, in which the specificity of these disease symptoms is weighted by the estimation of the degree of contribution to diagnose the disease. It significantly reduces the dependencies between attributes to apply the naive Bayes algorithm more properly. Then, the online learning process for parameter optimization of the inference engine was completed. At last, our decision support system utilizing the three-layer model was formally evaluated by two experienced doctors. By comparisons between prediction results and clinical results, our system can provide effective clinical recommendations to doctors. Moreover, we found that the three-layer model can improve the accuracy of predictions compared with the two-layer model. In light of some of the limitations of this study, we also identify and discuss several areas that need continued improvement.

  2. An open-loop, physiologic model-based decision support system can provide appropriate ventilator settings

    DEFF Research Database (Denmark)

    Karbing, Dan Stieper; Spadaro, Savino; Dey, Nilanjan

    2018-01-01

    OBJECTIVES: To evaluate the physiologic effects of applying advice on mechanical ventilation by an open-loop, physiologic model-based clinical decision support system. DESIGN: Prospective, observational study. SETTING: University and Regional Hospitals' ICUs. PATIENTS: Varied adult ICU population...

  3. Learning to maximize reward rate: a model based on semi-Markov decision processes.

    Science.gov (United States)

    Khodadadi, Arash; Fakhari, Pegah; Busemeyer, Jerome R

    2014-01-01

    WHEN ANIMALS HAVE TO MAKE A NUMBER OF DECISIONS DURING A LIMITED TIME INTERVAL, THEY FACE A FUNDAMENTAL PROBLEM: how much time they should spend on each decision in order to achieve the maximum possible total outcome. Deliberating more on one decision usually leads to more outcome but less time will remain for other decisions. In the framework of sequential sampling models, the question is how animals learn to set their decision threshold such that the total expected outcome achieved during a limited time is maximized. The aim of this paper is to provide a theoretical framework for answering this question. To this end, we consider an experimental design in which each trial can come from one of the several possible "conditions." A condition specifies the difficulty of the trial, the reward, the penalty and so on. We show that to maximize the expected reward during a limited time, the subject should set a separate value of decision threshold for each condition. We propose a model of learning the optimal value of decision thresholds based on the theory of semi-Markov decision processes (SMDP). In our model, the experimental environment is modeled as an SMDP with each "condition" being a "state" and the value of decision thresholds being the "actions" taken in those states. The problem of finding the optimal decision thresholds then is cast as the stochastic optimal control problem of taking actions in each state in the corresponding SMDP such that the average reward rate is maximized. Our model utilizes a biologically plausible learning algorithm to solve this problem. The simulation results show that at the beginning of learning the model choses high values of decision threshold which lead to sub-optimal performance. With experience, however, the model learns to lower the value of decision thresholds till finally it finds the optimal values.

  4. A model of reward- and effort-based optimal decision making and motor control.

    Directory of Open Access Journals (Sweden)

    Lionel Rigoux

    Full Text Available Costs (e.g. energetic expenditure and benefits (e.g. food are central determinants of behavior. In ecology and economics, they are combined to form a utility function which is maximized to guide choices. This principle is widely used in neuroscience as a normative model of decision and action, but current versions of this model fail to consider how decisions are actually converted into actions (i.e. the formation of trajectories. Here, we describe an approach where decision making and motor control are optimal, iterative processes derived from the maximization of the discounted, weighted difference between expected rewards and foreseeable motor efforts. The model accounts for decision making in cost/benefit situations, and detailed characteristics of control and goal tracking in realistic motor tasks. As a normative construction, the model is relevant to address the neural bases and pathological aspects of decision making and motor control.

  5. Combining Bayesian Networks and Agent Based Modeling to develop a decision-support model in Vietnam

    Science.gov (United States)

    Nong, Bao Anh; Ertsen, Maurits; Schoups, Gerrit

    2016-04-01

    Complexity and uncertainty in natural resources management have been focus themes in recent years. Within these debates, with the aim to define an approach feasible for water management practice, we are developing an integrated conceptual modeling framework for simulating decision-making processes of citizens, in our case in the Day river area, Vietnam. The model combines Bayesian Networks (BNs) and Agent-Based Modeling (ABM). BNs are able to combine both qualitative data from consultants / experts / stakeholders, and quantitative data from observations on different phenomena or outcomes from other models. Further strengths of BNs are that the relationship between variables in the system is presented in a graphical interface, and that components of uncertainty are explicitly related to their probabilistic dependencies. A disadvantage is that BNs cannot easily identify the feedback of agents in the system once changes appear. Hence, ABM was adopted to represent the reaction among stakeholders under changes. The modeling framework is developed as an attempt to gain better understanding about citizen's behavior and factors influencing their decisions in order to reduce uncertainty in the implementation of water management policy.

  6. A decision model for cost effective design of biomass based green energy supply chains.

    Science.gov (United States)

    Yılmaz Balaman, Şebnem; Selim, Hasan

    2015-09-01

    The core driver of this study is to deal with the design of anaerobic digestion based biomass to energy supply chains in a cost effective manner. In this concern, a decision model is developed. The model is based on fuzzy multi objective decision making in order to simultaneously optimize multiple economic objectives and tackle the inherent uncertainties in the parameters and decision makers' aspiration levels for the goals. The viability of the decision model is explored with computational experiments on a real-world biomass to energy supply chain and further analyses are performed to observe the effects of different conditions. To this aim, scenario analyses are conducted to investigate the effects of energy crop utilization and operational costs on supply chain structure and performance measures. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Bayesian risk-based decision method for model validation under uncertainty

    International Nuclear Information System (INIS)

    Jiang Xiaomo; Mahadevan, Sankaran

    2007-01-01

    This paper develops a decision-making methodology for computational model validation, considering the risk of using the current model, data support for the current model, and cost of acquiring new information to improve the model. A Bayesian decision theory-based method is developed for this purpose, using a likelihood ratio as the validation metric for model assessment. An expected risk or cost function is defined as a function of the decision costs, and the likelihood and prior of each hypothesis. The risk is minimized through correctly assigning experimental data to two decision regions based on the comparison of the likelihood ratio with a decision threshold. A Bayesian validation metric is derived based on the risk minimization criterion. Two types of validation tests are considered: pass/fail tests and system response value measurement tests. The methodology is illustrated for the validation of reliability prediction models in a tension bar and an engine blade subjected to high cycle fatigue. The proposed method can effectively integrate optimal experimental design into model validation to simultaneously reduce the cost and improve the accuracy of reliability model assessment

  8. Decision-Making in Agent-Based Models of Migration: State of the Art and Challenges.

    Science.gov (United States)

    Klabunde, Anna; Willekens, Frans

    We review agent-based models (ABM) of human migration with respect to their decision-making rules. The most prominent behavioural theories used as decision rules are the random utility theory, as implemented in the discrete choice model, and the theory of planned behaviour. We identify the critical choices that must be made in developing an ABM, namely the modelling of decision processes and social networks. We also discuss two challenges that hamper the widespread use of ABM in the study of migration and, more broadly, demography and the social sciences: (a) the choice and the operationalisation of a behavioural theory (decision-making and social interaction) and (b) the selection of empirical evidence to validate the model. We offer advice on how these challenges might be overcome.

  9. Graph-based Models for Data and Decision Making

    Science.gov (United States)

    2016-02-16

    most softwru-e) do not allow extemal synchronization. This is a generalized version of the MATB developed to assess multitasking in pilot -like... Multitasking …………………………...2 1.7 ACT-R and LBA Model Mimicry Reveals Similarity Across Levels of Analysis……..2 1.8 Exploring Individual Differences via...Netherlands, April 9-11, 39-44.) 1.6 Modeling the Workload of Capacity of Visual Multitasking We are extending the application of the capacity

  10. Cortical and hippocampal correlates of deliberation during model-based decisions for rewards in humans.

    Directory of Open Access Journals (Sweden)

    Aaron M Bornstein

    Full Text Available How do we use our memories of the past to guide decisions we've never had to make before? Although extensive work describes how the brain learns to repeat rewarded actions, decisions can also be influenced by associations between stimuli or events not directly involving reward - such as when planning routes using a cognitive map or chess moves using predicted countermoves - and these sorts of associations are critical when deciding among novel options. This process is known as model-based decision making. While the learning of environmental relations that might support model-based decisions is well studied, and separately this sort of information has been inferred to impact decisions, there is little evidence concerning the full cycle by which such associations are acquired and drive choices. Of particular interest is whether decisions are directly supported by the same mnemonic systems characterized for relational learning more generally, or instead rely on other, specialized representations. Here, building on our previous work, which isolated dual representations underlying sequential predictive learning, we directly demonstrate that one such representation, encoded by the hippocampal memory system and adjacent cortical structures, supports goal-directed decisions. Using interleaved learning and decision tasks, we monitor predictive learning directly and also trace its influence on decisions for reward. We quantitatively compare the learning processes underlying multiple behavioral and fMRI observables using computational model fits. Across both tasks, a quantitatively consistent learning process explains reaction times, choices, and both expectation- and surprise-related neural activity. The same hippocampal and ventral stream regions engaged in anticipating stimuli during learning are also engaged in proportion to the difficulty of decisions. These results support a role for predictive associations learned by the hippocampal memory system to

  11. Challenges Associated With Applying Physiologically Based Pharmacokinetic Modeling for Public Health Decision-Making

    Science.gov (United States)

    The development and application of physiologically based pharmacokinetic (PBPK) models in chemical toxicology have grown steadily since their emergence in the 1980s. However, critical evaluation of PBPK models to support public health decision-making across federal agencies has t...

  12. 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

  13. Modeling bidding decision in engineering field with incomplete information: A static game–based approach

    Directory of Open Access Journals (Sweden)

    Zhi-xing Huang

    2016-01-01

    Full Text Available Corporate investment decision about engineering projects is a key issue for project management. This article aims to study the process of bidding decision-making in engineering field under the condition of incomplete information and investigating the influence of bidders’ game behaviors on investment decision. With reasonable assumed scenes, this article uses an approach to describe the decision process for bidding. The approach is based on the static game theory. With the proposed model, the effectiveness of game participants and the objective function are put forward, and the characteristics of price quotation and the best strategies of bidders under the equilibrium condition are discussed. The results can give a better understanding of investment decision in engineering management and are helpful for tenderees to avoid excessive competition among bidders.

  14. MRI-based decision tree model for diagnosis of biliary atresia.

    Science.gov (United States)

    Kim, Yong Hee; Kim, Myung-Joon; Shin, Hyun Joo; Yoon, Haesung; Han, Seok Joo; Koh, Hong; Roh, Yun Ho; Lee, Mi-Jung

    2018-02-23

    To evaluate MRI findings and to generate a decision tree model for diagnosis of biliary atresia (BA) in infants with jaundice. We retrospectively reviewed features of MRI and ultrasonography (US) performed in infants with jaundice between January 2009 and June 2016 under approval of the institutional review board, including the maximum diameter of periportal signal change on MRI (MR triangular cord thickness, MR-TCT) or US (US-TCT), visibility of common bile duct (CBD) and abnormality of gallbladder (GB). Hepatic subcapsular flow was reviewed on Doppler US. We performed conditional inference tree analysis using MRI findings to generate a decision tree model. A total of 208 infants were included, 112 in the BA group and 96 in the non-BA group. Mean age at the time of MRI was 58.7 ± 36.6 days. Visibility of CBD, abnormality of GB and MR-TCT were good discriminators for the diagnosis of BA and the MRI-based decision tree using these findings with MR-TCT cut-off 5.1 mm showed 97.3 % sensitivity, 94.8 % specificity and 96.2 % accuracy. MRI-based decision tree model reliably differentiates BA in infants with jaundice. MRI can be an objective imaging modality for the diagnosis of BA. • MRI-based decision tree model reliably differentiates biliary atresia in neonatal cholestasis. • Common bile duct, gallbladder and periportal signal changes are the discriminators. • MRI has comparable performance to ultrasonography for diagnosis of biliary atresia.

  15. Multi-objective decision-making model based on CBM for an aircraft fleet

    Science.gov (United States)

    Luo, Bin; Lin, Lin

    2018-04-01

    Modern production management patterns, in which multi-unit (e.g., a fleet of aircrafts) are managed in a holistic manner, have brought new challenges for multi-unit maintenance decision making. To schedule a good maintenance plan, not only does the individual machine maintenance have to be considered, but also the maintenance of the other individuals have to be taken into account. Since most condition-based maintenance researches for aircraft focused on solely reducing maintenance cost or maximizing the availability of single aircraft, as well as considering that seldom researches concentrated on both the two objectives: minimizing cost and maximizing the availability of a fleet (total number of available aircraft in fleet), a multi-objective decision-making model based on condition-based maintenance concentrated both on the above two objectives is established. Furthermore, in consideration of the decision maker may prefer providing the final optimal result in the form of discrete intervals instead of a set of points (non-dominated solutions) in real decision-making problem, a novel multi-objective optimization method based on support vector regression is proposed to solve the above multi-objective decision-making model. Finally, a case study regarding a fleet is conducted, with the results proving that the approach efficiently generates outcomes that meet the schedule requirements.

  16. 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

  17. How Feedback Can Improve Managerial Evaluations of Model-based Marketing Decision Support Systems

    NARCIS (Netherlands)

    U. Kayande (Ujwal); A. de Bruyn (Arnoud); G.L. Lilien (Gary); A. Rangaswamy (Arvind); G.H. van Bruggen (Gerrit)

    2006-01-01

    textabstractMarketing managers often provide much poorer evaluations of model-based marketing decision support systems (MDSSs) than are warranted by the objective performance of those systems. We show that a reason for this discrepant evaluation may be that MDSSs are often not designed to help users

  18. Decision tree based knowledge acquisition and failure diagnosis using a PWR loop vibration model

    International Nuclear Information System (INIS)

    Bauernfeind, V.; Ding, Y.

    1993-01-01

    An analytical vibration model of the primary system of a 1300 MW PWR was used for simulating mechanical faults. Deviations in the calculated power density spectra and coherence functions are determined and classified. The decision tree technique is then used for a personal computer supported knowledge presentation and for optimizing the logical relationships between the simulated faults and the observed symptoms. The optimized decision tree forms the knowledge base and can be used to diagnose known cases as well as to include new data into the knowledge base if new faults occur. (author)

  19. An Agent-Based Model of Farmer Decision Making in Jordan

    Science.gov (United States)

    Selby, Philip; Medellin-Azuara, Josue; Harou, Julien; Klassert, Christian; Yoon, Jim

    2016-04-01

    We describe an agent based hydro-economic model of groundwater irrigated agriculture in the Jordan Highlands. The model employs a Multi-Agent-Simulation (MAS) framework and is designed to evaluate direct and indirect outcomes of climate change scenarios and policy interventions on farmer decision making, including annual land use, groundwater use for irrigation, and water sales to a water tanker market. Land use and water use decisions are simulated for groups of farms grouped by location and their behavioural and economic similarities. Decreasing groundwater levels, and the associated increase in pumping costs, are important drivers for change within Jordan'S agricultural sector. We describe how this is considered by coupling of agricultural and groundwater models. The agricultural production model employs Positive Mathematical Programming (PMP), a method for calibrating agricultural production functions to observed planted areas. PMP has successfully been used with disaggregate models for policy analysis. We adapt the PMP approach to allow explicit evaluation of the impact of pumping costs, groundwater purchase fees and a water tanker market. The work demonstrates the applicability of agent-based agricultural decision making assessment in the Jordan Highlands and its integration with agricultural model calibration methods. The proposed approach is designed and implemented with software such that it could be used to evaluate a variety of physical and human influences on decision making in agricultural water management.

  20. Towards An Intelligent Model-Based Decision Support System For An Integrated Oil Company (EGPC)

    International Nuclear Information System (INIS)

    Khorshid, M.; Hassan, H.; Abdel Latife, M.A.

    2004-01-01

    Decision Support System (DSS) is an interactive, flexible and adaptable computer-based support system specially developed for supporting the solution of unstructured management problems [31] DSS has become widespread for oil industry domain in recent years. The computer-based DSS, which were developed and implemented in oil industry, are used to address the complex short-term planning and operational issues associated with downstream industry. Most of these applications concentrate on the data-centered tools, while the model-centered applications of DSS are still very limited up till now [20]. This study develops an Intelligent Model-Based DSS for an integrated oil company, to help policy makers and petroleum planner in improving the effectiveness of the strategic planning in oil sector. This domain basically imposes semi-structured or unstructured decisions and involves a very complex modeling process

  1. Decision-making model of generation technology under uncertainty based on real option theory

    International Nuclear Information System (INIS)

    Ming, Zeng; Ping, Zhang; Shunkun, Yu; Ge, Zhang

    2016-01-01

    Highlights: • A decision-making model of generation technology investment is proposed. • The irreversible investment concept and real option theory is introduced. • Practical data was used to prove the validity of the model. • Impact of electricity and fuel price fluctuation on investment was analyzed. - Abstract: The introduction of market competition and the increased uncertainty factors makes the generators have to decide not only on whether to invest generation capacity or not but also on what kind of generation technology to choose. In this paper, a decision-making model of generation technology investment is proposed. The irreversible investment concept and real option theory is introduced as the fundamental of the model. In order to explain the decision-making process of generator’s investment, the decision-making optimization model was built considering two generation technologies, i.e., the heat-only system and the combined heat and power generation. Also, we discussed the theory deducing process, which explained how to eliminate the overrated economic potential caused by risk hazard, based on economic evaluation of both generation technologies. Finally, practical data from electricity market of Inner Mongolia was used to prove the validity of the model and the impact of uncertainties of electricity and fuel price fluctuation on investment was analyzed according to the simulated results.

  2. Consumer Decision-Making Styles Extension to Trust-Based Product Comparison Site Usage Model

    Directory of Open Access Journals (Sweden)

    Radoslaw Macik

    2016-09-01

    Full Text Available The paper describes an implementation of extended consumer decision-making styles concept in explaining consumer choices made in product comparison site environment in the context of trust-based information technology acceptance model. Previous research proved that trust-based acceptance model is useful in explaining purchase intention and anticipated satisfaction in product comparison site environment, as an example of online decision shopping aids. Trust to such aids is important in explaining their usage by consumers. The connections between consumer decision-making styles, product and sellers opinions usage, cognitive and affective trust toward online product comparison site, as well as choice outcomes (purchase intention and brand choice are explored trough structural equation models using PLS-SEM approach, using a sample of 461 young consumers. Research confirmed the validity of research model in explaining product comparison usage, and some consumer decision-making styles influenced consumers’ choices and purchase intention. Product and sellers reviews usage were partially mediating mentioned relationships.

  3. 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.

  4. Support System Model for Value based Group Decision on Roof System Selection

    Directory of Open Access Journals (Sweden)

    Christiono Utomo

    2011-02-01

    Full Text Available A group decision support system is required on a value-based decision because there are different concern caused by differing preferences, experiences, and background. It is to enable each decision-maker to evaluate and rank the solution alternatives before engaging into negotiation with other decision-makers. Stakeholder of multi-criteria decision making problems usually evaluates the alternative solution from different perspective, making it possible to have a dominant solution among the alternatives. Each stakeholder needs to identify the goals that can be optimized and those that can be compromised in order to reach an agreement with other stakeholders. This paper presents group decision model involving three decision-makers on the selection of suitable system for a building’s roof. The objective of the research is to find an agreement options model and coalition algorithms for multi person decision with two main preferences of value which are function and cost. The methodology combines value analysis method using Function Analysis System Technique (FAST; Life Cycle Cost analysis, group decision analysis method based on Analytical Hierarchy Process (AHP in a satisfying options, and Game theory-based agent system to develop agreement option and coalition formation for the support system. The support system bridges theoretical gap between automated design in construction domain and automated negotiation in information technology domain by providing a structured methodology which can lead to systematic support system and automated negotiation. It will contribute to value management body of knowledge as an advanced method for creativity and analysis phase, since the practice of this knowledge is teamwork based. In the case of roof system selection, it reveals the start of the first negotiation round. Some of the solutions are not an option because no individual stakeholder or coalition of stakeholders desires to select it. The result indicates

  5. 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

  6. Cognitive decision modelling of emotion-based learning impairment in schizophrenia: the role of awareness.

    Science.gov (United States)

    Cella, Matteo; Dymond, Simon; Cooper, Andrew; Turnbull, Oliver H

    2012-03-30

    Individuals with schizophrenia often lack insight or awareness. Resulting impairment has been observed in various cognitive domains and, recently, linked to problems in emotion-based learning. The Iowa Gambling Task (IGT) has been used to assess emotion-based decision-making in patients with schizophrenia, but results have been inconclusive. The current study further investigates emotion-based decision-making in schizophrenia by elucidating the unique contribution of awareness. Twenty-five patients with schizophrenia and 24 healthy controls were assessed with a modified version of the IGT recording awareness at regular intervals. Symptom assessment, medication and medical history were recorded for the clinical group. Patients with schizophrenia underperformed on the IGT compared to controls. Subjective awareness levels were significantly lower in the schizophrenia group and were associated with hallucination severity. Cognitive decision modelling further indicated that patients with schizophrenia had impaired attention to losses, compared to controls. This parameter was positively correlated with awareness. We also found that positive symptoms altered awareness levels and suggest that this disruption may contribute to sub-optimal decision-making. Overall, a lack of awareness may be an important aspect in understanding impaired social cognitive functioning and emotion-based learning observed in schizophrenia. Copyright © 2011 Elsevier Ltd. All rights reserved.

  7. A Common Decision of Compartmental Models on the Base of Laplace Transform and Retain Function Concept

    International Nuclear Information System (INIS)

    Dimitrov, L.; Tzvetkova, A.; Nikolov, A.

    1997-01-01

    The compartmental models have a variety of applications in the analysis of the transport of radioactive and non-radioactive material in complex systems as atmosphere, hydrosphere, food chains, human body. The analysis of the biokinetic behaviour of the radioactive material into a human body gives a possibility for correct assessment of the dose from internal irradiation. Skrable has given a decision of non-cyclic linear compartmental models in case of a single intake of material in the compartments as an initial condition. The main purpose of our article is to write down a procedure for analysis of a general compartmental model in case of continuous intake of material into the compartments. This procedure is related to retain function concept and had developed on the base of Laplace transform. On the base on the proposed procedure a non-cyclic linear compartmental model decisions are given in case of both a single and a continuous intake. The Laplace images of cyclic and circular linear compartmental model decisions and their originals in some cases are given too. (author)

  8. The role of inertia in modeling decisions from experience with instance-based learning.

    Science.gov (United States)

    Dutt, Varun; Gonzalez, Cleotilde

    2012-01-01

    One form of inertia is the tendency to repeat the last decision irrespective of the obtained outcomes while making decisions from experience (DFE). A number of computational models based upon the Instance-Based Learning Theory, a theory of DFE, have included different inertia implementations and have shown to simultaneously account for both risk-taking and alternations between alternatives. The role that inertia plays in these models, however, is unclear as the same model without inertia is also able to account for observed risk-taking quite well. This paper demonstrates the predictive benefits of incorporating one particular implementation of inertia in an existing IBL model. We use two large datasets, estimation and competition, from the Technion Prediction Tournament involving a repeated binary-choice task to show that incorporating an inertia mechanism in an IBL model enables it to account for the observed average risk-taking and alternations. Including inertia, however, does not help the model to account for the trends in risk-taking and alternations over trials compared to the IBL model without the inertia mechanism. We generalize the two IBL models, with and without inertia, to the competition set by using the parameters determined in the estimation set. The generalization process demonstrates both the advantages and disadvantages of including inertia in an IBL model.

  9. A decision-making model based on a spiking neural circuit and synaptic plasticity.

    Science.gov (United States)

    Wei, Hui; Bu, Yijie; Dai, Dawei

    2017-10-01

    To adapt to the environment and survive, most animals can control their behaviors by making decisions. The process of decision-making and responding according to cues in the environment is stable, sustainable, and learnable. Understanding how behaviors are regulated by neural circuits and the encoding and decoding mechanisms from stimuli to responses are important goals in neuroscience. From results observed in Drosophila experiments, the underlying decision-making process is discussed, and a neural circuit that implements a two-choice decision-making model is proposed to explain and reproduce the observations. Compared with previous two-choice decision making models, our model uses synaptic plasticity to explain changes in decision output given the same environment. Moreover, biological meanings of parameters of our decision-making model are discussed. In this paper, we explain at the micro-level (i.e., neurons and synapses) how observable decision-making behavior at the macro-level is acquired and achieved.

  10. Validation and selection of ODE based systems biology models: how to arrive at more reliable decisions.

    Science.gov (United States)

    Hasdemir, Dicle; Hoefsloot, Huub C J; Smilde, Age K

    2015-07-08

    Most ordinary differential equation (ODE) based modeling studies in systems biology involve a hold-out validation step for model validation. In this framework a pre-determined part of the data is used as validation data and, therefore it is not used for estimating the parameters of the model. The model is assumed to be validated if the model predictions on the validation dataset show good agreement with the data. Model selection between alternative model structures can also be performed in the same setting, based on the predictive power of the model structures on the validation dataset. However, drawbacks associated with this approach are usually under-estimated. We have carried out simulations by using a recently published High Osmolarity Glycerol (HOG) pathway from S.cerevisiae to demonstrate these drawbacks. We have shown that it is very important how the data is partitioned and which part of the data is used for validation purposes. The hold-out validation strategy leads to biased conclusions, since it can lead to different validation and selection decisions when different partitioning schemes are used. Furthermore, finding sensible partitioning schemes that would lead to reliable decisions are heavily dependent on the biology and unknown model parameters which turns the problem into a paradox. This brings the need for alternative validation approaches that offer flexible partitioning of the data. For this purpose, we have introduced a stratified random cross-validation (SRCV) approach that successfully overcomes these limitations. SRCV leads to more stable decisions for both validation and selection which are not biased by underlying biological phenomena. Furthermore, it is less dependent on the specific noise realization in the data. Therefore, it proves to be a promising alternative to the standard hold-out validation strategy.

  11. A Multi-layer Dynamic Model for Coordination Based Group Decision Making in Water Resource Allocation and Scheduling

    Science.gov (United States)

    Huang, Wei; Zhang, Xingnan; Li, Chenming; Wang, Jianying

    Management of group decision-making is an important issue in water source management development. In order to overcome the defects in lacking of effective communication and cooperation in the existing decision-making models, this paper proposes a multi-layer dynamic model for coordination in water resource allocation and scheduling based group decision making. By introducing the scheme-recognized cooperative satisfaction index and scheme-adjusted rationality index, the proposed model can solve the problem of poor convergence of multi-round decision-making process in water resource allocation and scheduling. Furthermore, the problem about coordination of limited resources-based group decision-making process can be solved based on the effectiveness of distance-based group of conflict resolution. The simulation results show that the proposed model has better convergence than the existing models.

  12. Modelling and simulating decision processes of linked lives: An approach based on concurrent processes and stochastic race

    NARCIS (Netherlands)

    Warnke, T.; Reinhardt, O.; Klabunde, A.; Willekens, F.J.; Uhrmacher, A.

    2017-01-01

    Individuals’ decision processes play a central role in understanding modern migration phenomena and other demographic processes. Their integration into agent-based computational demography depends largely on suitable support by a modelling language. We are developing the Modelling Language for

  13. Consensual decision-making model based on game theory for LNG processes

    International Nuclear Information System (INIS)

    Castillo, Luis; Dorao, Carlos A.

    2012-01-01

    Highlights: ► A Decision Making (DM) approach for LNG projects based on game theory is presented. ► DM framework was tested with two different cases, using analytical models and a simple LNG process. ► The problems were solved by using a Genetic Algorithm (GA) binary coding and Nash-GA. ► Integrated models from the design and optimization of the process could result in more realistic outcome. ► The major challenge in such a framework is related to the uncertainties in the market models. - Abstract: Decision-Making (DM) in LNG projects is a quite complex process due to the number of actors, approval phases, large investments and capital return in the long time. Furthermore, due to the very high investment of a LNG project, a detailed and efficient DM process is required in order to minimize risks. In this work a Decision-Making (DM) approach for LNG projects is presented. The approach is based on a consensus algorithm to address the consensus output over a common value using cost functions within a framework based on game theory. The DM framework was tested with two different cases. The first case was used for evaluating the performance of the framework with analytical models, while the second case corresponds to a simple LNG process. The problems were solved by using a Genetic Algorithm (GA) binary coding and Nash-GA. The results of the DM framework in the LNG project indicate that considering an integrated DM model and including the markets role from the design and optimization of the process more realistic outcome could be obtained. However, the major challenge in such a framework is related to the uncertainties in the market models.

  14. Emotions as a Vehicle for Rationality: Rational Decision Making Models Based on Emotion-Related Valuing and Hebbian Learning

    NARCIS (Netherlands)

    Treur, J.; Umair, M.

    2015-01-01

    In this paper an adaptive decision model based on predictive loops through feeling states is analysed from the perspective of rationality. Hebbian learning is considered for different types of connections in the decision model. To assess the extent of rationality, a measure is introduced reflecting

  15. Selecting Products Considering the Regret Behavior of Consumer: A Decision Support Model Based on Online Ratings

    Directory of Open Access Journals (Sweden)

    Xia Liang

    2018-05-01

    Full Text Available With the remarkable promotion of e-commerce platforms, consumers increasingly prefer to purchase products online. Online ratings facilitate consumers to choose among products. Thus, to help consumers effectively select products, it is necessary to provide decision support methods for consumers to trade online. Considering the decision makers are bounded rational, this paper proposes a novel decision support model for product selection based on online ratings, in which the regret aversion behavior of consumers is formulated. Massive online ratings provided by experienced consumers for alternative products associated with several evaluation attributes are obtained by software finders. Then, the evaluations of alternative products in format of stochastic variables are conducted. To select a desirable alternative product, a novel method is introduced to calculate gain and loss degrees of each alternative over others. Considering the regret behavior of consumers in the product selection process, the regret and rejoice values of alternative products for consumer are computed to obtain the perceived utility values of alternative products. According to the prior order of the evaluation attributes provided by the consumer, the prior weights of attributes are determined based on the perceived utility values of alternative products. Furthermore, the overall perceived utility values of alternative products are obtained to generate a ranking result. Finally, a practical example from Zol.com.cn for tablet computer selection is used to demonstrate the feasibility and practically of the proposed model.

  16. A triangular climate-based decision model to forecast crop anomalies in Kenya

    Science.gov (United States)

    Guimarães Nobre, G.; Davenport, F.; Veldkamp, T.; Jongman, B.; Funk, C. C.; Husak, G. J.; Ward, P.; Aerts, J.

    2017-12-01

    By the end of 2017, the world is expected to experience unprecedented demands for food assistance where, across 45 countries, some 81 million people will face a food security crisis. Prolonged droughts in Eastern Africa are playing a major role in these crises. To mitigate famine risk and save lives, government bodies and international donor organisations are increasingly building up efforts to resolve conflicts and secure humanitarian relief. Disaster-relief and financing organizations traditionally focus on emergency response, providing aid after an extreme drought event, instead of taking actions in advance based on early warning. One of the reasons for this approach is that the seasonal risk information provided by early warning systems is often considered highly uncertain. Overcoming the reluctance to act based on early warnings greatly relies on understanding the risk of acting in vain, and assessing the cost-effectiveness of early actions. This research develops a triangular climate-based decision model for multiple seasonal time-scales to forecast strong anomalies in crop yield shortages in Kenya using Casual Discovery Algorithms and Fast and Frugal Decision Trees. This Triangular decision model (1) estimates the causality and strength of the relationship between crop yields and hydro climatological predictors (extracted from the Famine Early Warning Systems Network's data archive) during the crop growing season; (2) provides probabilistic forecasts of crop yield shortages in multiple time scales before the harvesting season; and (3) evaluates the cost-effectiveness of different financial mechanisms to respond to early warning indicators of crop yield shortages obtained from the model. Furthermore, we reflect on how such a model complements and advances the current state-of-art FEWS Net system, and examine its potential application to improve the management of agricultural risks in Kenya.

  17. 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...

  18. Modelling and simulating decision processes of linked lives: An approach based on concurrent processes and stochastic race.

    Science.gov (United States)

    Warnke, Tom; Reinhardt, Oliver; Klabunde, Anna; Willekens, Frans; Uhrmacher, Adelinde M

    2017-10-01

    Individuals' decision processes play a central role in understanding modern migration phenomena and other demographic processes. Their integration into agent-based computational demography depends largely on suitable support by a modelling language. We are developing the Modelling Language for Linked Lives (ML3) to describe the diverse decision processes of linked lives succinctly in continuous time. The context of individuals is modelled by networks the individual is part of, such as family ties and other social networks. Central concepts, such as behaviour conditional on agent attributes, age-dependent behaviour, and stochastic waiting times, are tightly integrated in the language. Thereby, alternative decisions are modelled by concurrent processes that compete by stochastic race. Using a migration model, we demonstrate how this allows for compact description of complex decisions, here based on the Theory of Planned Behaviour. We describe the challenges for the simulation algorithm posed by stochastic race between multiple concurrent complex decisions.

  19. An Integrated Scenario Ensemble-Based Framework for Hurricane Evacuation Modeling: Part 1-Decision Support System.

    Science.gov (United States)

    Davidson, Rachel A; Nozick, Linda K; Wachtendorf, Tricia; Blanton, Brian; Colle, Brian; Kolar, Randall L; DeYoung, Sarah; Dresback, Kendra M; Yi, Wenqi; Yang, Kun; Leonardo, Nicholas

    2018-03-30

    This article introduces a new integrated scenario-based evacuation (ISE) framework to support hurricane evacuation decision making. It explicitly captures the dynamics, uncertainty, and human-natural system interactions that are fundamental to the challenge of hurricane evacuation, but have not been fully captured in previous formal evacuation models. The hazard is represented with an ensemble of probabilistic scenarios, population behavior with a dynamic decision model, and traffic with a dynamic user equilibrium model. The components are integrated in a multistage stochastic programming model that minimizes risk and travel times to provide a tree of evacuation order recommendations and an evaluation of the risk and travel time performance for that solution. The ISE framework recommendations offer an advance in the state of the art because they: (1) are based on an integrated hazard assessment (designed to ultimately include inland flooding), (2) explicitly balance the sometimes competing objectives of minimizing risk and minimizing travel time, (3) offer a well-hedged solution that is robust under the range of ways the hurricane might evolve, and (4) leverage the substantial value of increasing information (or decreasing degree of uncertainty) over the course of a hurricane event. A case study for Hurricane Isabel (2003) in eastern North Carolina is presented to demonstrate how the framework is applied, the type of results it can provide, and how it compares to available methods of a single scenario deterministic analysis and a two-stage stochastic program. © 2018 Society for Risk Analysis.

  20. A decision rule based on goal programming and one-stage models for uncertain multi-criteria mixed decision making and games against nature

    Directory of Open Access Journals (Sweden)

    Helena Gaspars-Wieloch

    2017-01-01

    Full Text Available This paper is concerned with games against nature and multi-criteria decision making under uncertainty along with scenario planning. We focus on decision problems where a deterministic evaluation of criteria is not possible. The procedure we propose is based on weighted goal programming and may be applied when seeking a mixed strategy. A mixed strategy allows the decision maker to select and perform a weighted combination of several accessible alternatives. The new method takes into consideration the decision maker’s preference structure (importance of particular goals and nature (pessimistic, moderate or optimistic attitude towards a given problem. It is designed for one-shot decisions made under uncertainty with unknown probabilities (frequencies, i.e. for decision making under complete uncertainty or decision making under strategic uncertainty. The procedure refers to one-stage models, i.e. models considering combinations of scenarios and criteria (scenario-criterion pairs as distinct meta-attributes, which means that the novel approach can be used in the case of totally independent payoff matrices for particular targets. The algorithm does not require any information about frequencies, which is especially desirable for new decision problems. It can be successfully applied by passive decision makers, as only criteria weights and the coefficient of optimism have to be declared.

  1. 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.

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

    Directory of Open Access Journals (Sweden)

    Pengpeng Jiao

    2015-01-01

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

  3. Improving rural electricity system planning: An agent-based model for stakeholder engagement and decision making

    International Nuclear Information System (INIS)

    Alfaro, Jose F.; Miller, Shelie; Johnson, Jeremiah X.; Riolo, Rick R.

    2017-01-01

    Energy planners in regions with low rates of electrification face complex and high-risk challenges in selecting appropriate generating technologies and grid centralization. To better inform such processes, we present an Agent-Based Model (ABM) that facilitates engagement with stakeholders. This approach evaluates long-term plans using the cost of delivered electricity, resource mix, jobs and economic stimulus created within communities, and decentralized generation mix of the system, with results provided in a spatially-resolved format. This approach complements existing electricity planning methods (e.g., Integrated Resource Planning) by offering novel evaluation criteria based on typical stakeholder preferences. We demonstrate the utility of this approach with a case study based on a “blank-slate” scenario, which begins without generation or transmission infrastructure, for the long-term rural renewable energy plans of Liberia, West Africa. We consider five electrification strategies: prioritizing larger populations, deploying large resources, creating jobs, providing economic stimulus, and step-wise cost minimization. Through the case study we demonstrate how this approach can be used to engage stakeholders, supplement more established energy planning tools, and illustrate the effects of stakeholder decisions and preferences on the performance of the system. - Highlights: • An Agent Based Model, BABSTER, for electrification planning is presented. • BABSTER provides a highly engaging spatially resolved interface. • Allows flexible investigation of decision strategies with real-world incentives. • We show that decision strategies directly impact centralization and resource choice. • It is illustrated through the case study of Liberia, West Africa.

  4. Theoretical foundations of human decision-making in agent-based land use models – A review

    NARCIS (Netherlands)

    Groeneveld, Geert J.; Müller, B.; Buchmann, C.M.; Dressler, Gunnar; Guo, C.; Hase, N.; Hoffmann, F.; John, F.; Klassert, C.; Lauf, T.; Liebelt, V.; Nolzen, H.; Pannicke, N.; Schulze, J.; Weise, H.; Schwarz, N.

    2017-01-01

    Recent reviews stated that the complex and context-dependent nature of human decision-making resulted in ad-hoc representations of human decision in agent-based land use change models (LUCC ABMs) and that these representations are often not explicitly grounded in theory. However, a systematic survey

  5. 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.

  6. Strategies for memory-based decision making: Modeling behavioral and neural signatures within a cognitive architecture.

    Science.gov (United States)

    Fechner, Hanna B; Pachur, Thorsten; Schooler, Lael J; Mehlhorn, Katja; Battal, Ceren; Volz, Kirsten G; Borst, Jelmer P

    2016-12-01

    How do people use memories to make inferences about real-world objects? We tested three strategies based on predicted patterns of response times and blood-oxygen-level-dependent (BOLD) responses: one strategy that relies solely on recognition memory, a second that retrieves additional knowledge, and a third, lexicographic (i.e., sequential) strategy, that considers knowledge conditionally on the evidence obtained from recognition memory. We implemented the strategies as computational models within the Adaptive Control of Thought-Rational (ACT-R) cognitive architecture, which allowed us to derive behavioral and neural predictions that we then compared to the results of a functional magnetic resonance imaging (fMRI) study in which participants inferred which of two cities is larger. Overall, versions of the lexicographic strategy, according to which knowledge about many but not all alternatives is searched, provided the best account of the joint patterns of response times and BOLD responses. These results provide insights into the interplay between recognition and additional knowledge in memory, hinting at an adaptive use of these two sources of information in decision making. The results highlight the usefulness of implementing models of decision making within a cognitive architecture to derive predictions on the behavioral and neural level. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. Integrated Model-Based Decisions for Water, Energy and Food Nexus

    Science.gov (United States)

    Zhang, X.; Vesselinov, V. V.

    2015-12-01

    Energy, water and food are critical resources for sustaining social development and human lives; human beings cannot survive without any one of them. Energy crises, water shortages and food security are crucial worldwide problems. The nexus of energy, water and food has received more and more attention in the past decade. Energy, water and food are closely interrelated; water is required in energy development such as electricity generation; energy is indispensable for collecting, treating, and transporting water; both energy and water are crucial inputs for food production. Changes of either of them can lead to substantial impacts on other two resources, and vice versa. Effective decisions should be based on thorough research efforts for better understanding of their complex nexus. Rapid increase of population has significantly intensified the pressures on energy, water and food. Addressing and quantifying their interactive relationships are important for making robust and cost-effective strategies for managing the three resources simultaneously. In addition, greenhouse gases (GHGs) are emitted in energy, water, food production, consequently making contributions to growing climate change. Reflecting environmental impacts of GHGs is also desired (especially, on the quality and quantity of fresh water resources). Thus, a socio-economic model is developed in this study to quantitatively address the complex connections among energy, water and food production. A synthetic problem is proposed to demonstrate the model's applicability and feasibility. Preliminary results related to integrated decisions on energy supply management, water use planning, electricity generation planning, energy facility capacity expansion, food production, and associated GHG emission control are generated for providing cost-effective supports for decision makers.

  8. A risk based model supporting long term maintenance and reinvestment strategy decision making

    Energy Technology Data Exchange (ETDEWEB)

    Sand, Kjell; Montard, Julien; Tremoen, Tord H.

    2010-02-15

    This Technical Report is a product from the project Risk-Based Distribution System Asset Management (short: RISK DSAM) - Work Package 3 Risk exposure on company/strategic level. In the report a concept for portfolio distribution system asset management is presented. The approach comprises four main steps: 1. Decide the asset base. 2. Divide the asset base into relevant archetypes. 3. Develop or select relevant maintenance and reinvestment strategies for the different archetypes. 4. Estimate risks and costs for each archetype for the relevant strategies. For the different steps guidelines are given and a proposal for implementation of the concept is given in terms of a proposed IT system architecture.To evaluate the feasibility of such a concept, a prototype was developed in by using Visual Basic macros in Excel using real technical data from a small DSO. The experience from using the prototype shows that the concept is realistic. All assets are included and depending of the ambition of the risk analysis both simple simulation models and more advanced might be embedded. Presentations of the concept for a utility engineers have receive positive feedback indicating that the concept is regarded as a practical way to develop risk based asset management strategies for the asset fleet. It should be noted that the concept should be applied on a company strategic level and is thus not designed to be applied for a specific project or asset decisions. For this, more detailed models with area specific information, topology etc. are needed. (Author)

  9. Model based decision support system of operating settings for MMAT nozzles

    Directory of Open Access Journals (Sweden)

    Fritz Bradley Keith

    2016-04-01

    Full Text Available Droplet size, which is affected by nozzle type, nozzle setups and operation, and spray solution, is one of the most critical factors influencing spray performance, environment pollution, food safety, and must be considered as part of any application scenario. Characterizing spray nozzles can be a timely and expensive proposition if the entire operational space (all combinations of spray pressure and orifice size, what influence flow rate is to be evaluated. This research proposes a structured, experimental design that allows for the development of computational models for droplet size based on any combination of a nozzle’s potential operational settings. The developed droplet size determination model can be used as Decision Support System (DSS for precise selection of sprayer working parameters to adapt to local field scenarios. Five nozzle types (designs were evaluated across their complete range of orifice size (flow rate* and spray pressures using a response surface experimental design. Several of the models showed high level fits of the modeled to the measured data while several did not as a result of the lack of significant effect from either orifice size (flow rate* or spray pressure. The computational models were integrated into a spreadsheet based user interface for ease of use. The proposed experimental design provides for efficient nozzle evaluations and development of computational models that allow for the determination of droplet size spectrum and spraying classification for any combination of a given nozzle’s operating settings. The proposed DSS will allow for the ready assessment and modification of a sprayers performance based on the operational settings, to ensure the application is made following recommendations in plant protection products (PPP labels.

  10. Model-Based Calculations of the Probability of a Country's Nuclear Proliferation Decisions

    International Nuclear Information System (INIS)

    Li, Jun; Yim, Man-Sung; McNelis, David N.

    2007-01-01

    explain the occurrences of proliferation decisions. However, predicting major historical proliferation events using model-based predictions has been unreliable. Nuclear proliferation decisions by a country is affected by three main factors: (1) technology; (2) finance; and (3) political motivation [1]. Technological capability is important as nuclear weapons development needs special materials, detonation mechanism, delivery capability, and the supporting human resources and knowledge base. Financial capability is likewise important as the development of the technological capabilities requires a serious financial commitment. It would be difficult for any state with a gross national product (GNP) significantly less than that of about $100 billion to devote enough annual governmental funding to a nuclear weapon program to actually achieve positive results within a reasonable time frame (i.e., 10 years). At the same time, nuclear proliferation is not a matter determined by a mastery of technical details or overcoming financial constraints. Technology or finance is a necessary condition but not a sufficient condition for nuclear proliferation. At the most fundamental level, the proliferation decision by a state is controlled by its political motivation. To effectively address the issue of predicting proliferation events, all three of the factors must be included in the model. To the knowledge of the authors, none of the exiting models considered the 'technology' variable as part of the modeling. This paper presents an attempt to develop a methodology for statistical modeling and predicting a country's nuclear proliferation decisions. The approach is based on the combined use of data on a country's nuclear technical capability profiles economic development status, security environment factors and internal political and cultural factors. All of the information utilized in the study was from open source literature. (authors)

  11. 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.

  12. Online decision support based on modeling with the aim of increased irrigation efficiency

    Science.gov (United States)

    Dövényi-Nagy, Tamás; Bakó, Károly; Molnár, Krisztina; Rácz, Csaba; Vasvári, Gyula; Nagy, János; Dobos, Attila

    2015-04-01

    The significant changes in the structure of ownership and control of irrigation infrastructure in the past decades resultted in the decrease of total irrigable and irrigated area (Szilárd, 1999). In this paper, the development of a model-based online service is described whose aim is to aid reasonable irrigation practice and increase water use efficiency. In order to establish a scientific background for irrigation, an agrometeorological station network has been built up by the Agrometeorological and Agroecological Monitoring Centre. A website has been launched in order to provide direct access for local agricultural producers to both the measured weather parameters and results of model based calculations. The public site provides information for general use, registered partners get a handy model based toolkit for decision support at the plot level concerning irrigation, plant protection or frost forecast. The agrometeorological reference station network was established in the recent years by the Agrometeorological and Agroecological Monitoring Centre and is distributed to cover most of the irrigated cropland areas of Hungary. From the spatial aspect, the stations have been deployed mainly in Eastern Hungary with concentrated irrigation infrastructure. The meteorological stations' locations have been carefully chosen to represent their environment in terms of soil, climatic and topographic factors, thereby assuring relevant and up-to-date input data for the models. The measured parameters range from classic meteorological data (air temperature, relative humidity, solar irradiation, wind speed etc.) to specific data which are not available from other services in the region, such as soil temperature, soil water content in multiple depths and leaf wetness. In addition to the basic grid of reference stations, specific stations under irrigated conditions have been deployed to calibrate and validate the models. A specific modeling framework (MetAgro) has been developed

  13. A Decision Model for Merging Base Operations: Outsourcing Pest Management on Joint Base Anacostia-Bolling

    Science.gov (United States)

    2011-11-30

    OH: South- Western Cengage Learning. Mankiw , N. G. (2006). Principles of economics (4th ed.). Mason, OH: Thompson South- Western. Private...When the choice to in-source or outsource an installation function or service requirement exists, in these challenging economic times, it is now more...decision uncertainties. When the choice to in-source or outsource an installation function or service requirement exists, in these challenging economic

  14. TOPSIS-based consensus model for group decision-making with incomplete interval fuzzy preference relations.

    Science.gov (United States)

    Liu, Fang; Zhang, Wei-Guo

    2014-08-01

    Due to the vagueness of real-world environments and the subjective nature of human judgments, it is natural for experts to estimate their judgements by using incomplete interval fuzzy preference relations. In this paper, based on the technique for order preference by similarity to ideal solution method, we present a consensus model for group decision-making (GDM) with incomplete interval fuzzy preference relations. To do this, we first define a new consistency measure for incomplete interval fuzzy preference relations. Second, a goal programming model is proposed to estimate the missing interval preference values and it is guided by the consistency property. Third, an ideal interval fuzzy preference relation is constructed by using the induced ordered weighted averaging operator, where the associated weights of characterizing the operator are based on the defined consistency measure. Fourth, a similarity degree between complete interval fuzzy preference relations and the ideal one is defined. The similarity degree is related to the associated weights, and used to aggregate the experts' preference relations in such a way that more importance is given to ones with the higher similarity degree. Finally, a new algorithm is given to solve the GDM problem with incomplete interval fuzzy preference relations, which is further applied to partnership selection in formation of virtual enterprises.

  15. 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.

  16. 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.

  17. 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

  18. Safety assessment of dangerous goods transport enterprise based on the relative entropy aggregation in group decision making model.

    Science.gov (United States)

    Wu, Jun; Li, Chengbing; Huo, Yueying

    2014-01-01

    Safety of dangerous goods transport is directly related to the operation safety of dangerous goods transport enterprise. Aiming at the problem of the high accident rate and large harm in dangerous goods logistics transportation, this paper took the group decision making problem based on integration and coordination thought into a multiagent multiobjective group decision making problem; a secondary decision model was established and applied to the safety assessment of dangerous goods transport enterprise. First of all, we used dynamic multivalue background and entropy theory building the first level multiobjective decision model. Secondly, experts were to empower according to the principle of clustering analysis, and combining with the relative entropy theory to establish a secondary rally optimization model based on relative entropy in group decision making, and discuss the solution of the model. Then, after investigation and analysis, we establish the dangerous goods transport enterprise safety evaluation index system. Finally, case analysis to five dangerous goods transport enterprises in the Inner Mongolia Autonomous Region validates the feasibility and effectiveness of this model for dangerous goods transport enterprise recognition, which provides vital decision making basis for recognizing the dangerous goods transport enterprises.

  19. A risk-based model for maintenance decision support of civil structures using RAMS

    NARCIS (Netherlands)

    Viana Da Rocha, T. C.; Stipanovic, I.; Hartmann, A.; Bakker, J.

    2017-01-01

    As a cornerstone of transportation asset management, risk-based approaches have been used to support maintenance decisions of civil structures. However, ambiguous and subjective risk criteria and inconsistency on the use of risk-based approaches can lead to a fuzzy understanding of the risks

  20. Abstraction of an Affective-Cognitive Decision Making Model Based on Simulated Behaviour and Perception Chains

    Science.gov (United States)

    Sharpanskykh, Alexei; Treur, Jan

    Employing rich internal agent models of actors in large-scale socio-technical systems often results in scalability issues. The problem addressed in this paper is how to improve computational properties of a complex internal agent model, while preserving its behavioral properties. The problem is addressed for the case of an existing affective-cognitive decision making model instantiated for an emergency scenario. For this internal decision model an abstracted behavioral agent model is obtained, which ensures a substantial increase of the computational efficiency at the cost of approximately 1% behavioural error. The abstraction technique used can be applied to a wide range of internal agent models with loops, for example, involving mutual affective-cognitive interactions.

  1. Processing Technology Selection for Municipal Sewage Treatment Based on a Multi-Objective Decision Model under Uncertainty

    Directory of Open Access Journals (Sweden)

    Xudong Chen

    2018-03-01

    Full Text Available This study considers the two factors of environmental protection and economic benefits to address municipal sewage treatment. Based on considerations regarding the sewage treatment plant construction site, processing technology, capital investment, operation costs, water pollutant emissions, water quality and other indicators, we establish a general multi-objective decision model for optimizing municipal sewage treatment plant construction. Using the construction of a sewage treatment plant in a suburb of Chengdu as an example, this paper tests the general model of multi-objective decision-making for the sewage treatment plant construction by implementing a genetic algorithm. The results show the applicability and effectiveness of the multi-objective decision model for the sewage treatment plant. This paper provides decision and technical support for the optimization of municipal sewage treatment.

  2. Processing Technology Selection for Municipal Sewage Treatment Based on a Multi-Objective Decision Model under Uncertainty.

    Science.gov (United States)

    Chen, Xudong; Xu, Zhongwen; Yao, Liming; Ma, Ning

    2018-03-05

    This study considers the two factors of environmental protection and economic benefits to address municipal sewage treatment. Based on considerations regarding the sewage treatment plant construction site, processing technology, capital investment, operation costs, water pollutant emissions, water quality and other indicators, we establish a general multi-objective decision model for optimizing municipal sewage treatment plant construction. Using the construction of a sewage treatment plant in a suburb of Chengdu as an example, this paper tests the general model of multi-objective decision-making for the sewage treatment plant construction by implementing a genetic algorithm. The results show the applicability and effectiveness of the multi-objective decision model for the sewage treatment plant. This paper provides decision and technical support for the optimization of municipal sewage treatment.

  3. Implementation of a model of dynamic activity-travel rescheduling decisions: an agent-based micro-simulation framework

    NARCIS (Netherlands)

    Arentze, T.A.; Pelizaro, C.; Timmermans, H.J.P.

    2005-01-01

    Recent progress in activity-based analysis has witnessed the development of some dynamic models of activity-travel rescheduling decisions. Most of this work involved descriptive analyses. Timmermans et al. (2001) elaborated this work and developed a more comprehensive theory and model of activity

  4. Modelling continuous pharmaceutical and bio-based processes at plant-wide level: A roadmap towards efficient decision-making

    DEFF Research Database (Denmark)

    Ramin, Pedram; Mansouri, Seyed Soheil; Udugama, Isuru A.

    2018-01-01

    The importance of developing simulation models for decision making in pharmaceutical and bio-based production processes is elaborated in this article. The advantages of modelling continuous processes are outlined and certain barriers in this regard are identified. Although there have been some...

  5. 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.

  6. A new computational account of cognitive control over reinforcement-based decision-making: Modeling of a probabilistic learning task.

    Science.gov (United States)

    Zendehrouh, Sareh

    2015-11-01

    Recent work on decision-making field offers an account of dual-system theory for decision-making process. This theory holds that this process is conducted by two main controllers: a goal-directed system and a habitual system. In the reinforcement learning (RL) domain, the habitual behaviors are connected with model-free methods, in which appropriate actions are learned through trial-and-error experiences. However, goal-directed behaviors are associated with model-based methods of RL, in which actions are selected using a model of the environment. Studies on cognitive control also suggest that during processes like decision-making, some cortical and subcortical structures work in concert to monitor the consequences of decisions and to adjust control according to current task demands. Here a computational model is presented based on dual system theory and cognitive control perspective of decision-making. The proposed model is used to simulate human performance on a variant of probabilistic learning task. The basic proposal is that the brain implements a dual controller, while an accompanying monitoring system detects some kinds of conflict including a hypothetical cost-conflict one. The simulation results address existing theories about two event-related potentials, namely error related negativity (ERN) and feedback related negativity (FRN), and explore the best account of them. Based on the results, some testable predictions are also presented. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. 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.

  8. An ontology-driven, case-based clinical decision support model for removable partial denture design

    Science.gov (United States)

    Chen, Qingxiao; Wu, Ji; Li, Shusen; Lyu, Peijun; Wang, Yong; Li, Miao

    2016-06-01

    We present the initial work toward developing a clinical decision support model for specific design of removable partial dentures (RPDs) in dentistry. We developed an ontological paradigm to represent knowledge of a patient’s oral conditions and denture component parts. During the case-based reasoning process, a cosine similarity algorithm was applied to calculate similarity values between input patients and standard ontology cases. A group of designs from the most similar cases were output as the final results. To evaluate this model, the output designs of RPDs for 104 randomly selected patients were compared with those selected by professionals. An area under the curve of the receiver operating characteristic (AUC-ROC) was created by plotting true-positive rates against the false-positive rate at various threshold settings. The precision at position 5 of the retrieved cases was 0.67 and at the top of the curve it was 0.96, both of which are very high. The mean average of precision (MAP) was 0.61 and the normalized discounted cumulative gain (NDCG) was 0.74 both of which confirmed the efficient performance of our model. All the metrics demonstrated the efficiency of our model. This methodology merits further research development to match clinical applications for designing RPDs. This paper is organized as follows. After the introduction and description of the basis for the paper, the evaluation and results are presented in Section 2. Section 3 provides a discussion of the methodology and results. Section 4 describes the details of the ontology, similarity algorithm, and application.

  9. Collaborative Decision Model on Stockpile Material of a Traditional Market Infrastructure using Value-Based HBU

    Science.gov (United States)

    Utomo, C.; Rahmawati, Y.; Pararta, D. L.; Ariesta, A.

    2017-11-01

    Readiness of infrastructure establishment is needed in the early phase of real estate development. To meet the needs of retail property in the form of traditional markets, the Government prepares to build a new 1300 units. Traditional market development requires infrastructure development. One of it is the preparation of sand material embankment as much as ± 200,000 m3. With a distance of 30 km, sand material can be delivered to the project site by dump trucks that can only be operated by 2 trip per day. The material is managed by using stockpile method. Decision of stockpile location requires multi person and multi criteria in a collaborative environment. The highest and the best use (HBU) criteria was used to construct a value-based decision hierarchy. Decision makers from five stakeholders analyzed the best of three locations by giving their own preference of development cost and HBU function. Analytical Hierarchy Process (AHP) based on satisfying options and cooperative game was applied for agreement options and coalition formation on collaborative decision. The result indicates that not all solutions become a possible location for the stockpile material. It shows the ‘best fit’ options process for all decision makers.

  10. Agent-based Modelling of Social Emotional Decision Making in Emergency Situations

    NARCIS (Netherlands)

    Bosse, T.; Hoogendoorn, M.; Klein, M.C.A.; Sharpanskykh, A.; Treur, J.; van der Wal, C.N.; van Wissen, A.

    2013-01-01

    Social decision making under stressful circumstances may involve strong emotions and contagion from others. Recent developments in Social Neuroscience have revealed neural mechanisms by which social contagion of cognitive and emotional states can be realised. In this paper, based on these

  11. A classification model of Hyperion image base on SAM combined decision tree

    Science.gov (United States)

    Wang, Zhenghai; Hu, Guangdao; Zhou, YongZhang; Liu, Xin

    2009-10-01

    Monitoring the Earth using imaging spectrometers has necessitated more accurate analyses and new applications to remote sensing. A very high dimensional input space requires an exponentially large amount of data to adequately and reliably represent the classes in that space. On the other hand, with increase in the input dimensionality the hypothesis space grows exponentially, which makes the classification performance highly unreliable. Traditional classification algorithms Classification of hyperspectral images is challenging. New algorithms have to be developed for hyperspectral data classification. The Spectral Angle Mapper (SAM) is a physically-based spectral classification that uses an ndimensional angle to match pixels to reference spectra. The algorithm determines the spectral similarity between two spectra by calculating the angle between the spectra, treating them as vectors in a space with dimensionality equal to the number of bands. The key and difficulty is that we should artificial defining the threshold of SAM. The classification precision depends on the rationality of the threshold of SAM. In order to resolve this problem, this paper proposes a new automatic classification model of remote sensing image using SAM combined with decision tree. It can automatic choose the appropriate threshold of SAM and improve the classify precision of SAM base on the analyze of field spectrum. The test area located in Heqing Yunnan was imaged by EO_1 Hyperion imaging spectrometer using 224 bands in visual and near infrared. The area included limestone areas, rock fields, soil and forests. The area was classified into four different vegetation and soil types. The results show that this method choose the appropriate threshold of SAM and eliminates the disturbance and influence of unwanted objects effectively, so as to improve the classification precision. Compared with the likelihood classification by field survey data, the classification precision of this model

  12. Orthogonal search-based rule extraction for modelling the decision to transfuse.

    Science.gov (United States)

    Etchells, T A; Harrison, M J

    2006-04-01

    Data from an audit relating to transfusion decisions during intermediate or major surgery were analysed to determine the strengths of certain factors in the decision making process. The analysis, using orthogonal search-based rule extraction (OSRE) from a trained neural network, demonstrated that the risk of tissue hypoxia (ROTH) assessed using a 100-mm visual analogue scale, the haemoglobin value (Hb) and the presence or absence of on-going haemorrhage (OGH) were able to reproduce the transfusion decisions with a joint specificity of 0.96 and sensitivity of 0.93 and a positive predictive value of 0.9. The rules indicating transfusion were: 1. ROTH > 32 mm and Hb 13 mm and Hb 38 mm, Hb < 102 g x l(-1) and OGH; 4. Hb < 78 g x l(-1).

  13. 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

  14. A Multi Criteria Group Decision-Making Model for Teacher Evaluation in Higher Education Based on Cloud Model and Decision Tree

    Science.gov (United States)

    Chang, Ting-Cheng; Wang, Hui

    2016-01-01

    This paper proposes a cloud multi-criteria group decision-making model for teacher evaluation in higher education which is involving subjectivity, imprecision and fuzziness. First, selecting the appropriate evaluation index depending on the evaluation objectives, indicating a clear structural relationship between the evaluation index and…

  15. Multilevel Flow Modeling Based Decision Support System and Its Task Organization

    DEFF Research Database (Denmark)

    Zhang, Xinxin; Lind, Morten; Ravn, Ole

    2013-01-01

    For complex engineering systems, there is an increasing demand for safety and reliability. Decision support system (DSS) is designed to offer su-pervision and analysis about operational situations. A proper model representa-tion is required for DSS to understand the process knowledge. Multilevel ...... techniques of MFM reasoning and less mature yet relevant MFM concepts are considered. It also offers an architecture design of task organization for MFM software tools by using the concept of agent and technology of multiagent software system....

  16. Combined prediction model for supply risk in nuclear power equipment manufacturing industry based on support vector machine and decision tree

    International Nuclear Information System (INIS)

    Shi Chunsheng; Meng Dapeng

    2011-01-01

    The prediction index for supply risk is developed based on the factor identifying of nuclear equipment manufacturing industry. The supply risk prediction model is established with the method of support vector machine and decision tree, based on the investigation on 3 important nuclear power equipment manufacturing enterprises and 60 suppliers. Final case study demonstrates that the combination model is better than the single prediction model, and demonstrates the feasibility and reliability of this model, which provides a method to evaluate the suppliers and measure the supply risk. (authors)

  17. A Cercla-Based Decision Model to Support Remedy Selection for an Uncertain Volume of Contaminants at a DOE Facility

    Energy Technology Data Exchange (ETDEWEB)

    Christine E. Kerschus

    1999-03-31

    The Paducah Gaseous Diffusion Plant (PGDP) operated by the Department of Energy is challenged with selecting the appropriate remediation technology to cleanup contaminants at Waste Area Group (WAG) 6. This research utilizes value-focused thinking and multiattribute preference theory concepts to produce a decision analysis model designed to aid the decision makers in their selection process. The model is based on CERCLA's five primary balancing criteria, tailored specifically to WAG 6 and the contaminants of concern, utilizes expert opinion and the best available engineering, cost, and performance data, and accounts for uncertainty in contaminant volume. The model ranks 23 remediation technologies (trains) in their ability to achieve the CERCLA criteria at various contaminant volumes. A sensitivity analysis is performed to examine the effects of changes in expert opinion and uncertainty in volume. Further analysis reveals how volume uncertainty is expected to affect technology cost, time and ability to meet the CERCLA criteria. The model provides the decision makers with a CERCLA-based decision analysis methodology that is objective, traceable, and robust to support the WAG 6 Feasibility Study. In addition, the model can be adjusted to address other DOE contaminated sites.

  18. A Cercla-Based Decision Model to Support Remedy Selection for an Uncertain Volume of Contaminants at a DOE Facility

    International Nuclear Information System (INIS)

    Christine E. Kerschus

    1999-01-01

    The Paducah Gaseous Diffusion Plant (PGDP) operated by the Department of Energy is challenged with selecting the appropriate remediation technology to cleanup contaminants at Waste Area Group (WAG) 6. This research utilizes value-focused thinking and multiattribute preference theory concepts to produce a decision analysis model designed to aid the decision makers in their selection process. The model is based on CERCLA's five primary balancing criteria, tailored specifically to WAG 6 and the contaminants of concern, utilizes expert opinion and the best available engineering, cost, and performance data, and accounts for uncertainty in contaminant volume. The model ranks 23 remediation technologies (trains) in their ability to achieve the CERCLA criteria at various contaminant volumes. A sensitivity analysis is performed to examine the effects of changes in expert opinion and uncertainty in volume. Further analysis reveals how volume uncertainty is expected to affect technology cost, time and ability to meet the CERCLA criteria. The model provides the decision makers with a CERCLA-based decision analysis methodology that is objective, traceable, and robust to support the WAG 6 Feasibility Study. In addition, the model can be adjusted to address other DOE contaminated sites

  19. 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).

  20. Ultrasonographic diagnosis of biliary atresia based on a decision-making tree model

    International Nuclear Information System (INIS)

    Lee, So Mi; Cheon, Jung Eun; Choi, Young Hun; Kim, Woo Sun; Cho, Hyun Hye; Kim, In One; You, Sun Kyoung

    2015-01-01

    To assess the diagnostic value of various ultrasound (US) findings and to make a decision-tree model for US diagnosis of biliary atresia (BA). From March 2008 to January 2014, the following US findings were retrospectively evaluated in 100 infants with cholestatic jaundice (BA, n = 46; non-BA, n = 54): length and morphology of the gallbladder, triangular cord thickness, hepatic artery and portal vein diameters, and visualization of the common bile duct. Logistic regression analyses were performed to determine the features that would be useful in predicting BA. Conditional inference tree analysis was used to generate a decision-making tree for classifying patients into the BA or non-BA groups. Multivariate logistic regression analysis showed that abnormal gallbladder morphology and greater triangular cord thickness were significant predictors of BA (p = 0.003 and 0.001; adjusted odds ratio: 345.6 and 65.6, respectively). In the decision-making tree using conditional inference tree analysis, gallbladder morphology and triangular cord thickness (optimal cutoff value of triangular cord thickness, 3.4 mm) were also selected as significant discriminators for differential diagnosis of BA, and gallbladder morphology was the first discriminator. The diagnostic performance of the decision-making tree was excellent, with sensitivity of 100% (46/46), specificity of 94.4% (51/54), and overall accuracy of 97% (97/100). Abnormal gallbladder morphology and greater triangular cord thickness (> 3.4 mm) were the most useful predictors of BA on US. We suggest that the gallbladder morphology should be evaluated first and that triangular cord thickness should be evaluated subsequently in cases with normal gallbladder morphology

  1. Ultrasonographic Diagnosis of Biliary Atresia Based on a Decision-Making Tree Model.

    Science.gov (United States)

    Lee, So Mi; Cheon, Jung-Eun; Choi, Young Hun; Kim, Woo Sun; Cho, Hyun-Hae; Cho, Hyun-Hye; Kim, In-One; You, Sun Kyoung

    2015-01-01

    To assess the diagnostic value of various ultrasound (US) findings and to make a decision-tree model for US diagnosis of biliary atresia (BA). From March 2008 to January 2014, the following US findings were retrospectively evaluated in 100 infants with cholestatic jaundice (BA, n = 46; non-BA, n = 54): length and morphology of the gallbladder, triangular cord thickness, hepatic artery and portal vein diameters, and visualization of the common bile duct. Logistic regression analyses were performed to determine the features that would be useful in predicting BA. Conditional inference tree analysis was used to generate a decision-making tree for classifying patients into the BA or non-BA groups. Multivariate logistic regression analysis showed that abnormal gallbladder morphology and greater triangular cord thickness were significant predictors of BA (p = 0.003 and 0.001; adjusted odds ratio: 345.6 and 65.6, respectively). In the decision-making tree using conditional inference tree analysis, gallbladder morphology and triangular cord thickness (optimal cutoff value of triangular cord thickness, 3.4 mm) were also selected as significant discriminators for differential diagnosis of BA, and gallbladder morphology was the first discriminator. The diagnostic performance of the decision-making tree was excellent, with sensitivity of 100% (46/46), specificity of 94.4% (51/54), and overall accuracy of 97% (97/100). Abnormal gallbladder morphology and greater triangular cord thickness (> 3.4 mm) were the most useful predictors of BA on US. We suggest that the gallbladder morphology should be evaluated first and that triangular cord thickness should be evaluated subsequently in cases with normal gallbladder morphology.

  2. Ultrasonographic diagnosis of biliary atresia based on a decision-making tree model

    Energy Technology Data Exchange (ETDEWEB)

    Lee, So Mi; Cheon, Jung Eun; Choi, Young Hun; Kim, Woo Sun; Cho, Hyun Hye; Kim, In One; You, Sun Kyoung [Dept. of Radiology, Seoul National University College of Medicine, Seoul (Korea, Republic of)

    2015-12-15

    To assess the diagnostic value of various ultrasound (US) findings and to make a decision-tree model for US diagnosis of biliary atresia (BA). From March 2008 to January 2014, the following US findings were retrospectively evaluated in 100 infants with cholestatic jaundice (BA, n = 46; non-BA, n = 54): length and morphology of the gallbladder, triangular cord thickness, hepatic artery and portal vein diameters, and visualization of the common bile duct. Logistic regression analyses were performed to determine the features that would be useful in predicting BA. Conditional inference tree analysis was used to generate a decision-making tree for classifying patients into the BA or non-BA groups. Multivariate logistic regression analysis showed that abnormal gallbladder morphology and greater triangular cord thickness were significant predictors of BA (p = 0.003 and 0.001; adjusted odds ratio: 345.6 and 65.6, respectively). In the decision-making tree using conditional inference tree analysis, gallbladder morphology and triangular cord thickness (optimal cutoff value of triangular cord thickness, 3.4 mm) were also selected as significant discriminators for differential diagnosis of BA, and gallbladder morphology was the first discriminator. The diagnostic performance of the decision-making tree was excellent, with sensitivity of 100% (46/46), specificity of 94.4% (51/54), and overall accuracy of 97% (97/100). Abnormal gallbladder morphology and greater triangular cord thickness (> 3.4 mm) were the most useful predictors of BA on US. We suggest that the gallbladder morphology should be evaluated first and that triangular cord thickness should be evaluated subsequently in cases with normal gallbladder morphology.

  3. Model For Marketing Strategy Decision Based On Multicriteria Decicion Making: A Case Study In Batik Madura Industry

    Science.gov (United States)

    Anna, I. D.; Cahyadi, I.; Yakin, A.

    2018-01-01

    Selection of marketing strategy is a prominent competitive advantage for small and medium enterprises business development. The selection process is is a multiple criteria decision-making problem, which includes evaluation of various attributes or criteria in a process of strategy formulation. The objective of this paper is to develop a model for the selection of a marketing strategy in Batik Madura industry. The current study proposes an integrated approach based on analytic network process (ANP) and technique for order preference by similarity to ideal solution (TOPSIS) to determine the best strategy for Batik Madura marketing problems. Based on the results of group decision-making technique, this study selected fourteen criteria, including consistency, cost, trend following, customer loyalty, business volume, uniqueness manpower, customer numbers, promotion, branding, bussiness network, outlet location, credibility and the inovation as Batik Madura marketing strategy evaluation criteria. A survey questionnaire developed from literature review was distributed to a sample frame of Batik Madura SMEs in Pamekasan. In the decision procedure step, expert evaluators were asked to establish the decision matrix by comparing the marketing strategy alternatives under each of the individual criteria. Then, considerations obtained from ANP and TOPSIS methods were applied to build the specific criteria constraints and range of the launch strategy in the model. The model in this study demonstrates that, under current business situation, Straight-focus marketing strategy is the best marketing strategy for Batik Madura SMEs in Pamekasan.

  4. Impaired Flexible Reward-Based Decision-Making in Binge Eating Disorder: Evidence from Computational Modeling and Functional Neuroimaging.

    Science.gov (United States)

    Reiter, Andrea M F; Heinze, Hans-Jochen; Schlagenhauf, Florian; Deserno, Lorenz

    2017-02-01

    Despite its clinical relevance and the recent recognition as a diagnostic category in the DSM-5, binge eating disorder (BED) has rarely been investigated from a cognitive neuroscientific perspective targeting a more precise neurocognitive profiling of the disorder. BED patients suffer from a lack of behavioral control during recurrent binge eating episodes and thus fail to adapt their behavior in the face of negative consequences, eg, high risk for obesity. To examine impairments in flexible reward-based decision-making, we exposed BED patients (n=22) and matched healthy individuals (n=22) to a reward-guided decision-making task during functional resonance imaging (fMRI). Performing fMRI analysis informed via computational modeling of choice behavior, we were able to identify specific signatures of altered decision-making in BED. On the behavioral level, we observed impaired behavioral adaptation in BED, which was due to enhanced switching behavior, a putative deficit in striking a balance between exploration and exploitation appropriately. This was accompanied by diminished activation related to exploratory decisions in the anterior insula/ventro-lateral prefrontal cortex. Moreover, although so-called model-free reward prediction errors remained intact, representation of ventro-medial prefrontal learning signatures, incorporating inference on unchosen options, was reduced in BED, which was associated with successful decision-making in the task. On the basis of a computational psychiatry account, the presented findings contribute to defining a neurocognitive phenotype of BED.

  5. Cognitive Tutoring based on Intelligent Decision Support in the PENTHA Instructional Design Model

    Science.gov (United States)

    dall'Acqua, Luisa

    2010-06-01

    The research finality of this paper is how to support Authors to develop rule driven—subject oriented, adaptable course content, meta-rules—representing the disciplinary epistemology, model of teaching, Learning Path structure, and assessment parameters—for intelligent Tutoring actions in a personalized, adaptive e-Learning environment. The focus is to instruct the student to be a decision manager for himself, able to recognize the elements of a problem, select the necessary information with the perspective of factual choices. In particular, our research intends to provide some fundamental guidelines for the definition of didactical rules and logical relations, that Authors should provide to a cognitive Tutoring system through the use of an Instructional Design method (PENTHA Model) which proposes an educational environment, able to: increase productivity and operability, create conditions for a cooperative dialogue, developing participatory research activities of knowledge, observations and discoveries, customizing the learning design in a complex and holistic vision of the learning / teaching processes.

  6. Independence and interdependence in collective decision making: an agent-based model of nest-site choice by honeybee swarms

    Science.gov (United States)

    List, Christian; Elsholtz, Christian; Seeley, Thomas D.

    2008-01-01

    Condorcet's jury theorem shows that when the members of a group have noisy but independent information about what is best for the group as a whole, majority decisions tend to outperform dictatorial ones. When voting is supplemented by communication, however, the resulting interdependencies between decision makers can strengthen or undermine this effect: they can facilitate information pooling, but also amplify errors. We consider an intriguing non-human case of independent information pooling combined with communication: the case of nest-site choice by honeybee (Apis mellifera) swarms. It is empirically well documented that when there are different nest sites that vary in quality, the bees usually choose the best one. We develop a new agent-based model of the bees' decision process and show that its remarkable reliability stems from a particular interplay of independence and interdependence between the bees. PMID:19073474

  7. The necessary burden of involving stakeholders in agent-based modelling for education and decision-making

    Science.gov (United States)

    Bommel, P.; Bautista Solís, P.; Leclerc, G.

    2016-12-01

    We implemented a participatory process with water stakeholders for improving resilience to drought at watershed scale, and for reducing water pollution disputes in drought prone Northwestern Costa Rica. The purpose is to facilitate co-management in a rural watershed impacted by recurrent droughts related to ENSO. The process involved designing "ContaMiCuenca", a hybrid agent-based model where users can specify the decisions of their agents. We followed a Companion Modeling approach (www.commod.org) and organized 10 workshops that included research techniques such as participatory diagnostics, actor-resources-interaction and UML diagrams, multi-agents model design, and interactive simulation sessions. We collectively assessed the main water issues in the watershed, prioritized their importance, defined the objectives of the process, and pilot-tested ContaMiCuenca for environmental education with adults and children. Simulation sessions resulted in debates about the need to improve the model accuracy, arguably more relevant for decision-making. This helped identify sensible knowledge gaps in the groundwater pollution and aquifer dynamics that need to be addressed in order to improve our collective learning. Significant mismatches among participants expectations, objectives, and agendas considerably slowed down the participatory process. The main issue may originate in participants expecting technical solutions from a positivist science, as constantly promoted in the region by dole-out initiatives, which is incompatible with the constructivist stance of participatory modellers. This requires much closer interaction of community members with modellers, which may be hard to attain in the current research practice and institutional context. Nevertheless, overcoming these constraints is necessary for a true involvement of water stakeholders to achieve community-based decisions that facilitate integrated water management. Our findings provide significant guidance for

  8. Evaluating the role of behavioral factors and practical constraints in the performance of an agent-based model of farmer decision making

    DEFF Research Database (Denmark)

    Malawska, Anna Katarzyna; Topping, Christopher John

    2016-01-01

    Farmer decision making models often focus on the behavioral assumptions in the representation of the decision making, applying bounded rationality theory to shift away from the generally criticized profit maximizer approach. Although complex on the behavioral side, such representations are usually...... simplistic with respect to the available choice options in farmer decision making and practical constraints related to farming decisions. To ascertain the relevance of modeling different facets of farmer decision making, we developed an agent based model of farmer decision making on crop choice, fertilizer...... and pesticide usage using an existing economic farm optimization model. We then gradually modified the model to include practical agronomic constraints and assumptions reflecting bounded rationality, and assessed the explanatory power of the added model components. The assessments were based on comparisons...

  9. Modelling continuous pharmaceutical and bio-based processes at plant-wide level: A roadmap towards efficient decision-making

    DEFF Research Database (Denmark)

    Ramin, Pedram; Mansouri, Seyed Soheil; Udugama, Isuru A.

    2018-01-01

    The importance of developing simulation models for decision making in pharmaceutical and bio-based production processes is elaborated in this article. The advantages of modelling continuous processes are outlined and certain barriers in this regard are identified. Although there have been some...... advancements in the field, there needs to be a larger international collaboration in this regard for providing reliable data for model validation, for development of generic modelbased frameworks and implementing them in computer-aided platforms in the form of software tools....

  10. 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.

  11. Scrutinizing individuals’ leisure-shopping travel decisions to appraise activity-based models of travel demand

    NARCIS (Netherlands)

    D. Kusamastuti (Diana); E. Hannes (Els); D. Janssens (Davy); G. Wets (Geert); B.G.C. Dellaert (Benedict)

    2010-01-01

    textabstractActivity-based models for modeling individuals’ travel demand have come to a new era in addressing individuals’ and households’ travel behavior on a disaggregate level. Quantitative data are mainly used in this domain to enable a realistic representation of individual choices and a true

  12. A decision-tree-based model for evaluating the thermal comfort of horses

    Directory of Open Access Journals (Sweden)

    Ana Paula de Assis Maia

    2013-12-01

    Full Text Available Thermal comfort is of great importance in preserving body temperature homeostasis during thermal stress conditions. Although the thermal comfort of horses has been widely studied, there is no report of its relationship with surface temperature (T S. This study aimed to assess the potential of data mining techniques as a tool to associate surface temperature with thermal comfort of horses. T S was obtained using infrared thermography image processing. Physiological and environmental variables were used to define the predicted class, which classified thermal comfort as "comfort" and "discomfort". The variables of armpit, croup, breast and groin T S of horses and the predicted classes were then subjected to a machine learning process. All variables in the dataset were considered relevant for the classification problem and the decision-tree model yielded an accuracy rate of 74 %. The feature selection methods used to reduce computational cost and simplify predictive learning decreased model accuracy to 70 %; however, the model became simpler with easily interpretable rules. For both these selection methods and for the classification using all attributes, armpit and breast T S had a higher power rating for predicting thermal comfort. Data mining techniques show promise in the discovery of new variables associated with the thermal comfort of horses.

  13. The Sustainable Island Development Evaluation Model and Its Application Based on the Nonstructural Decision Fuzzy Set

    Directory of Open Access Journals (Sweden)

    Quanming Wang

    2013-01-01

    Full Text Available Due to the complexity and diversity of the issue of sustainable island development, no widely accepted and applicable evaluation system model regarding the issue currently exists. In this paper, we discuss and establish the sustainable development indicator system and the model approach from the perspective of resources, the island environment, the island development status, the island social development, and the island intelligence development. We reference the sustainable development theory and the sustainable development indicator system method concerning land region, combine the character of the sustainable island development, analyze and evaluate the extent of the sustainable island development, orient development, and identify the key and limited factors of sustainable island development capability. This research adopts the entropy method and the nonstructural decision fuzzy set theory model to determine the weight of the evaluating indicators. Changhai County was selected as the subject of the research, which consisted of a quantitative study of its sustainable development status from 2001 to 2008 to identify the key factors influencing its sustainability development, existing problems, and limited factors and to provide basic technical support for ocean development planning and economic development planning.

  14. Modeling the Construct of an Expert Evidence-Adaptive Knowledge Base for a Pressure Injury Clinical Decision Support System

    Directory of Open Access Journals (Sweden)

    Peck Chui Betty Khong

    2017-07-01

    Full Text Available The selection of appropriate wound products for the treatment of pressure injuries is paramount in promoting wound healing. However, nurses find it difficult to decide on the most optimal wound product(s due to limited live experiences in managing pressure injuries resulting from successfully implemented pressure injury prevention programs. The challenges of effective decision-making in wound treatments by nurses at the point of care are compounded by the yearly release of wide arrays of newly researched wound products into the consumer market. A clinical decision support system for pressure injury (PI-CDSS was built to facilitate effective decision-making and selection of optimal wound treatments. This paper describes the development of PI-CDSS with an expert knowledge base using an interactive development environment, Blaze Advisor. A conceptual framework using decision-making and decision theory, knowledge representation, and process modelling guided the construct of the PI-CDSS. This expert system has incorporated the practical and relevant decision knowledge of wound experts in assessment and wound treatments in its algorithm. The construct of the PI-CDSS is adaptive, with scalable capabilities for expansion to include other CDSSs and interoperability to interface with other existing clinical and administrative systems. The algorithm was formatively evaluated and tested for usability. The treatment modalities generated after using patient-specific assessment data were found to be consistent with the treatment plan(s proposed by the wound experts. The overall agreement exceeded 90% between the wound experts and the generated treatment modalities for the choice of wound products, instructions, and alerts. The PI-CDSS serves as a just-in-time wound treatment protocol with suggested clinical actions for nurses, based on the best evidence available.

  15. Risk-based emergency decision support

    International Nuclear Information System (INIS)

    Koerte, Jens

    2003-01-01

    In the present paper we discuss how to assist critical decisions taken under complex, contingent circumstances, with a high degree of uncertainty and short time frames. In such sharp-end decision regimes, standard rule-based decision support systems do not capture the complexity of the situation. At the same time, traditional risk analysis is of little use due to variability in the specific circumstances. How then, can an organisation provide assistance to, e.g. pilots in dealing with such emergencies? A method called 'contingent risk and decision analysis' is presented, to provide decision support for decisions under variable circumstances and short available time scales. The method consists of nine steps of definition, modelling, analysis and criteria definition to be performed 'off-line' by analysts, and procedure generation to transform the analysis result into an operational decision aid. Examples of pilots' decisions in response to sudden vibration in offshore helicopter transport method are used to illustrate the approach

  16. Cloud decision model for selecting sustainable energy crop based on linguistic intuitionistic information

    Science.gov (United States)

    Peng, Hong-Gang; Wang, Jian-Qiang

    2017-11-01

    In recent years, sustainable energy crop has become an important energy development strategy topic in many countries. Selecting the most sustainable energy crop is a significant problem that must be addressed during any biofuel production process. The focus of this study is the development of an innovative multi-criteria decision-making (MCDM) method to handle sustainable energy crop selection problems. Given that various uncertain data are encountered in the evaluation of sustainable energy crops, linguistic intuitionistic fuzzy numbers (LIFNs) are introduced to present the information necessary to the evaluation process. Processing qualitative concepts requires the effective support of reliable tools; then, a cloud model can be used to deal with linguistic intuitionistic information. First, LIFNs are converted and a novel concept of linguistic intuitionistic cloud (LIC) is proposed. The operations, score function and similarity measurement of the LICs are defined. Subsequently, the linguistic intuitionistic cloud density-prioritised weighted Heronian mean operator is developed, which served as the basis for the construction of an applicable MCDM model for sustainable energy crop selection. Finally, an illustrative example is provided to demonstrate the proposed method, and its feasibility and validity are further verified by comparing it with other existing methods.

  17. Predicting IT Governance Performance : A Method for Model-Based Decision Making

    OpenAIRE

    Simonsson, Mårten

    2008-01-01

    Contemporary enterprises are largely dependent on Information Technology (IT), which makes decision making on IT matters important. There are numerous issues that confuse IT decision making, including contradictive business needs, financial constraints, lack of communication between business and IT stakeholders and difficulty in understanding the often heterogeneous and integrated IT systems. The discipline of IT governance aims at providing the decision making structures, processes, and rela...

  18. 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.

  19. Global Earth Observation System of Systems: Characterizing Uncertainties of Space- based Measurements and Earth System Models Informing Decision Tools

    Science.gov (United States)

    Birk, R. J.; Frederick, M.

    2006-05-01

    The Global Earth Observation System of Systems (GEOSS) framework identifies the benefits of systematically and scientifically networking the capacity of organizations and systems into solutions that benefit nine societal benefit areas. The U.S. Integrated Earth Observation System (IEOS), the U.S. contribution to the GEOSS, focuses on near-term, mid-term, and long-term opportunities to establish integrated system solutions based on capacities and capabilities of member agencies and affiliations. Scientists at NASA, NOAA, DOE, NSF and other U.S. agencies are evolving the predictive capacity of models of Earth processes based on space-based, airborne and surface-based instruments and their measurements. NASA research activities include advancing the power and accessibility of computational resources (i.e. Project Columbia) to enable robust science data analysis, modeling, and assimilation techniques to rapidly advance. The integration of the resulting observations and predictions into decision support tools require characterization of the accuracies of a range of input measurements includes temperature and humidity profiles, wind speed, ocean height, sea surface temperature, and atmospheric constituents that are measured globally by U.S. deployed spacecraft. These measurements are stored in many data formats on many different information systems with widely varying accessibility and have processes whose documentation ranges from extremely detailed to very minimal. Integrated and interdisciplinary modeling (enabled by the Earth System Model Framework) enable the types of ensemble analysis that are useful for decision processes associated with energy management, public health risk assessments, and optimizing transportation safety and efficiency. Interdisciplinary approaches challenge systems integrators (both scientists and engineers) to expand beyond the traditional boundaries of particular disciplines to develop, verify and validate, and ultimately benchmark the

  20. 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

  1. Prediction of axillary lymph node metastasis in primary breast cancer patients using a decision tree-based model

    Directory of Open Access Journals (Sweden)

    Takada Masahiro

    2012-06-01

    Full Text Available Abstract Background The aim of this study was to develop a new data-mining model to predict axillary lymph node (AxLN metastasis in primary breast cancer. To achieve this, we used a decision tree-based prediction method—the alternating decision tree (ADTree. Methods Clinical datasets for primary breast cancer patients who underwent sentinel lymph node biopsy or AxLN dissection without prior treatment were collected from three institutes (institute A, n = 148; institute B, n = 143; institute C, n = 174 and were used for variable selection, model training and external validation, respectively. The models were evaluated using area under the receiver operating characteristics (ROC curve analysis to discriminate node-positive patients from node-negative patients. Results The ADTree model selected 15 of 24 clinicopathological variables in the variable selection dataset. The resulting area under the ROC curve values were 0.770 [95% confidence interval (CI, 0.689–0.850] for the model training dataset and 0.772 (95% CI: 0.689–0.856 for the validation dataset, demonstrating high accuracy and generalization ability of the model. The bootstrap value of the validation dataset was 0.768 (95% CI: 0.763–0.774. Conclusions Our prediction model showed high accuracy for predicting nodal metastasis in patients with breast cancer using commonly recorded clinical variables. Therefore, our model might help oncologists in the decision-making process for primary breast cancer patients before starting treatment.

  2. Rule-based approach to cognitive modeling of real-time decision making

    International Nuclear Information System (INIS)

    Thorndyke, P.W.

    1982-01-01

    Recent developments in the fields of cognitive science and artificial intelligence have made possible the creation of a new class of models of complex human behavior. These models, referred to as either expert or knowledge-based systems, describe the high-level cognitive processing undertaken by a skilled human to perform a complex, largely mental, task. Expert systems have been developed to provide simulations of skilled performance of a variety of tasks. These include problems of data interpretation, system monitoring and fault isolation, prediction, planning, diagnosis, and design. In general, such systems strive to produce prescriptive (error-free) behavior, rather than model descriptively the typical human's errorful behavior. However, some research has sought to develop descriptive models of human behavior using the same theoretical frameworks adopted by expert systems builders. This paper presents an overview of this theoretical framework and modeling approach, and indicates the applicability of such models to the development of a model of control room operators in a nuclear power plant. Such a model could serve several beneficial functions in plant design, licensing, and operation

  3. A decision support model for improving a multi-family housing complex based on CO2 emission from electricity consumption.

    Science.gov (United States)

    Hong, Taehoon; Koo, Choongwan; Kim, Hyunjoong

    2012-12-15

    The number of deteriorated multi-family housing complexes in South Korea continues to rise, and consequently their electricity consumption is also increasing. This needs to be addressed as part of the nation's efforts to reduce energy consumption. The objective of this research was to develop a decision support model for determining the need to improve multi-family housing complexes. In this research, 1664 cases located in Seoul were selected for model development. The research team collected the characteristics and electricity energy consumption data of these projects in 2009-2010. The following were carried out in this research: (i) using the Decision Tree, multi-family housing complexes were clustered based on their electricity energy consumption; (ii) using Case-Based Reasoning, similar cases were retrieved from the same cluster; and (iii) using a combination of Multiple Regression Analysis, Artificial Neural Network, and Genetic Algorithm, the prediction performance of the developed model was improved. The results of this research can be used as follows: (i) as basic research data for continuously managing several energy consumption data of multi-family housing complexes; (ii) as advanced research data for predicting energy consumption based on the project characteristics; (iii) as practical research data for selecting the most optimal multi-family housing complex with the most potential in terms of energy savings; and (iv) as consistent and objective criteria for incentives and penalties. Copyright © 2012 Elsevier Ltd. All rights reserved.

  4. 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.

  5. Efficient Design of Distribution Logistics by Using a Model-Based Decision Support System

    OpenAIRE

    J. Becker; R. Arnold

    2016-01-01

    The design of distribution logistics has a decisive impact on a company's logistics costs and performance. Hence, such solutions make an essential contribution to corporate success. This article describes a decision support system for analyzing the potential of distribution logistics in terms of logistics costs and performance. In contrast to previous procedures of business process re-engineering (BPR), this method maps distribution logistics holistically under variable distribution structure...

  6. Decision making for business model development : A process study of effectuation and causation in new technology-based ventures

    NARCIS (Netherlands)

    Reymen, Isabelle; Berends, Hans; Oudehand, Rob; Stultiëns, Rutger

    2017-01-01

    This study investigates the decision-making logics used by new ventures to develop their business models. In particular, they focussed on the logics of effectuation and causation and how their dynamics shape the development of business models over time. They found that the effectual decision-making

  7. 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.

  8. 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.

  9. 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....

  10. 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)

  11. Expert judgment based multi-criteria decision model to address uncertainties in risk assessment of nanotechnology-enabled food products

    International Nuclear Information System (INIS)

    Flari, Villie; Chaudhry, Qasim; Neslo, Rabin; Cooke, Roger

    2011-01-01

    Currently, risk assessment of nanotechnology-enabled food products is considered difficult due to the large number of uncertainties involved. We developed an approach which could address some of the main uncertainties through the use of expert judgment. Our approach employs a multi-criteria decision model, based on probabilistic inversion that enables capturing experts’ preferences in regard to safety of nanotechnology-enabled food products, and identifying their opinions in regard to the significance of key criteria that are important in determining the safety of such products. An advantage of these sample-based techniques is that they provide out-of-sample validation and therefore a robust scientific basis. This validation in turn adds predictive power to the model developed. We achieved out-of-sample validation in two ways: (1) a portion of the expert preference data was excluded from the model’s fitting and was then predicted by the model fitted on the remaining rankings and (2) a (partially) different set of experts generated new scenarios, using the same criteria employed in the model, and ranked them; their ranks were compared with ranks predicted by the model. The degree of validation in each method was less than perfect but reasonably substantial. The validated model we applied captured and modelled experts’ preferences regarding safety of hypothetical nanotechnology-enabled food products. It appears therefore that such an approach can provide a promising route to explore further for assessing the risk of nanotechnology-enabled food products.

  12. Model-based decision making in early clinical development: minimizing the impact of a blood pressure adverse event.

    Science.gov (United States)

    Stroh, Mark; Addy, Carol; Wu, Yunhui; Stoch, S Aubrey; Pourkavoos, Nazaneen; Groff, Michelle; Xu, Yang; Wagner, John; Gottesdiener, Keith; Shadle, Craig; Wang, Hong; Manser, Kimberly; Winchell, Gregory A; Stone, Julie A

    2009-03-01

    We describe how modeling and simulation guided program decisions following a randomized placebo-controlled single-rising oral dose first-in-man trial of compound A where an undesired transient blood pressure (BP) elevation occurred in fasted healthy young adult males. We proposed a lumped-parameter pharmacokinetic-pharmacodynamic (PK/PD) model that captured important aspects of the BP homeostasis mechanism. Four conceptual units characterized the feedback PD model: a sinusoidal BP set point, an effect compartment, a linear effect model, and a system response. To explore approaches for minimizing the BP increase, we coupled the PD model to a modified PK model to guide oral controlled-release (CR) development. The proposed PK/PD model captured the central tendency of the observed data. The simulated BP response obtained with theoretical release rate profiles suggested some amelioration of the peak BP response with CR. This triggered subsequent CR formulation development; we used actual dissolution data from these candidate CR formulations in the PK/PD model to confirm a potential benefit in the peak BP response. Though this paradigm has yet to be tested in the clinic, our model-based approach provided a common rational framework to more fully utilize the limited available information for advancing the program.

  13. Interorganizational Knowledge Division Decision Model Based on Cooperative Innovation of Supply Chain System

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2014-01-01

    Full Text Available Within interorganizational cooperative innovation of construction supply chain system, the achievement of project value-adding could be reflected by several factors, such as project-based organizational effect level, and the relationship between project cooperative innovation objectives. In this paper, based on the assumption of equal cooperation between project-based organizations, we selected the knowledge cooperation between the owner and contractor in construction supply chain system as research object. From the perspective of maximizing project value-adding and the relationship of effort cost between knowledge input and innovation stage in consideration, we established the knowledge collaborative incentive model for interorganizational cooperative innovation of construction supply chain system and proposed the first-order and second-order approaches. Then we conducted the digital simulation and example analysis, its results showed that if the owner has the capability to achieve project value-adding in knowledge cooperation, he would adopt a part commissioned way. Otherwise, a fully commissioned way would be better.

  14. 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

  15. 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.

  16. Design of multilevel flow modelling-based decision support system by using multiagent platform

    DEFF Research Database (Denmark)

    Zhang, Xinxin; Lind, Morten; Ravn, Ole

    2015-01-01

    For complex engineering systems, there is an increasing demand forsafety and reliability. Decision support system (DSS) is designed to offersupervision and analysis about operational situations. A proper modelrepresentation is required for DSS to understand the process knowledge.Multilevel flow...... available techniques of MFM reasoning and less matureyet relevant MFM concepts are considered. It also offers an architecture designof task organisation for MFM software tools by using the concept of agent andtechnology of multiagent software system...

  17. Developed Model for Debts Relief Decision Based on Financial and Accounting Reports Applied on PORT TRANS EUROPE SA

    Directory of Open Access Journals (Sweden)

    Riana Iren RADU

    2013-12-01

    Full Text Available Business agents are today facing with a dynamic economic environment transformed by the direct effects of the economic crisis. In these circumstances the managers of the entities are forced to adapt to the economic activities by various types of decisions. A special attention is paid to financial decisions. Financial issues touch all aspects of economic life of an agent. In this context are fitting the management of debts. Management of debts problem can be addressed through a decision-making model. In this paper we propose the development of a multidimensional decision to be strengthened the management of debts of PORT TRANS EUROPE SA, in order to reduce them.

  18. 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.

  19. Knowledge service decision making in business incubators based on the supernetwork model

    Science.gov (United States)

    Zhao, Liming; Zhang, Haihong; Wu, Wenqing

    2017-08-01

    As valuable resources for incubating firms, knowledge resources have received gradually increasing attention from all types of business incubators, and business incubators use a variety of knowledge services to stimulate rapid growth in incubating firms. Based on previous research, we generalize the knowledge transfer and knowledge networking services of two main forms of knowledge services and further divide knowledge transfer services into knowledge depth services and knowledge breadth services. Then, we construct the business incubators' knowledge supernetwork model, describe the evolution mechanism among heterogeneous agents and utilize a simulation to explore the performance variance of different business incubators' knowledge services. The simulation results show that knowledge stock increases faster when business incubators are able to provide knowledge services to more incubating firms and that the degree of discrepancy in the knowledge stock increases during the process of knowledge growth. Further, knowledge transfer services lead to greater differences in the knowledge structure, while knowledge networking services lead to smaller differences. Regarding the two types of knowledge transfer services, knowledge depth services are more conducive to knowledge growth than knowledge breadth services, but knowledge depth services lead to greater gaps in knowledge stocks and greater differences in knowledge structures. Overall, it is optimal for business incubators to select a single knowledge service or portfolio strategy based on the amount of time and energy expended on the two types of knowledge services.

  20. Decision-making based on emotional images.

    Science.gov (United States)

    Katahira, Kentaro; Fujimura, Tomomi; Okanoya, Kazuo; Okada, Masato

    2011-01-01

    The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants' choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward, the "reward value" of the decision outcome, which guided the update of value for each choice, is unknown beforehand. To estimate the reward value of emotional pictures from participants' choice data, we used reinforcement learning models that have successfully been used in previous studies for modeling value-based decision making. Consequently, we found that the estimated reward value was asymmetric between positive and negative pictures. The negative reward value of negative pictures (relative to neutral pictures) was larger in magnitude than the positive reward value of positive pictures. This asymmetry was not observed in valence for an individual picture, which was rated by the participants regarding the emotion experienced upon viewing it. These results suggest that there may be a difference between experienced emotion and the effect of the experienced emotion on subsequent behavior. Our experimental and computational paradigm provides a novel way for quantifying how and what aspects of emotional events affect human behavior. The present study is a first step toward relating a large amount of knowledge in emotion science and in taking computational approaches to value-based decision making.

  1. 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

  2. Applications of decision theory to test-based decision making

    NARCIS (Netherlands)

    van der Linden, Willem J.

    1987-01-01

    The use of Bayesian decision theory to solve problems in test-based decision making is discussed. Four basic decision problems are distinguished: (1) selection; (2) mastery; (3) placement; and (4) classification, the situation where each treatment has its own criterion. Each type of decision can be

  3. 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.

  4. 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.

  5. Handling equipment Selection in open pit mines by using an integrated model based on group decision making

    Directory of Open Access Journals (Sweden)

    Abdolreza Yazdani-Chamzini

    2012-10-01

    Full Text Available Process of handling equipment selection is one of the most important and basic parts in the project planning, particularly mining projects due to holding a high charge of the total project's cost. Different criteria impact on the handling equipment selection, while these criteria often are in conflicting with each other. Therefore, the process of handling equipment selection is a complex and multi criteria decision making problem. There are a variety of methods for selecting the most appropriate equipment among a set of alternatives. Likewise, according to the sophisticated structure of the problem, imprecise data, less of information, and inherent uncertainty, the usage of the fuzzy sets can be useful. In this study a new integrated model based on fuzzy analytic hierarchy process (FAHP and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS is proposed, which uses group decision making to reduce individual errors. In order to calculate the weights of the evaluation criteria, FAHP is utilized in the process of handling equipment selection, and then these weights are inserted to the FTOPSIS computations to select the most appropriate handling system among a pool of alternatives. The results of this study demonstrate the potential application and effectiveness of the proposed model, which can be applied to different types of sophisticated problems in real problems.

  6. Research on efficiency evaluation model of integrated energy system based on hybrid multi-attribute decision-making.

    Science.gov (United States)

    Li, Yan

    2017-05-25

    The efficiency evaluation model of integrated energy system, involving many influencing factors, and the attribute values are heterogeneous and non-deterministic, usually cannot give specific numerical or accurate probability distribution characteristics, making the final evaluation result deviation. According to the characteristics of the integrated energy system, a hybrid multi-attribute decision-making model is constructed. The evaluation model considers the decision maker's risk preference. In the evaluation of the efficiency of the integrated energy system, the evaluation value of some evaluation indexes is linguistic value, or the evaluation value of the evaluation experts is not consistent. These reasons lead to ambiguity in the decision information, usually in the form of uncertain linguistic values and numerical interval values. In this paper, the risk preference of decision maker is considered when constructing the evaluation model. Interval-valued multiple-attribute decision-making method and fuzzy linguistic multiple-attribute decision-making model are proposed. Finally, the mathematical model of efficiency evaluation of integrated energy system is constructed.

  7. Hospital-Based Physicians' Intubation Decisions and Associated Mental Models when Managing a Critically and Terminally Ill Older Patient.

    Science.gov (United States)

    Haliko, Shannon; Downs, Julie; Mohan, Deepika; Arnold, Robert; Barnato, Amber E

    2018-04-01

    Variation in the intensity of acute care treatment at the end of life is influenced more strongly by hospital and provider characteristics than patient preferences. We sought to describe physicians' mental models (i.e., thought processes) when encountering a simulated critically and terminally ill older patient, and to compare those models based on whether their treatment plan was patient preference-concordant or preference-discordant. Seventy-three hospital-based physicians from 3 academic medical centers engaged in a simulated patient encounter and completed a mental model interview while watching the video recording of their encounter. We used an "expert" model to code the interviews. We then used Kruskal-Wallis tests to compare the weighted mental model themes of physicians who provided preference-concordant treatment with those who provided preference-discordant treatment. Sixty-six (90%) physicians provided preference-concordant treatment and 7 (10%) provided preference-discordant treatment (i.e., they intubated the patient). Physicians who intubated the patient were more likely to emphasize the reversible and emergent nature of the patient situation (z = -2.111, P = 0.035), their own comfort (z = -2.764, P = 0.006), and rarely focused on explicit patient preferences (z = 2.380, P = 0.017). Post-decisional interviewing with audio/video prompting may induce hindsight bias. The expert model has not yet been validated and may not be exhaustive. The small sample size limits generalizability and power. Hospital-based physicians providing preference-discordant used a different mental model for decision making for a critically and terminally ill simulated case. These differences may offer targets for future interventions to promote preference-concordant care for seriously ill patients.

  8. Pattern-based Automatic Translation of Structured Power System Data to Functional Models for Decision Support Applications

    DEFF Research Database (Denmark)

    Heussen, Kai; Weckesser, Johannes Tilman Gabriel; Kullmann, Daniel

    2013-01-01

    Improved information and insight for decision support in operations and design are central promises of a smart grid. Well-structured information about the composition of power systems is increasingly becoming available in the domain, e.g. due to standard information models (e.g. CIM or IEC61850......) or otherwise structured databases. More measurements and data do not automatically improve decisions, but there is an opportunity to capitalize on this information for decision support. With suitable reasoning strategies data can be contextualized and decision-relevant events can be promoted and identified....... This paper presents an approach to link available structured power system data directly to a functional representation suitable for diagnostic reasoning. The translation method is applied to test cases also illustrating decision support....

  9. Active vision and image/video understanding with decision structures based on the network-symbolic models

    Science.gov (United States)

    Kuvich, Gary

    2003-08-01

    Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. The ability of human brain to emulate knowledge structures in the form of networks-symbolic models is found. And that means an important shift of paradigm in our knowledge about brain from neural networks to "cortical software". Symbols, predicates and grammars naturally emerge in such active multilevel hierarchical networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type decision structure created via multilevel hierarchical compression of visual information. Mid-level vision processes like clustering, perceptual grouping, separation of figure from ground, are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena are results of such analysis. Composition of network-symbolic models works similar to frames and agents, combines learning, classification, analogy together with higher-level model-based reasoning into a single framework. Such models do not require supercomputers. Based on such principles, and using methods of Computational intelligence, an Image Understanding system can convert images into the network-symbolic knowledge models, and effectively resolve uncertainty and ambiguity, providing unifying representation for perception and cognition. That allows creating new intelligent computer vision systems for robotic and defense industries.

  10. A methodology for eliciting, representing, and analysing stakeholder knowledge for decision making on complex socio-ecological systems: from cognitive maps to agent-based models.

    Science.gov (United States)

    Elsawah, Sondoss; Guillaume, Joseph H A; Filatova, Tatiana; Rook, Josefine; Jakeman, Anthony J

    2015-03-15

    This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation models (quantitative) with the ultimate goal of improving understanding and communication about decision making in complex socio-ecological systems. The methodology integrates cognitive mapping and agent based modelling. It cascades through a sequence of qualitative/soft and numerical methods comprising: (1) Interviews to elicit mental models; (2) Cognitive maps to represent and analyse individual and group mental models; (3) Time-sequence diagrams to chronologically structure the decision making process; (4) All-encompassing conceptual model of decision making, and (5) computational (in this case agent-based) Model. We apply the proposed methodology (labelled ICTAM) in a case study of viticulture irrigation in South Australia. Finally, we use strengths-weakness-opportunities-threats (SWOT) analysis to reflect on the methodology. Results show that the methodology leverages the use of cognitive mapping to capture the richness of decision making and mental models, and provides a combination of divergent and convergent analysis methods leading to the construction of an Agent Based Model. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. A cloud model based multi-attribute decision making approach for selection and evaluation of groundwater management schemes

    Science.gov (United States)

    Lu, Hongwei; Ren, Lixia; Chen, Yizhong; Tian, Peipei; Liu, Jia

    2017-12-01

    Due to the uncertainty (i.e., fuzziness, stochasticity and imprecision) existed simultaneously during the process for groundwater remediation, the accuracy of ranking results obtained by the traditional methods has been limited. This paper proposes a cloud model based multi-attribute decision making framework (CM-MADM) with Monte Carlo for the contaminated-groundwater remediation strategies selection. The cloud model is used to handle imprecise numerical quantities, which can describe the fuzziness and stochasticity of the information fully and precisely. In the proposed approach, the contaminated concentrations are aggregated via the backward cloud generator and the weights of attributes are calculated by employing the weight cloud module. A case study on the remedial alternative selection for a contaminated site suffering from a 1,1,1-trichloroethylene leakage problem in Shanghai, China is conducted to illustrate the efficiency and applicability of the developed approach. Totally, an attribute system which consists of ten attributes were used for evaluating each alternative through the developed method under uncertainty, including daily total pumping rate, total cost and cloud model based health risk. Results indicated that A14 was evaluated to be the most preferred alternative for the 5-year, A5 for the 10-year, A4 for the 15-year and A6 for the 20-year remediation.

  12. An evidence-based decision assistance model for predicting training outcome in juvenile guide dogs.

    Science.gov (United States)

    Harvey, Naomi D; Craigon, Peter J; Blythe, Simon A; England, Gary C W; Asher, Lucy

    2017-01-01

    Working dog organisations, such as Guide Dogs, need to regularly assess the behaviour of the dogs they train. In this study we developed a questionnaire-style behaviour assessment completed by training supervisors of juvenile guide dogs aged 5, 8 and 12 months old (n = 1,401), and evaluated aspects of its reliability and validity. Specifically, internal reliability, temporal consistency, construct validity, predictive criterion validity (comparing against later training outcome) and concurrent criterion validity (comparing against a standardised behaviour test) were evaluated. Thirty-nine questions were sourced either from previously published literature or created to meet requirements identified via Guide Dogs staff surveys and staff feedback. Internal reliability analyses revealed seven reliable and interpretable trait scales named according to the questions within them as: Adaptability; Body Sensitivity; Distractibility; Excitability; General Anxiety; Trainability and Stair Anxiety. Intra-individual temporal consistency of the scale scores between 5-8, 8-12 and 5-12 months was high. All scales excepting Body Sensitivity showed some degree of concurrent criterion validity. Predictive criterion validity was supported for all seven scales, since associations were found with training outcome, at at-least one age. Thresholds of z-scores on the scales were identified that were able to distinguish later training outcome by identifying 8.4% of all dogs withdrawn for behaviour and 8.5% of all qualified dogs, with 84% and 85% specificity. The questionnaire assessment was reliable and could detect traits that are consistent within individuals over time, despite juvenile dogs undergoing development during the study period. By applying thresholds to scores produced from the questionnaire this assessment could prove to be a highly valuable decision-making tool for Guide Dogs. This is the first questionnaire-style assessment of juvenile dogs that has shown value in predicting

  13. A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images.

    Science.gov (United States)

    Bi, Fukun; Chen, Jing; Zhuang, Yin; Bian, Mingming; Zhang, Qingjun

    2017-06-22

    With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency.

  14. Consumer Product Data for Exposure Screening, Modeling and Prioritization, and Risk-based Decision Making

    Science.gov (United States)

    This presentation will provide an overview of the research efforts underway in EPA ORD's Chemicals for Safety and Sustainability research program which relate to providing information to prioritize chemicals in consumer products based on risk. It also describes effort to make dat...

  15. Strategies for memory-based decision making : Modeling behavioral and neural signatures within a cognitive architecture

    NARCIS (Netherlands)

    Fechner, Hanna B; Pachur, Thorsten; Schooler, Lael J; Mehlhorn, Katja; Battal, Ceren; Volz, Kirsten G; Borst, Jelmer P.

    2016-01-01

    How do people use memories to make inferences about real-world objects? We tested three strategies based on predicted patterns of response times and blood-oxygen-level-dependent (BOLD) responses: one strategy that relies solely on recognition memory, a second that retrieves additional knowledge, and

  16. Management of the Area 5 Radioactive Waste Management Site using Decision-based, Probabilistic Performance Assessment Modeling

    International Nuclear Information System (INIS)

    Carilli, J.; Crowe, B.; Black, P.; Tauxe, J.; Stockton, T.; Catlett, K.; Yucel, V.

    2003-01-01

    Low-level radioactive waste from cleanup activities at the Nevada Test Site and from multiple sites across the U.S. Department of Energy (DOE) complex is disposed at two active Radioactive Waste Management Sites (RWMS) on the Nevada Test Site. These facilities, which are managed by the DOE National Nuclear Security Administration Nevada Site Office, were recently designated as one of two regional disposal centers and yearly volumes of disposed waste now exceed 50,000 m3 (> 2 million ft3). To safely and cost-effectively manage the disposal facilities, the Waste Management Division of Environmental Management has implemented decision-based management practices using flexible and problem-oriented probabilistic performance assessment modeling. Deterministic performance assessments and composite analyses were completed originally for the Area 5 and Area 3 RWMSs located in, respectively, Frenchman Flat and Yucca Flat on the Nevada Test Site. These documents provide the technical bases for issuance of disposal authorization statements for continuing operation of the disposal facilities. Both facilities are now in a maintenance phase that requires testing of conceptual models, reduction of uncertainty, and site monitoring all leading to eventual closure of the facilities and transition to long-term stewardship

  17. Advances in the application of decision theory to test-based decision making

    NARCIS (Netherlands)

    van der Linden, Willem J.

    This paper reviews recent research in the Netherlands on the application of decision theory to test-based decision making about personnel selection and student placement. The review is based on an earlier model proposed for the classification of decision problems, and emphasizes an empirical

  18. 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....

  19. Assessment of Urban Ecosystem Health Based on Entropy Weight Extension Decision Model in Urban Agglomeration

    Directory of Open Access Journals (Sweden)

    Qian Yang

    2016-08-01

    Full Text Available Urban ecosystem health evaluation can assist in sustainable ecological management at a regional level. This study examined urban agglomeration ecosystem health in the middle reaches of the Yangtze River with entropy weight and extension theories. The model overcomes information omissions and subjectivity problems in the evaluation process of urban ecosystem health. Results showed that human capital and education, economic development level as well as urban infrastructure have a significant effect on the health states of urban agglomerations. The health status of the urban agglomeration’s ecosystem was not optimistic in 2013. The majority of the cities were unhealthy or verging on unhealthy, accounting for 64.52% of the total number of cities in the urban agglomeration. The regional differences of the 31 cities’ ecosystem health are significant. The cause originated from an imbalance in economic development and the policy guidance of city development. It is necessary to speed up the integration process to promote coordinated regional development. The present study will aid us in understanding and advancing the health situation of the urban ecosystem in the middle reaches of the Yangtze River and will provide an efficient urban ecosystem health evaluation method that can be used in other areas.

  20. Evaluation of Performance of Investment Funds Based on Decision Models (DEA

    Directory of Open Access Journals (Sweden)

    Alireza Samet

    2016-12-01

    Full Text Available Selection of a suitable investment funds is very important from investors' point of view and may have a significant impact on the profit or loss of the funds. Therefore, evaluation of performance of investment funds to choose the most suitable fund will be given special emphasis. One of the new techniques for evaluating the performance of the Funds based on efficiency is the Data Envelopment Analysis technique. Accordingly, the present study is aimed to analyze and evaluate the performance of investment Funds in capital market of Iran, using the technique of efficiency evaluation through data envelopment analysis technique (DEA. This research is a descriptive - applicable study and to analyze the efficiency and effectiveness, 53 investment funds in the capital market of Iran in 2013 were considered as the sample. To analyze the efficiency of these funds, data envelopment analysis (DEA is used. Research findings showed that in 2013, of a total of 53 examined funds, 11 funds were in the efficiency situation and the other 42 funds were in a state of inefficiency. Also the reference funds and virtual composited funds of all inefficient funds were evaluated.

  1. Research on investment decisions model of trans-regional transmission network based on the theory of NPV

    Science.gov (United States)

    Zai, Wenjiao; Wang, Bo; Liu, Jichun; Shi, Haobo; Zeng, Pingliang

    2018-02-01

    The investment decision model of trans-regional transmission network in the context of Global Energy Internet was studied in this paper. The key factors affecting the trans-regional transmission network investment income: the income tax rate, the loan interest rate, the expected return on investment of the investment subject, the per capita GDP and so on were considered in the transmission network investment income model. First, according to the principle of system dynamics, the causality diagram of key factors was constructed. Then, the dynamic model of transmission investment decision was established. A case study of the power transmission network between China and Mongolia, through the simulation of the system dynamic model, the influence of the above key factors on the investment returns was analyzed, and the feasibility and effectiveness of the model was proved.

  2. Decision making based on emotional images

    Directory of Open Access Journals (Sweden)

    Kentaro eKatahira

    2011-10-01

    Full Text Available The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants’ choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward, the reward value of the decision outcome, which guided the update of value for each choice, is unknown beforehand. To estimate the reward value of emotional pictures from participants’ choice data, we used reinforcement learning models that have success- fully been used in previous studies for modeling value-based decision making. Consequently, we found that the estimated reward value was asymmetric between positive and negative pictures. The negative reward value of negative pictures (relative to neutral pictures was larger in magnitude than the positive reward value of positive pictures. This asymmetry was not observed in valence for an individual picture, which was rated by the participants regarding the emotion experienced upon viewing it. These results suggest that there may be a difference between experienced emotion and the effect of the experienced emotion on subsequent behavior. Our experimental and computational paradigm provides a novel way for quantifying how and what aspects of emotional events affect human behavior. The present study is a first step toward relating a large amount of knowledge in emotion science and in taking computational approaches to value-based decision making.

  3. 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.

  4. Proposal optimization in nuclear accident emergency decision based on IAHP

    International Nuclear Information System (INIS)

    Xin Jing

    2007-01-01

    On the basis of establishing the multi-layer structure of nuclear accident emergency decision, several decision objectives are synthetically analyzed, and an optimization model of decision proposals for nuclear accident emergency based on interval analytic hierarchy process is proposed in the paper. The model makes comparisons among several emergency decision proposals quantified, and the optimum proposal is selected out, which solved the uncertain and fuzzy decision problem of judgments by experts' experiences in nuclear accidents emergency decision. Case study shows that the optimization result is much more reasonable, objective and reliable than subjective judgments, and it could be decision references for nuclear accident emergency. (authors)

  5. Cross-site comparison of land-use decision-making and its consequences across land systems with a generalized agent-based model.

    Science.gov (United States)

    Magliocca, Nicholas R; Brown, Daniel G; Ellis, Erle C

    2014-01-01

    Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM) as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model) landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model enhancement.

  6. Cross-site comparison of land-use decision-making and its consequences across land systems with a generalized agent-based model.

    Directory of Open Access Journals (Sweden)

    Nicholas R Magliocca

    Full Text Available Local changes in land use result from the decisions and actions of land-users within land systems, which are structured by local and global environmental, economic, political, and cultural contexts. Such cross-scale causation presents a major challenge for developing a general understanding of how local decision-making shapes land-use changes at the global scale. This paper implements a generalized agent-based model (ABM as a virtual laboratory to explore how global and local processes influence the land-use and livelihood decisions of local land-users, operationalized as settlement-level agents, across the landscapes of six real-world test sites. Test sites were chosen in USA, Laos, and China to capture globally-significant variation in population density, market influence, and environmental conditions, with land systems ranging from swidden to commercial agriculture. Publicly available global data were integrated into the ABM to model cross-scale effects of economic globalization on local land-use decisions. A suite of statistics was developed to assess the accuracy of model-predicted land-use outcomes relative to observed and random (i.e. null model landscapes. At four of six sites, where environmental and demographic forces were important constraints on land-use choices, modeled land-use outcomes were more similar to those observed across sites than the null model. At the two sites in which market forces significantly influenced land-use and livelihood decisions, the model was a poorer predictor of land-use outcomes than the null model. Model successes and failures in simulating real-world land-use patterns enabled the testing of hypotheses on land-use decision-making and yielded insights on the importance of missing mechanisms. The virtual laboratory approach provides a practical framework for systematic improvement of both theory and predictive skill in land change science based on a continual process of experimentation and model

  7. Optimal policy for value-based decision-making.

    Science.gov (United States)

    Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre

    2016-08-18

    For decades now, normative theories of perceptual decisions, and their implementation as drift diffusion models, have driven and significantly improved our understanding of human and animal behaviour and the underlying neural processes. While similar processes seem to govern value-based decisions, we still lack the theoretical understanding of why this ought to be the case. Here, we show that, similar to perceptual decisions, drift diffusion models implement the optimal strategy for value-based decisions. Such optimal decisions require the models' decision boundaries to collapse over time, and to depend on the a priori knowledge about reward contingencies. Diffusion models only implement the optimal strategy under specific task assumptions, and cease to be optimal once we start relaxing these assumptions, by, for example, using non-linear utility functions. Our findings thus provide the much-needed theory for value-based decisions, explain the apparent similarity to perceptual decisions, and predict conditions under which this similarity should break down.

  8. An interval-valued 2-tuple linguistic group decision-making model based on the Choquet integral operator

    Science.gov (United States)

    Liu, Bingsheng; Fu, Meiqing; Zhang, Shuibo; Xue, Bin; Zhou, Qi; Zhang, Shiruo

    2018-01-01

    The Choquet integral (IL) operator is an effective approach for handling interdependence among decision attributes in complex decision-making problems. However, the fuzzy measures of attributes and attribute sets required by IL are difficult to achieve directly, which limits the application of IL. This paper proposes a new method for determining fuzzy measures of attributes by extending Marichal's concept of entropy for fuzzy measure. To well represent the assessment information, interval-valued 2-tuple linguistic context is utilised to represent information. Then, we propose a Choquet integral operator in an interval-valued 2-tuple linguistic environment, which can effectively handle the correlation between attributes. In addition, we apply these methods to solve multi-attribute group decision-making problems. The feasibility and validity of the proposed operator is demonstrated by comparisons with other models in illustrative example part.

  9. Developing a decision-making model based on an interdisciplinary oncological care group for the management of colorectal cancer.

    Science.gov (United States)

    Genovesi, Domenico; Mazzilli, Lorenzo; Trignani, Marianna; DI Tommaso, Monica; Nuzzo, Antonio; Biondi, Edoardo; Tinari, Nicola; Martino, Maria Teresa; Innocenti, Paolo; DI Sebastiano, Pierluigi; Mazzola, Lorenzo; Lanci, Carmine; Neri, Matteo; Laterza, Francesco; Marino, Maria; Ferrini, Giovanni; Spadaccini, Antonio; Filippone, Antonella; DI Giandomenico, Enzo; Marulli, Antonio; Palombo, Giuseppe; Sparvieri, Antonio; Marchetti, Antonio; Pizzicannella, Giuseppe; Petrini, Flavia; DI Felice, Maria; Ottaviani, Floriana; Monteodorisio, Antonio; DI Nicola, Marta; Cefaro, Giampiero Ausili

    2014-05-01

    To report our experience on implementation and preliminary results of a decision-making model based on the recommendations of an Interdisciplinary Oncological Care Group developed for the management of colorectal cancer. The multidisciplinary team identified a reference guideline using appraisal of guidelines for research and evaluation (AGREE) tool based on a sequential assessment of the guideline quality. Thereafter, internal guidelines with diagnostic and therapeutic management for early, locally advanced and metastatic colonic and rectal cancer were drafted; organizational aspects, responsibility matrices, protocol actions for each area of specialty involved and indicators for performing audits were also defined. The National Institute for Health and Care Excellence (NICE) UK guideline was the reference for drafting the internal guideline document; from February to November 2013, 125 patients with colorectal cancer were discussed by and taken under the care of the Interdisciplinary Oncological Care Group. The first audit performed in December 2013 revealed optimal adherence to the internal guideline, mainly in terms of uniformity and accuracy of perioperative staging, coordination and timing of multi-modal therapies. To date, all patients under observation are within the diagnostic and therapeutic course, no patient came out from the multidisciplinary "path" and only in 14% of cases have the first recommendations proposed been changed. The selected indicators appear effective and reliable, while at the moment, it is not yet possible to assess the impact of the multidisciplinary team on clinical outcome. Although having a short observation period, our model seems capable of determining optimal uniformity of diagnostic and therapeutic management, to a high degree of patient satisfaction. A longer observation period is necessary in order to confirm these observations and for assessing the impact on clinical outcome.

  10. Towards a cognitive robotics methodology for reward-based decision-making: dynamical systems modelling of the Iowa Gambling Task

    Science.gov (United States)

    Lowe, Robert; Ziemke, Tom

    2010-09-01

    The somatic marker hypothesis (SMH) posits that the role of emotions and mental states in decision-making manifests through bodily responses to stimuli of import to the organism's welfare. The Iowa Gambling Task (IGT), proposed by Bechara and Damasio in the mid-1990s, has provided the major source of empirical validation to the role of somatic markers in the service of flexible and cost-effective decision-making in humans. In recent years the IGT has been the subject of much criticism concerning: (1) whether measures of somatic markers reveal that they are important for decision-making as opposed to behaviour preparation; (2) the underlying neural substrate posited as critical to decision-making of the type relevant to the task; and (3) aspects of the methodological approach used, particularly on the canonical version of the task. In this paper, a cognitive robotics methodology is proposed to explore a dynamical systems approach as it applies to the neural computation of reward-based learning and issues concerning embodiment. This approach is particularly relevant in light of a strongly emerging alternative hypothesis to the SMH, the reversal learning hypothesis, which links, behaviourally and neurocomputationally, a number of more or less complex reward-based decision-making tasks, including the 'A-not-B' task - already subject to dynamical systems investigations with a focus on neural activation dynamics. It is also suggested that the cognitive robotics methodology may be used to extend systematically the IGT benchmark to more naturalised, but nevertheless controlled, settings that might better explore the extent to which the SMH, and somatic states per se, impact on complex decision-making.

  11. Discussing Landscape Compositional Scenarios Generated with Maximization of Non-Expected Utility Decision Models Based on Weighted Entropies

    Directory of Open Access Journals (Sweden)

    José Pinto Casquilho

    2017-02-01

    Full Text Available The search for hypothetical optimal solutions of landscape composition is a major issue in landscape planning and it can be outlined in a two-dimensional decision space involving economic value and landscape diversity, the latter being considered as a potential safeguard to the provision of services and externalities not accounted in the economic value. In this paper, we use decision models with different utility valuations combined with weighted entropies respectively incorporating rarity factors associated to Gini-Simpson and Shannon measures. A small example of this framework is provided and discussed for landscape compositional scenarios in the region of Nisa, Portugal. The optimal solutions relative to the different cases considered are assessed in the two-dimensional decision space using a benchmark indicator. The results indicate that the likely best combination is achieved by the solution using Shannon weighted entropy and a square root utility function, corresponding to a risk-averse behavior associated to the precautionary principle linked to safeguarding landscape diversity, anchoring for ecosystem services provision and other externalities. Further developments are suggested, mainly those relative to the hypothesis that the decision models here outlined could be used to revisit the stability-complexity debate in the field of ecological studies.

  12. Using Virtual Reality to Assess Ethical Decisions in Road Traffic Scenarios: Applicability of Value-of-Life-Based Models and Influences of Time Pressure

    Directory of Open Access Journals (Sweden)

    Leon R. Sütfeld

    2017-07-01

    Full Text Available Self-driving cars are posing a new challenge to our ethics. By using algorithms to make decisions in situations where harming humans is possible, probable, or even unavoidable, a self-driving car's ethical behavior comes pre-defined. Ad hoc decisions are made in milliseconds, but can be based on extensive research and debates. The same algorithms are also likely to be used in millions of cars at a time, increasing the impact of any inherent biases, and increasing the importance of getting it right. Previous research has shown that moral judgment and behavior are highly context-dependent, and comprehensive and nuanced models of the underlying cognitive processes are out of reach to date. Models of ethics for self-driving cars should thus aim to match human decisions made in the same context. We employed immersive virtual reality to assess ethical behavior in simulated road traffic scenarios, and used the collected data to train and evaluate a range of decision models. In the study, participants controlled a virtual car and had to choose which of two given obstacles they would sacrifice in order to spare the other. We randomly sampled obstacles from a variety of inanimate objects, animals and humans. Our model comparison shows that simple models based on one-dimensional value-of-life scales are suited to describe human ethical behavior in these situations. Furthermore, we examined the influence of severe time pressure on the decision-making process. We found that it decreases consistency in the decision patterns, thus providing an argument for algorithmic decision-making in road traffic. This study demonstrates the suitability of virtual reality for the assessment of ethical behavior in humans, delivering consistent results across subjects, while closely matching the experimental settings to the real world scenarios in question.

  13. Using Virtual Reality to Assess Ethical Decisions in Road Traffic Scenarios: Applicability of Value-of-Life-Based Models and Influences of Time Pressure.

    Science.gov (United States)

    Sütfeld, Leon R; Gast, Richard; König, Peter; Pipa, Gordon

    2017-01-01

    Self-driving cars are posing a new challenge to our ethics. By using algorithms to make decisions in situations where harming humans is possible, probable, or even unavoidable, a self-driving car's ethical behavior comes pre-defined. Ad hoc decisions are made in milliseconds, but can be based on extensive research and debates. The same algorithms are also likely to be used in millions of cars at a time, increasing the impact of any inherent biases, and increasing the importance of getting it right. Previous research has shown that moral judgment and behavior are highly context-dependent, and comprehensive and nuanced models of the underlying cognitive processes are out of reach to date. Models of ethics for self-driving cars should thus aim to match human decisions made in the same context. We employed immersive virtual reality to assess ethical behavior in simulated road traffic scenarios, and used the collected data to train and evaluate a range of decision models. In the study, participants controlled a virtual car and had to choose which of two given obstacles they would sacrifice in order to spare the other. We randomly sampled obstacles from a variety of inanimate objects, animals and humans. Our model comparison shows that simple models based on one-dimensional value-of-life scales are suited to describe human ethical behavior in these situations. Furthermore, we examined the influence of severe time pressure on the decision-making process. We found that it decreases consistency in the decision patterns, thus providing an argument for algorithmic decision-making in road traffic. This study demonstrates the suitability of virtual reality for the assessment of ethical behavior in humans, delivering consistent results across subjects, while closely matching the experimental settings to the real world scenarios in question.

  14. 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

  15. 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. ...

  16. Decision support for choice optimal power generation projects: Fuzzy comprehensive evaluation model based on the electricity market

    International Nuclear Information System (INIS)

    Liang Zhihong; Yang Kun; Sun Yaowei; Yuan Jiahai; Zhang Hongwei; Zhang Zhizheng

    2006-01-01

    In 2002, China began to inspire restructuring of the electric power sector to improve its performance. Especially, with the rapid increase of electricity demand in China, there is a need for non-utility generation investment that cannot be met by government finance alone. However, a first prerequisite is that regulators and decision-makers (DMs) should carefully consider how to balance the need to attract private investment against the policy objectives of minimizing monopoly power and fostering competitive markets. So in the interim term of electricity market, a decentralized decision-making process should eventually replace the centralized generation capacity expansion planning. In this paper, firstly, on the basis of the current situation, a model for evaluating generation projects by comprehensive utilization of fuzzy appraisal and analytic hierarchy process (AHP) is developed. Secondly, a case study of generation project evaluation in China is presented to illustrate the effectiveness of the model in selecting optimal generation projects and attracting private investors. In the case study, with considerations of attracting adequate private investment and promoting energy conservation in China, five most promising policy instruments selected as evaluation factors include project duration, project costs, predicted on-grid price level, environmental protection, enterprise credit grading and performance. Finally, a comprehensive framework that enables the DM to have better concentration and to make more sound decisions by combining the model proposed with modern computer science is designed

  17. 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.

  18. 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...

  19. A text-based data mining and toxicity prediction modeling system for a clinical decision support in radiation oncology: A preliminary study

    Science.gov (United States)

    Kim, Kwang Hyeon; Lee, Suk; Shim, Jang Bo; Chang, Kyung Hwan; Yang, Dae Sik; Yoon, Won Sup; Park, Young Je; Kim, Chul Yong; Cao, Yuan Jie

    2017-08-01

    The aim of this study is an integrated research for text-based data mining and toxicity prediction modeling system for clinical decision support system based on big data in radiation oncology as a preliminary research. The structured and unstructured data were prepared by treatment plans and the unstructured data were extracted by dose-volume data image pattern recognition of prostate cancer for research articles crawling through the internet. We modeled an artificial neural network to build a predictor model system for toxicity prediction of organs at risk. We used a text-based data mining approach to build the artificial neural network model for bladder and rectum complication predictions. The pattern recognition method was used to mine the unstructured toxicity data for dose-volume at the detection accuracy of 97.9%. The confusion matrix and training model of the neural network were achieved with 50 modeled plans (n = 50) for validation. The toxicity level was analyzed and the risk factors for 25% bladder, 50% bladder, 20% rectum, and 50% rectum were calculated by the artificial neural network algorithm. As a result, 32 plans could cause complication but 18 plans were designed as non-complication among 50 modeled plans. We integrated data mining and a toxicity modeling method for toxicity prediction using prostate cancer cases. It is shown that a preprocessing analysis using text-based data mining and prediction modeling can be expanded to personalized patient treatment decision support based on big data.

  20. 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

  1. Expected Utility and Entropy-Based Decision-Making Model for Large Consumers in the Smart Grid

    Directory of Open Access Journals (Sweden)

    Bingtuan Gao

    2015-09-01

    Full Text Available In the smart grid, large consumers can procure electricity energy from various power sources to meet their load demands. To maximize its profit, each large consumer needs to decide their energy procurement strategy under risks such as price fluctuations from the spot market and power quality issues. In this paper, an electric energy procurement decision-making model is studied for large consumers who can obtain their electric energy from the spot market, generation companies under bilateral contracts, the options market and self-production facilities in the smart grid. Considering the effect of unqualified electric energy, the profit model of large consumers is formulated. In order to measure the risks from the price fluctuations and power quality, the expected utility and entropy is employed. Consequently, the expected utility and entropy decision-making model is presented, which helps large consumers to minimize their expected profit of electricity procurement while properly limiting the volatility of this cost. Finally, a case study verifies the feasibility and effectiveness of the proposed model.

  2. Rough set and rule-based multicriteria decision aiding

    Directory of Open Access Journals (Sweden)

    Roman Slowinski

    2012-08-01

    Full Text Available The aim of multicriteria decision aiding is to give the decision maker a recommendation concerning a set of objects evaluated from multiple points of view called criteria. Since a rational decision maker acts with respect to his/her value system, in order to recommend the most-preferred decision, one must identify decision maker's preferences. In this paper, we focus on preference discovery from data concerning some past decisions of the decision maker. We consider the preference model in the form of a set of "if..., then..." decision rules discovered from the data by inductive learning. To structure the data prior to induction of rules, we use the Dominance-based Rough Set Approach (DRSA. DRSA is a methodology for reasoning about data, which handles ordinal evaluations of objects on considered criteria and monotonic relationships between these evaluations and the decision. We review applications of DRSA to a large variety of multicriteria decision problems.

  3. Decision-Making Based on Emotional Images

    OpenAIRE

    Katahira, Kentaro; Fujimura, Tomomi; Okanoya, Kazuo; Okada, Masato

    2011-01-01

    The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants’ choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward...

  4. Decision making based on emotional images

    OpenAIRE

    Kentaro eKatahira; Kentaro eKatahira; Kentaro eKatahira; Tomomi eFujimura; Tomomi eFujimura; Kazuo eOkanoya; Kazuo eOkanoya; Kazuo eOkanoya; Masato eOkada; Masato eOkada; Masato eOkada

    2011-01-01

    The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants’ choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward...

  5. 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.

  6. Ship Domain Model for Multi-ship Collision Avoidance Decision-making with COLREGs Based on Artificial Potential Field

    Directory of Open Access Journals (Sweden)

    TengFei Wang

    2017-03-01

    Full Text Available A multi-ship collision avoidance decision-making and path planning formulation is studied in a distributed way. This paper proposes a complete set of solutions for multi-ship collision avoidance in intelligent navigation, by using a top-to-bottom organization to structure the system. The system is designed with two layers: the collision avoidance decision-making and the path planning. Under the general requirements of the International Regulations for Preventing Collisions at Sea (COLREGs, the performance of distributed path planning decision-making for anti-collision is analyzed for both give-way and stand-on ships situations, including the emergency actions taken by the stand-on ship in case of the give-way ship’s fault of collision avoidance measures. The Artificial Potential Field method(APF is used for the path planning in details. The developed APF method combined with the model of ship domain takes the target ships’ speed and course in-to account, so that it can judge the moving characteristics of obstacles more accurately. Simulation results indicate that the system proposed can work effectiveness.

  7. Distinct alterations in value-based decision-making and cognitive control in suicide attempters: toward a dual neurocognitive model.

    Science.gov (United States)

    Richard-Devantoy, Stéphane; Olié, Emilie; Guillaume, Sébastien; Bechara, Antoine; Courtet, Philippe; Jollant, Fabrice

    2013-12-01

    The literature suggests that many suicide attempters show impairment in both decision-making and cognitive control. However, it is not clear if these deficits are linked to each other, and if they may be related to more basic alterations in attention. This is a relevant question in the perspective of future interventions targeting cognitive deficits to prevent suicidal acts. Two different populations of patients with histories of suicide attempts were assessed (N=142 and 119). The Iowa Gambling Task (IGT) was used to measure decision-making in both populations. We used a D2 cancellation task and a verbal working memory task in population 1; the Stroop test, the N-Back task, the Trail Making Test, and the Hayling Sentence Completion test in population 2. Regarding decision-making, we only found a small negative correlation between the Hayling test error score (r=-0.24; p=0.01), and the net score from the second half of the IGT. In contrast, working memory, cognitive flexibility and cognitive inhibition measures were largely inter-correlated. Most patients were medicated. Only patients with mood disorders. These results add to previous findings suggesting that the neurocognitive vulnerability to suicidal behavior may rely on impairments in two distinct anatomical systems, one processing value-based decision-making (associated with ventral prefrontal cortex, among others) and one underlying cognitive control (associated with more dorsal prefrontal regions). This distinction may result in tailored-made cognitive interventions. Copyright © 2013 Elsevier B.V. All rights reserved.

  8. An objective decision model of power grid environmental protection based on environmental influence index and energy-saving and emission-reducing index

    Science.gov (United States)

    Feng, Jun-shu; Jin, Yan-ming; Hao, Wei-hua

    2017-01-01

    Based on modelling the environmental influence index of power transmission and transformation project and energy-saving and emission-reducing index of source-grid-load of power system, this paper establishes an objective decision model of power grid environmental protection, with constraints of power grid environmental protection objectives being legal and economical, and considering both positive and negative influences of grid on the environmental in all-life grid cycle. This model can be used to guide the programming work of power grid environmental protection. A numerical simulation of Jiangsu province’s power grid environmental protection objective decision model has been operated, and the results shows that the maximum goal of energy-saving and emission-reducing benefits would be reached firstly as investment increasing, and then the minimum goal of environmental influence.

  9. Modeling approaches for characterizing and evaluating environmental exposure to engineered nanomaterials in support of risk-based decision making.

    Science.gov (United States)

    Hendren, Christine Ogilvie; Lowry, Michael; Grieger, Khara D; Money, Eric S; Johnston, John M; Wiesner, Mark R; Beaulieu, Stephen M

    2013-02-05

    As the use of engineered nanomaterials becomes more prevalent, the likelihood of unintended exposure to these materials also increases. Given the current scarcity of experimental data regarding fate, transport, and bioavailability, determining potential environmental exposure to these materials requires an in depth analysis of modeling techniques that can be used in both the near- and long-term. Here, we provide a critical review of traditional and emerging exposure modeling approaches to highlight the challenges that scientists and decision-makers face when developing environmental exposure and risk assessments for nanomaterials. We find that accounting for nanospecific properties, overcoming data gaps, realizing model limitations, and handling uncertainty are key to developing informative and reliable environmental exposure and risk assessments for engineered nanomaterials. We find methods suited to recognizing and addressing significant uncertainty to be most appropriate for near-term environmental exposure modeling, given the current state of information and the current insufficiency of established deterministic models to address environmental exposure to engineered nanomaterials.

  10. 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.

  11. 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.

  12. 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

  13. 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…

  14. 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...

  15. A Watershed-Scale Agent-Based Model Incorporating Agent Learning and Interaction of Farmers' Decisions Subject to Carbon and Miscanthus Prices

    Science.gov (United States)

    Ng, T.; Eheart, J.; Cai, X.; Braden, J. B.

    2010-12-01

    Agricultural watersheds are coupled human-natural systems where the land use decisions of human agents (farmers) affect surface water quality, and in turn, are affected by the weather and yields. The reliable modeling of such systems requires an approach that considers both the human and natural aspects. Agent-based modeling (ABM), representing the human aspect, coupled with hydrologic modeling, representing the natural aspect, is one such approach. ABM is a relatively new modeling paradigm that formulates the system from the perspectives of the individual agents, i.e., each agent is modeled as a discrete autonomous entity with distinct goals and actions. The primary objective of this study is to demonstrate the applicability of this approach to agricultural watershed management. This is done using a semi-hypothetical case study of farmers in the Salt Creek watershed in East-Central Illinois under the influence markets for carbon and second-generation bioenergy crop (specifically, miscanthus). An agent-based model of the system is developed and linked to a hydrologic model of the watershed. The former is based on fundamental economic and mathematical programming principles, while the latter is based on the Soil and Water Assessment Tool (SWAT). Carbon and second-generation bioenergy crop markets are of interest here due to climate change and energy independence concerns. The agent-based model is applied to fifty hypothetical heterogeneous farmers. The farmers' decisions depend on their perceptions of future conditions. Those perceptions are updated, according to a pre-defined algorithm, as the farmers make new observations of prices, costs, yields and the weather with time. The perceptions are also updated as the farmers interact with each other as they share new information on initially unfamiliar activities (e.g., carbon trading, miscanthus cultivation). The updating algorithm is set differently for different farmers such that each is unique in his processing of

  16. [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.

  17. 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...

  18. A decision-tree model to detect post-calving diseases based on rumination, activity, milk yield, BW and voluntary visits to the milking robot.

    Science.gov (United States)

    Steensels, M; Antler, A; Bahr, C; Berckmans, D; Maltz, E; Halachmi, I

    2016-09-01

    Early detection of post-calving health problems is critical for dairy operations. Separating sick cows from the herd is important, especially in robotic-milking dairy farms, where searching for a sick cow can disturb the other cows' routine. The objectives of this study were to develop and apply a behaviour- and performance-based health-detection model to post-calving cows in a robotic-milking dairy farm, with the aim of detecting sick cows based on available commercial sensors. The study was conducted in an Israeli robotic-milking dairy farm with 250 Israeli-Holstein cows. All cows were equipped with rumination- and neck-activity sensors. Milk yield, visits to the milking robot and BW were recorded in the milking robot. A decision-tree model was developed on a calibration data set (historical data of the 10 months before the study) and was validated on the new data set. The decision model generated a probability of being sick for each cow. The model was applied once a week just before the veterinarian performed the weekly routine post-calving health check. The veterinarian's diagnosis served as a binary reference for the model (healthy-sick). The overall accuracy of the model was 78%, with a specificity of 87% and a sensitivity of 69%, suggesting its practical value.

  19. 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.

  20. 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 ...

  1. Integration of Life Cycle Assessment Into Agent-Based Modeling : Toward Informed Decisions on Evolving Infrastructure Systems

    NARCIS (Netherlands)

    Davis, C.B.; Nikoli?, I.; Dijkema, G.P.J.

    2009-01-01

    A method is presented that allows for a life cycle assessment (LCA) to provide environmental information on an energy infrastructure system while it evolves. Energy conversion facilities are represented in an agent-based model (ABM) as distinct instances of technologies with owners capable of making

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Decision-Based Design Integrating Consumer Preferences into Engineering Design

    CERN Document Server

    Chen, Wei; Wassenaar, Henk Jan

    2013-01-01

    Building upon the fundamental principles of decision theory, Decision-Based Design: Integrating Consumer Preferences into Engineering Design presents an analytical approach to enterprise-driven Decision-Based Design (DBD) as a rigorous framework for decision making in engineering design.  Once the related fundamentals of decision theory, economic analysis, and econometrics modelling are established, the remaining chapters describe the entire process, the associated analytical techniques, and the design case studies for integrating consumer preference modeling into the enterprise-driven DBD framework. Methods for identifying key attributes, optimal design of human appraisal experiments, data collection, data analysis, and demand model estimation are presented and illustrated using engineering design case studies. The scope of the chapters also provides: •A rigorous framework of integrating the interests from both producer and consumers in engineering design, •Analytical techniques of consumer choice model...

  7. An Investigation Of The Influence Of Leadership And Processes On Basic Performance Results Using A Decision Model Based On Efqm

    Directory of Open Access Journals (Sweden)

    Ahmet Talat İnan

    2013-06-01

    Full Text Available EFQM Excellence Model is a quality approach that companies benefit in achieving success. EFQM Excellence Model is an assessment tool helping to determine what is competence and missing aspects in achieving excellence.In this study, based on the EFQM Excellence Model, the influence of basic performance results caused by leadership and processes variables in this model of a firm engaged in maintenance and repair services due to a large-scale company. In this work, a survey was conducted that covering the company's employees and managers. The data obtained from this survey was utilized by using SPSS16.0 statistics software in respect of factor analysis, reliability analysis, correlation and regression analysis. The relation between variables was evaluated taking into account the resuşts of analysis.

  8. A Comprehensive Decision-Making Approach Based on Hierarchical Attribute Model for Information Fusion Algorithms’ Performance Evaluation

    Directory of Open Access Journals (Sweden)

    Lianhui Li

    2014-01-01

    Full Text Available Aiming at the problem of fusion algorithm performance evaluation in multiradar information fusion system, firstly the hierarchical attribute model of track relevance performance evaluation model is established based on the structural model and functional model and quantization methods of evaluation indicators are given; secondly a combination weighting method is proposed to determine the weights of evaluation indicators, in which the objective and subjective weights are separately determined by criteria importance through intercriteria correlation (CRITIC and trapezoidal fuzzy scale analytic hierarchy process (AHP, and then experience factor is introduced to obtain the combination weight; at last the improved technique for order preference by similarity to ideal solution (TOPSIS replacing Euclidean distance with Kullback-Leibler divergence (KLD is used to sort the weighted indicator value of the evaluation object. An example is given to illustrate the correctness and feasibility of the proposed method.

  9. Community Based Flood Modeling in Southern and Baja California to Meet End User Needs for Decision-Making

    Science.gov (United States)

    Sanders, B. F.

    2017-12-01

    Flooding of coastal and fluvial systems are the most significant natural hazards facing society, and damages have been escalating for decades globally and in the U.S. Almost all metropolitan areas are exposed to flood risk. The threat from river flooding is especially high in India and China, and coastal cities around the world are threatened by storm surge and rising sea levels. Several trends including rising sea levels, urbanization, deforestation, and rural-to-urban population shifts will increase flood exposure in the future. Flood impacts are escalating despite advances in hazards science and extensive effort to manage risks. The fundamental issue is not that flooding is becoming more severe, even though it is in some places, but rather that societies are become more vulnerable to flood impacts. A critical factor contributing to the escalation of flood impacts is that the most vulnerable sectors of communities are left out of processes to prepare for and respond to flooding. Furthermore, the translation of knowledge about flood hazards and vulnerabilities into actionable information for communities has not been effective. In Southern and Baja California, an interdisciplinary team of researchers has partnered with stakeholders in flood vulnerable communities to co-develop flood hazard information systems designed to meet end-user needs for decision-making. The initiative leveraged the power of advanced, fine-scale hydraulic models of flooding to craft intuitive visualizations of context-sensitive scenarios. This presentation will cover the ways by which the process of flood inundation modeling served as a focal point for knowledge development, as well as the unique visualizations that populate on-line information systems accessible here: http://floodrise.uci.edu/online-flood-hazard-viewers/

  10. 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...

  11. Health decision making: lynchpin of evidence-based practice.

    Science.gov (United States)

    Spring, Bonnie

    2008-01-01

    Health decision making is both the lynchpin and the least developed aspect of evidence-based practice. The evidence-based practice process requires integrating the evidence with consideration of practical resources and patient preferences and doing so via a process that is genuinely collaborative. Yet, the literature is largely silent about how to accomplish integrative, shared decision making. for evidence-based practice are discussed for 2 theories of clinician decision making (expected utility and fuzzy trace) and 2 theories of patient health decision making (transtheoretical model and reasoned action). Three suggestions are offered. First, it would be advantageous to have theory-based algorithms that weight and integrate the 3 data strands (evidence, resources, preferences) in different decisional contexts. Second, patients, not providers, make the decisions of greatest impact on public health, and those decisions are behavioral. Consequently, theory explicating how provider-patient collaboration can influence patient lifestyle decisions made miles from the provider's office is greatly needed. Third, although the preponderance of data on complex decisions supports a computational approach, such an approach to evidence-based practice is too impractical to be widely applied at present. More troublesomely, until patients come to trust decisions made computationally more than they trust their providers' intuitions, patient adherence will remain problematic. A good theory of integrative, collaborative health decision making remains needed.

  12. AN EXTENDED REINFORCEMENT LEARNING MODEL OF BASAL GANGLIA TO UNDERSTAND THE CONTRIBUTIONS OF SEROTONIN AND DOPAMINE IN RISK-BASED DECISION MAKING, REWARD PREDICTION, AND PUNISHMENT LEARNING

    Directory of Open Access Journals (Sweden)

    Pragathi Priyadharsini Balasubramani

    2014-04-01

    Full Text Available Although empirical and neural studies show that serotonin (5HT plays many functional roles in the brain, prior computational models mostly focus on its role in behavioral inhibition. In this study, we present a model of risk based decision making in a modified Reinforcement Learning (RL-framework. The model depicts the roles of dopamine (DA and serotonin (5HT in Basal Ganglia (BG. In this model, the DA signal is represented by the temporal difference error (δ, while the 5HT signal is represented by a parameter (α that controls risk prediction error. This formulation that accommodates both 5HT and DA reconciles some of the diverse roles of 5HT particularly in connection with the BG system. We apply the model to different experimental paradigms used to study the role of 5HT: 1 Risk-sensitive decision making, where 5HT controls risk assessment, 2 Temporal reward prediction, where 5HT controls time-scale of reward prediction, and 3 Reward/Punishment sensitivity, in which the punishment prediction error depends on 5HT levels. Thus the proposed integrated RL model reconciles several existing theories of 5HT and DA in the BG.

  13. An environmental fairness based optimisation model for the decision-support of joint control over the water quantity and quality of a river basin

    Science.gov (United States)

    Yu, Sen; He, Li; Lu, Hongwei

    2016-04-01

    This paper presented a new environmental fairness based optimisation model (EFOM) for the decision-support of water resources management and water pollution control at the watershed scale. The model integrated three prediction modules for water consumption and pollutant discharge (WCPD), environmental Gini coefficient (EGC) and water quality (WASP). The model is capable of optimizing the total discharge quantity in the whole basin and controlling units both spatially and temporally, and addressing the conflicts between environmental fairness and efficiency. The model was applied to the Songhua River basin, attempting to support decision-making of joint control over the water quantity and quality. Validation of the WASP module showed that the simulation agreed well with water quality monitoring values (2013) in the Harbin section. Results from the EFOM model also indicated that the water environment in the Harbin section would be improved significantly by effectively controlling the total pollution discharge. The identified optimal strategy obtained from the EFOM showed that the percentage of water in good quality reaches 72% in 2020, suggesting that the strategy would guarantee the planning goals of The China Action Plan for Water Pollution Control to be satisfied. Hence, the modelling under the consideration of environmental fairness can be a new attempt, which is beneficial to optimal joint control of water quantity and water quality at the watershed scale.

  14. 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...

  15. Bridging the gap between decision-making and emerging big data sources : an application of a model-based framework to disaster management in Brazil

    OpenAIRE

    Horita, Flávio E.A.; Albuquerque, João Porto de; Marchezini, Victor; Mendiondo, Eduardo M.

    2017-01-01

    With the emergence of big data and new data sources, a challenge posed to today's organizations consists of identifying how to align their decision-making and organizational processes to data that could help them make better-informed decisions. This paper presents a study in the context of disaster management in Brazil that applies oDMN +, a framework that connects decision-making with data sources through an extended modeling notation and a modeling process. The study results revealed that t...

  16. Reserch on Urban Spatial Expansion Model Based on Multi-Object Gray Decision-Making and Ca: a Case Study of Pidu District, Chengdu City

    Science.gov (United States)

    Liu, Z.; Li, Y.

    2018-04-01

    This paper from the perspective of the Neighbor cellular space, Proposed a new urban space expansion model based on a new multi-objective gray decision and CA. The model solved the traditional cellular automata conversion rules is difficult to meet the needs of the inner space-time analysis of urban changes and to overcome the problem of uncertainty in the combination of urban drivers and urban cellular automata. At the same time, the study takes Pidu District as a research area and carries out urban spatial simulation prediction and analysis, and draws the following conclusions: (1) The design idea of the urban spatial expansion model proposed in this paper is that the urban driving factor and the neighborhood function are tightly coupled by the multi-objective grey decision method based on geographical conditions. The simulation results show that the simulation error of urban spatial expansion is less than 5.27 %. The Kappa coefficient is 0.84. It shows that the model can better capture the inner transformation mechanism of the city. (2) We made a simulation prediction for Pidu District of Chengdu by discussing Pidu District of Chengdu as a system instance.In this way, we analyzed the urban growth tendency of this area.presenting a contiguous increasing mode, which is called "urban intensive development". This expansion mode accorded with sustainable development theory and the ecological urbanization design theory.

  17. Exploring the Integration of COSYSMO with a Model-Based Systems Engineering Methodology in Early Trade Space Analytics and Decisions

    Science.gov (United States)

    2016-06-01

    Air Force base AFIT Air Force Institute of Technology AoA analysis of alternatives AV All Viewpoint-DODAF bdd block definition diagram BPMN Business...Business ProcessModel Notation ( BPMN ) to name a few. Each of these languages has specific lifecycles and limitations to consider. The use of a customized...systems analysis. When utilizing other available languages such, as SysML, LML, and BPMN , increased interoperability in communication and performance

  18. 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

  19. 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)

  20. 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.

  1. 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 ...

  2. Parallel constraint satisfaction in memory-based decisions.

    Science.gov (United States)

    Glöckner, Andreas; Hodges, Sara D

    2011-01-01

    Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glöckner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases and confidence decreases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time-pressure conditions and even with decision times as short as 1.7 s. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time-pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.

  3. 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.

  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. Staged decision making based on probabilistic forecasting

    Science.gov (United States)

    Booister, Nikéh; Verkade, Jan; Werner, Micha; Cranston, Michael; Cumiskey, Lydia; Zevenbergen, Chris

    2016-04-01

    Flood forecasting systems reduce, but cannot eliminate uncertainty about the future. Probabilistic forecasts explicitly show that uncertainty remains. However, as - compared to deterministic forecasts - a dimension is added ('probability' or 'likelihood'), with this added dimension decision making is made slightly more complicated. A technique of decision support is the cost-loss approach, which defines whether or not to issue a warning or implement mitigation measures (risk-based method). With the cost-loss method a warning will be issued when the ratio of the response costs to the damage reduction is less than or equal to the probability of the possible flood event. This cost-loss method is not widely used, because it motivates based on only economic values and is a technique that is relatively static (no reasoning, yes/no decision). Nevertheless it has high potential to improve risk-based decision making based on probabilistic flood forecasting because there are no other methods known that deal with probabilities in decision making. The main aim of this research was to explore the ways of making decision making based on probabilities with the cost-loss method better applicable in practice. The exploration began by identifying other situations in which decisions were taken based on uncertain forecasts or predictions. These cases spanned a range of degrees of uncertainty: from known uncertainty to deep uncertainty. Based on the types of uncertainties, concepts of dealing with situations and responses were analysed and possible applicable concepts where chosen. Out of this analysis the concepts of flexibility and robustness appeared to be fitting to the existing method. Instead of taking big decisions with bigger consequences at once, the idea is that actions and decisions are cut-up into smaller pieces and finally the decision to implement is made based on economic costs of decisions and measures and the reduced effect of flooding. The more lead-time there is in

  6. Predicting Motivation: Computational Models of PFC Can Explain Neural Coding of Motivation and Effort-based Decision-making in Health and Disease.

    Science.gov (United States)

    Vassena, Eliana; Deraeve, James; Alexander, William H

    2017-10-01

    Human behavior is strongly driven by the pursuit of rewards. In daily life, however, benefits mostly come at a cost, often requiring that effort be exerted to obtain potential benefits. Medial PFC (MPFC) and dorsolateral PFC (DLPFC) are frequently implicated in the expectation of effortful control, showing increased activity as a function of predicted task difficulty. Such activity partially overlaps with expectation of reward and has been observed both during decision-making and during task preparation. Recently, novel computational frameworks have been developed to explain activity in these regions during cognitive control, based on the principle of prediction and prediction error (predicted response-outcome [PRO] model [Alexander, W. H., & Brown, J. W. Medial prefrontal cortex as an action-outcome predictor. Nature Neuroscience, 14, 1338-1344, 2011], hierarchical error representation [HER] model [Alexander, W. H., & Brown, J. W. Hierarchical error representation: A computational model of anterior cingulate and dorsolateral prefrontal cortex. Neural Computation, 27, 2354-2410, 2015]). Despite the broad explanatory power of these models, it is not clear whether they can also accommodate effects related to the expectation of effort observed in MPFC and DLPFC. Here, we propose a translation of these computational frameworks to the domain of effort-based behavior. First, we discuss how the PRO model, based on prediction error, can explain effort-related activity in MPFC, by reframing effort-based behavior in a predictive context. We propose that MPFC activity reflects monitoring of motivationally relevant variables (such as effort and reward), by coding expectations and discrepancies from such expectations. Moreover, we derive behavioral and neural model-based predictions for healthy controls and clinical populations with impairments of motivation. Second, we illustrate the possible translation to effort-based behavior of the HER model, an extended version of PRO

  7. 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…

  8. 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 ...

  9. 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

  10. The organization of societal conflicts by pavement ants Tetramorium caespitum: an agent-based model of amine-mediated decision making.

    Science.gov (United States)

    Hoover, Kevin M; Bubak, Andrew N; Law, Isaac J; Yaeger, Jazmine D W; Renner, Kenneth J; Swallow, John G; Greene, Michael J

    2016-06-01

    Ant colonies self-organize to solve complex problems despite the simplicity of an individual ant's brain. Pavement ant Tetramorium caespitum colonies must solve the problem of defending the territory that they patrol in search of energetically rich forage. When members of 2 colonies randomly interact at the territory boundary a decision to fight occurs when: 1) there is a mismatch in nestmate recognition cues and 2) each ant has a recent history of high interaction rates with nestmate ants. Instead of fighting, some ants will decide to recruit more workers from the nest to the fighting location, and in this way a positive feedback mediates the development of colony wide wars. In ants, the monoamines serotonin (5-HT) and octopamine (OA) modulate many behaviors associated with colony organization and in particular behaviors associated with nestmate recognition and aggression. In this article, we develop and explore an agent-based model that conceptualizes how individual changes in brain concentrations of 5-HT and OA, paired with a simple threshold-based decision rule, can lead to the development of colony wide warfare. Model simulations do lead to the development of warfare with 91% of ants fighting at the end of 1 h. When conducting a sensitivity analysis, we determined that uncertainty in monoamine concentration signal decay influences the behavior of the model more than uncertainty in the decision-making rule or density. We conclude that pavement ant behavior is consistent with the detection of interaction rate through a single timed interval rather than integration of multiple interactions.

  11. 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.

  12. Using Collaborative Simulation Modeling to Develop a Web-Based Tool to Support Policy-Level Decision Making About Breast Cancer Screening Initiation Age

    Directory of Open Access Journals (Sweden)

    Elizabeth S. Burnside MD, MPH, MS

    2017-07-01

    Full Text Available Background: There are no publicly available tools designed specifically to assist policy makers to make informed decisions about the optimal ages of breast cancer screening initiation for different populations of US women. Objective: To use three established simulation models to develop a web-based tool called Mammo OUTPuT. Methods: The simulation models use the 1970 US birth cohort and common parameters for incidence, digital screening performance, and treatment effects. Outcomes include breast cancers diagnosed, breast cancer deaths averted, breast cancer mortality reduction, false-positive mammograms, benign biopsies, and overdiagnosis. The Mammo OUTPuT tool displays these outcomes for combinations of age at screening initiation (every year from 40 to 49, annual versus biennial interval, lifetime versus 10-year horizon, and breast density, compared to waiting to start biennial screening at age 50 and continuing to 74. The tool was piloted by decision makers (n = 16 who completed surveys. Results: The tool demonstrates that benefits in the 40s increase linearly with earlier initiation age, without a specific threshold age. Likewise, the harms of screening increase monotonically with earlier ages of initiation in the 40s. The tool also shows users how the balance of benefits and harms varies with breast density. Surveys revealed that 100% of users (16/16 liked the appearance of the site; 94% (15/16 found the tool helpful; and 94% (15/16 would recommend the tool to a colleague. Conclusions: This tool synthesizes a representative subset of the most current CISNET (Cancer Intervention and Surveillance Modeling Network simulation model outcomes to provide policy makers with quantitative data on the benefits and harms of screening women in the 40s. Ultimate decisions will depend on program goals, the population served, and informed judgments about the weight of benefits and harms.

  13. How could Decision Support System Based on Non-Linear Model Help to Interpret Tumor Marker Measurments in Oncology

    Czech Academy of Sciences Publication Activity Database

    Pecen, Ladislav; Eben, Kryštof; Vondráček, Jiří; Holubec, L.; Topolčan, O.; Pikner, R.; Kausitz, J.; Nekulová, M.; Šimíčková, M.

    2002-01-01

    Roč. 23, Suppl.1 (2002), s. 38 ISSN 1010-4283. [Meeting of the International Society for Oncodevelopmental Biology and Medicine /30./. 08.09.2002-12.09.2002, Boston] Institutional research plan: AV0Z1030915 Keywords : tumor markers * decision support systems Subject RIV: BA - General Mathematics

  14. A simulation-based support tool for data-driven decision making : operational testing for dependence modelling

    NARCIS (Netherlands)

    Biller, B.; Akçay, A.E.; Tayur, S.; Corlu, C.

    2014-01-01

    Dependencies occur naturally between input processes of many manufacturing and service applications. When the dependence parameters are known with certainty, the failure to factor the dependencies into decisions is well known to waste significant resources in system management. Our focus is on the

  15. Optimisation models for decision support in the development of biomass-based industrial district-heating networks in Italy

    International Nuclear Information System (INIS)

    Chinese, Damiana; Meneghetti, Antonella

    2005-01-01

    A system optimisation approach is proposed to design biomass-based district-heating networks in the context of industrial districts, which are one of the main successful productive aspects of Italian industry. Two different perspectives are taken into account, that of utilities and of policy makers, leading to two optimisation models to be further integrated. A mixed integer linear-programming model is developed for a utility company's profit maximisation, while a linear-programming model aims at minimising the balance of greenhouse-gas emissions related to the proposed energy system and the avoided emissions due to the substitution of current fossil-fuel boilers with district-heating connections. To systematically compare their results, a sensitivity analysis is performed with respect to network size in order to identify how the optimal system configuration, in terms of selected boilers to be connected to a multiple energy-source network, may vary in the two cases and to detect possible optimal sizes. Then a factorial analysis is adopted to rank desirable client types under the two perspectives and identify proper marketing strategies. The proposed optimisation approach was applied to the design of a new district-heating network in the chair-manufacturing district of North-Eastern Italy. (Author)

  16. 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

  17. 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

  18. Reasoning in explanation-based decision making.

    Science.gov (United States)

    Pennington, N; Hastie, R

    1993-01-01

    A general theory of explanation-based decision making is outlined and the multiple roles of inference processes in the theory are indicated. A typology of formal and informal inference forms, originally proposed by Collins (1978a, 1978b), is introduced as an appropriate framework to represent inferences that occur in the overarching explanation-based process. Results from the analysis of verbal reports of decision processes are presented to demonstrate the centrality and systematic character of reasoning in a representative legal decision-making task.

  19. Linking Theoretical Decision-making Mechanisms in the Simon Task with Electrophysiological Data: A Model-based Neuroscience Study in Humans.

    Science.gov (United States)

    Servant, Mathieu; White, Corey; Montagnini, Anna; Burle, Borís

    2016-10-01

    A current challenge for decision-making research is in extending models of simple decisions to more complex and ecological choice situations. Conflict tasks (e.g., Simon, Stroop, Eriksen flanker) have been the focus of much interest, because they provide a decision-making context representative of everyday life experiences. Modeling efforts have led to an elaborated drift diffusion model for conflict tasks (DMC), which implements a superimposition of automatic and controlled decision activations. The DMC has proven to capture the diversity of behavioral conflict effects across various task contexts. This study combined DMC predictions with EEG and EMG measurements to test a set of linking propositions that specify the relationship between theoretical decision-making mechanisms involved in the Simon task and brain activity. Our results are consistent with a representation of the superimposed decision variable in the primary motor cortices. The decision variable was also observed in the EMG activity of response agonist muscles. These findings provide new insight into the neurophysiology of human decision-making. In return, they provide support for the DMC model framework.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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

  5. 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

  6. Multi-criteria decision making development of ion chromatographic method for determination of inorganic anions in oilfield waters based on artificial neural networks retention model.

    Science.gov (United States)

    Stefanović, Stefica Cerjan; Bolanča, Tomislav; Luša, Melita; Ukić, Sime; Rogošić, Marko

    2012-02-24

    This paper describes the development of ad hoc methodology for determination of inorganic anions in oilfield water, since their composition often significantly differs from the average (concentration of components and/or matrix). Therefore, fast and reliable method development has to be performed in order to ensure the monitoring of desired properties under new conditions. The method development was based on computer assisted multi-criteria decision making strategy. The used criteria were: maximal value of objective functions used, maximal robustness of the separation method, minimal analysis time, and maximal retention distance between two nearest components. Artificial neural networks were used for modeling of anion retention. The reliability of developed method was extensively tested by the validation of performance characteristics. Based on validation results, the developed method shows satisfactory performance characteristics, proving the successful application of computer assisted methodology in the described case study. Copyright © 2011 Elsevier B.V. All rights reserved.

  7. Irrigated Agriculture in Morocco: An Agent-Based Model of Adaptation and Decision Making Amid Increasingly Frequent Drought Events

    Science.gov (United States)

    Norton, M.

    2015-12-01

    In the past 100 years, Morocco has undertaken a heavy investment in developing water infrastructure that has led to a dramatic expansion of irrigated agriculture. Irrigated agriculture is the primary user of water in many arid countries, often accounting for 80-90% of total water usage. Irrigation is adopted by farmers not only because it leads to increased production, but also because it improves resilience to an uncertain climate. However, the Mediterranean region as a whole has also seen an increase in the frequency and severity of drought events. These droughts have had a dramatic impact on farmer livelihoods and have led to a number of coping strategies, including the adoption or disadoption of irrigation. In this study, we use a record of the annual extent of irrigated agriculture in Morocco to model the effect of drought on the extent of irrigated agriculture. Using an agent-based socioeconomic model, we seek to answer the following questions: 1) Do farmers expand irrigated agriculture in response to droughts? 2) Do drought events entail the removal of perennial crops like orchards? 3) Can we detect the retreat of irrigated agriculture in the more fragile watersheds of Morocco? Understanding the determinants of irrigated crop expansion and contractions will help us understand how agro-ecological systems transition from 20th century paradigms of expansion of water supply to a 21st century paradigm of water use efficiency. The answers will become important as countries learn how to manage water in new climate regimes characterized by less reliable and available precipitation.

  8. 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...

  9. 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…

  10. 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

  11. 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

  12. The Invasive Species Forecasting System (ISFS): An iRODS-Based, Cloud-Enabled Decision Support System for Invasive Species Habitat Suitability Modeling

    Science.gov (United States)

    Gill, Roger; Schnase, John L.

    2012-01-01

    The Invasive Species Forecasting System (ISFS) is an online decision support system that allows users to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of interest, such as a national park, monument, forest, or refuge. Target customers for ISFS are natural resource managers and decision makers who have a need for scientifically valid, model- based predictions of the habitat suitability of plant species of management concern. In a joint project involving NASA and the Maryland Department of Natural Resources, ISFS has been used to model the potential distribution of Wavyleaf Basketgrass in Maryland's Chesapeake Bay Watershed. Maximum entropy techniques are used to generate predictive maps using predictor datasets derived from remotely sensed data and climate simulation outputs. The workflow to run a model is implemented in an iRODS microservice using a custom ISFS file driver that clips and re-projects data to geographic regions of interest, then shells out to perform MaxEnt processing on the input data. When the model completes, all output files and maps from the model run are registered in iRODS and made accessible to the user. The ISFS user interface is a web browser that uses the iRODS PHP client to interact with the ISFS/iRODS- server. ISFS is designed to reside in a VMware virtual machine running SLES 11 and iRODS 3.0. The ISFS virtual machine is hosted in a VMware vSphere private cloud infrastructure to deliver the online service.

  13. 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...

  14. Towards a social psychology-based microscopic model of driver behavior and decision-making : modifying Lewin's field theory

    Science.gov (United States)

    2014-01-01

    Central to effective roadway design is the ability to understand how drivers behave as they traverse a segment of : roadway. While simple and complex microscopic models have been used over the years to analyse driver behaviour, : most models: 1.) inc...

  15. 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.

  16. 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.

  17. 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

  18. Justification of the concept of mathematical methods and models in making decisions on taxation

    OpenAIRE

    KORKUNA NATALIA MIKHAYLOVNA

    2017-01-01

    The paper presents the concept of the application of mathematical methods and models in making decisions on taxation in Ukraine as a phased process. Its performance result is the selection of an effective decision based on regression and optimization models.

  19. Multiple attribute decision making model and application to food safety risk evaluation.

    Science.gov (United States)

    Ma, Lihua; Chen, Hong; Yan, Huizhe; Yang, Lifeng; Wu, Lifeng

    2017-01-01

    Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

  20. Customer classification in banking system of Iran based on the credit risk model using multi-criteria decision-making models

    Directory of Open Access Journals (Sweden)

    Khalil Khalili

    2015-11-01

    Full Text Available One of the most important factors of survival of financial institutes and banks in the current competitive markets is to create balance and equality among resources and consumptions as well as to keep the health of money circulation in these institutes. According to the experiences obtained from recent financial crises in the world. The lack of appropriate management of the demands of banks and financial institutions can be considered as one of the main factors of occurrence of this crisis. The objective of the present study is to identify and classify customers according to credit risk and decisions of predictive models. The present research is a survey research employing field study in terms of the data collection method. The method of collecting theoretical framework was library research and the data were collected by two ways of data of a questionnaire and real customers’ financial data. To analyze the data of the questionnaire, analytical hierarchy process and to analyze real customers’ financial data, the TOPSIS method were employed. The population of the study included files of real customers in one of the branches of RefahKargaran Bank in city of Tabriz, Iran. From among 800 files, 140 files were completed and using Morgan’s table, 103 files were investigated. The final model was presented and with 95% of probability, if the next customer’s data is entered the model, it will capable of identifying accurately the degree of customer risk.

  1. Development of an interactive exploratory web-based modelling platform for informed decision-making and knowledgeable responses to global change

    Science.gov (United States)

    Holman, I.; Harrison, P.; Cojocaru, G.

    2013-12-01

    Informed decision-making and knowledgeable responses to global climate change impacts on natural resources and ecosystem services requires access to information resources that are credible, accurate, easy to understand, and appropriate. Too often stakeholders are limited to restricted scientific outputs produced by inaccessible models, generated from a limited number of scenario simulations chosen arbitrarily by researchers. This paper describes the outcomes of the CLIMSAVE project (www.climsave.eu), which has attempted to democratise climate change impacts, adaptation and vulnerability modelling, through developing the public domain interactive exploratory web-based CLIMSAVE Integrated Assessment (IA) Platform. The CLIMSAVE Integrated Assessment (IA) Platform aims to enable a wide range of stakeholders to improve their understanding surrounding impacts, adaptation responses and vulnerability of natural resources and ecosystem services under uncertain futures across Europe. The CLIMSAVE IA Platform contain linked simulation models (of the urban, water, agriculture, forestry, biodiversity and other sectors), IPCC AR4 climate scenarios and CLIMSAVE socio-economic scenarios, enabling users to select their inputs (climate and socioeconomic), rapidly run the models across Europe using their input settings and view their selected Impact (before, or after, adaptation) and Vulnerability (Figure 1) indicators. The CLIMSAVE IA Platform has been designed to promote both cognitive accessibility - the ease of understanding - and practical accessibility - the ease of application. Based upon partner and CLIMSAVE international experts' experience, examination of other participatory model interfaces and potential user requirements, we describe the design concepts and functionality that were identified, incorporated into the prototype CLIMSAVE IA Platform and further refined based on stakeholder feedback. The CLIMSAVE IA Platform is designed to facilitate a two-way iterative process

  2. 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.

  3. An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

    OpenAIRE

    Bo Sun; Qiang Feng; Songjie Li

    2012-01-01

    According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules) based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negoti...

  4. Information acquisition during online decision-making : A model-based exploration using eye-tracking data

    NARCIS (Netherlands)

    Shi, W.; Wedel, M.; Pieters, R.

    2013-01-01

    We propose a model of eye-tracking data to understand information acquisition patterns on attribute-by-product matrices, which are common in online choice environments such as comparison websites. The objective is to investigate how consumers gather product and attribute information from moment to

  5. Application of stakeholder-based and modelling approaches for supporting robust adaptation decision making under future climatic uncertainty and changing urban-agricultural water demand

    Science.gov (United States)

    Bhave, Ajay; Dessai, Suraje; Conway, Declan; Stainforth, David

    2016-04-01

    Deep uncertainty in future climate change and socio-economic conditions necessitates the use of assess-risk-of-policy approaches over predict-then-act approaches for adaptation decision making. Robust Decision Making (RDM) approaches embody this principle and help evaluate the ability of adaptation options to satisfy stakeholder preferences under wide-ranging future conditions. This study involves the simultaneous application of two RDM approaches; qualitative and quantitative, in the Cauvery River Basin in Karnataka (population ~23 million), India. The study aims to (a) determine robust water resources adaptation options for the 2030s and 2050s and (b) compare the usefulness of a qualitative stakeholder-driven approach with a quantitative modelling approach. For developing a large set of future scenarios a combination of climate narratives and socio-economic narratives was used. Using structured expert elicitation with a group of climate experts in the Indian Summer Monsoon, climatic narratives were developed. Socio-economic narratives were developed to reflect potential future urban and agricultural water demand. In the qualitative RDM approach, a stakeholder workshop helped elicit key vulnerabilities, water resources adaptation options and performance criteria for evaluating options. During a second workshop, stakeholders discussed and evaluated adaptation options against the performance criteria for a large number of scenarios of climatic and socio-economic change in the basin. In the quantitative RDM approach, a Water Evaluation And Planning (WEAP) model was forced by precipitation and evapotranspiration data, coherent with the climatic narratives, together with water demand data based on socio-economic narratives. We find that compared to business-as-usual conditions options addressing urban water demand satisfy performance criteria across scenarios and provide co-benefits like energy savings and reduction in groundwater depletion, while options reducing

  6. 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

  7. Spatial soil zinc content distribution from terrain parameters: A GIS-based decision-tree model in Lebanon

    International Nuclear Information System (INIS)

    Bou Kheir, Rania; Greve, Mogens H.; Abdallah, Chadi; Dalgaard, Tommy

    2010-01-01

    Heavy metal contamination has been and continues to be a worldwide phenomenon that has attracted a great deal of attention from governments and regulatory bodies. In this context, our study proposes a regression-tree model to predict the concentration level of zinc in the soils of northern Lebanon (as a case study of Mediterranean landscapes) under a GIS environment. The developed tree-model explained 88% of variance in zinc concentration using pH (100% in relative importance), surroundings of waste areas (90%), proximity to roads (80%), nearness to cities (50%), distance to drainage line (25%), lithology (24%), land cover/use (14%), slope gradient (10%), conductivity (7%), soil type (7%), organic matter (5%), and soil depth (5%). The overall accuracy of the quantitative zinc map produced (at 1:50.000 scale) was estimated to be 78%. The proposed tree model is relatively simple and may also be applied to other areas. - GIS regression-tree analysis explained 88% of the variability in field/laboratory Zinc concentrations.

  8. Spatial soil zinc content distribution from terrain parameters: A GIS-based decision-tree model in Lebanon

    Energy Technology Data Exchange (ETDEWEB)

    Bou Kheir, Rania, E-mail: rania.boukheir@agrsci.d [Lebanese University, Faculty of Letters and Human Sciences, Department of Geography, GIS Research Laboratory, P.O. Box 90-1065, Fanar (Lebanon); Department of Agroecology and Environment, Faculty of Agricultural Sciences (DJF), Aarhus University, Blichers Alle 20, P.O. Box 50, DK-8830 Tjele (Denmark); Greve, Mogens H. [Department of Agroecology and Environment, Faculty of Agricultural Sciences (DJF), Aarhus University, Blichers Alle 20, P.O. Box 50, DK-8830 Tjele (Denmark); Abdallah, Chadi [National Council for Scientific Research, Remote Sensing Center, P.O. Box 11-8281, Beirut (Lebanon); Dalgaard, Tommy [Department of Agroecology and Environment, Faculty of Agricultural Sciences (DJF), Aarhus University, Blichers Alle 20, P.O. Box 50, DK-8830 Tjele (Denmark)

    2010-02-15

    Heavy metal contamination has been and continues to be a worldwide phenomenon that has attracted a great deal of attention from governments and regulatory bodies. In this context, our study proposes a regression-tree model to predict the concentration level of zinc in the soils of northern Lebanon (as a case study of Mediterranean landscapes) under a GIS environment. The developed tree-model explained 88% of variance in zinc concentration using pH (100% in relative importance), surroundings of waste areas (90%), proximity to roads (80%), nearness to cities (50%), distance to drainage line (25%), lithology (24%), land cover/use (14%), slope gradient (10%), conductivity (7%), soil type (7%), organic matter (5%), and soil depth (5%). The overall accuracy of the quantitative zinc map produced (at 1:50.000 scale) was estimated to be 78%. The proposed tree model is relatively simple and may also be applied to other areas. - GIS regression-tree analysis explained 88% of the variability in field/laboratory Zinc concentrations.

  9. 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.  

  10. A Probabilistic Model for Propagating Ungauged Basin Runoff Prediction Variability and Uncertainty Into Estuarine Water Quality Dynamics and Water Quality-Based Management Decisions

    Science.gov (United States)

    Anderson, R.; Gronewold, A.; Alameddine, I.; Reckhow, K.

    2008-12-01

    probabilistic modeling software program Analytica. This approach not only reflects uncertainty in parameter estimates but, by modeling the predicted daily runoff rate as a random variable, propagates that variability into the tidal prism model as well. The tidal prism model has the advantage of having only one hydrodynamic calibration parameter, the tidal exchange ratio (the ratio between the volume of water returning to an estuary on an incoming tide and the volume of water which exited the estuary on the previous outgoing tide). We estimate the tidal exchange ratio by calibrating the tidal prism model to salinity data using a Bayesian Markov chain Monte Carlo (MCMC) procedure and, as with other parameters, encode it as a random variable in the comprehensive model. We compare our results to those of a purely deterministic model, and find that intrinsic sources of variability in ungauged basin runoff predictions, when ignored, lead to pollutant concentration forecasts with unnecessarily large prediction intervals, and to potentially over-conservative management decisions. By demonstrating an innovative approach to capturing and explicitly acknowledging uncertainty in runoff model parameter estimates, our modeling approach serves as an ideal building block for future comprehensive model-based pollutant mitigation planning efforts in ungauged coastal watersheds, including those implemented through the US Environmental Protection Agency total maximum daily load program.

  11. 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.

  12. 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...

  13. 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

  14. 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

  15. Simulation of operating rules and discretional decisions using a fuzzy rule-based system integrated into a water resources management model

    Science.gov (United States)

    Macian-Sorribes, Hector; Pulido-Velazquez, Manuel

    2013-04-01

    Water resources systems are operated, mostly, using a set of pre-defined rules not regarding, usually, to an optimal allocation in terms of water use or economic benefits, but to historical and institutional reasons. These operating policies are reproduced, commonly, as hedging rules, pack rules or zone-based operations, and simulation models can be used to test their performance under a wide range of hydrological and/or socio-economic hypothesis. Despite the high degree of acceptation and testing that these models have achieved, the actual operation of water resources systems hardly follows all the time the pre-defined rules with the consequent uncertainty on the system performance. Real-world reservoir operation is very complex, affected by input uncertainty (imprecision in forecast inflow, seepage and evaporation losses, etc.), filtered by the reservoir operator's experience and natural risk-aversion, while considering the different physical and legal/institutional constraints in order to meet the different demands and system requirements. The aim of this work is to expose a fuzzy logic approach to derive and assess the historical operation of a system. This framework uses a fuzzy rule-based system to reproduce pre-defined rules and also to match as close as possible the actual decisions made by managers. After built up, the fuzzy rule-based system can be integrated in a water resources management model, making possible to assess the system performance at the basin scale. The case study of the Mijares basin (eastern Spain) is used to illustrate the method. A reservoir operating curve regulates the two main reservoir releases (operated in a conjunctive way) with the purpose of guaranteeing a high realiability of supply to the traditional irrigation districts with higher priority (more senior demands that funded the reservoir construction). A fuzzy rule-based system has been created to reproduce the operating curve's performance, defining the system state (total

  16. 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.

  17. Evaluation of the validity of treatment decisions based on surrogate country models before introduction of the Polish FRAX and recommendations in comparison to current practice.

    Science.gov (United States)

    Glinkowski, Wojciech M; Narloch, Jerzy; Glinkowska, Bożena; Bandura, Małgorzata

    2018-03-01

    Patients diagnosed before the Polish FRAX was introduced may require re-evaluation and treatment changes if the diagnosis was established according to a surrogate country FRAX score. The aim of the study was to evaluate the validity of treatment decisions based on the surrogate country model before introduction of the Polish FRAX and to provide recommendations based on the current practice. We evaluated a group of 142 postmenopausal women (70.7 ±8.9 years) who underwent bone mineral density measurements. We used 22 country-specific FRAX models and compared these to the Polish model. The mean risk values for hip and major osteoporotic fractures within 10 years were 4.575 (from 0.82 to 8.46) and 12.47% (from 2.18 to 21.65), respectively. In the case of a major fracture, 94.4% of women would receive lifestyle advice, and 5.6% would receive treatment according to the Polish FRAX using the guidelines of the National Osteoporosis Foundation (NOF). Polish treatment thresholds would implement pharmacotherapy in 32.4% of the study group. In the case of hip fractures, 45% of women according to the NOF would require pharmacotherapy but only 9.8% of women would qualify according to Polish guidelines. Nearly all surrogate FRAX calculator scores proved significantly different form Polish ( p > 0.05). More patients might have received antiresorptive medication before the Polish FRAX. This study recommends re-evaluation of patients who received medical therapy before the Polish FRAX was introduced and a review of the recommendations, considering the side effects of antiresorptive medication.

  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. A methodology for eliciting, representing, and analysing stakeholder knowledge for decision making on complex socio-ecological systems: From cognitive maps to agent-based models

    NARCIS (Netherlands)

    El-Sawah, Sondoss; Guillaume, Joseph H.A.; Filatova, Tatiana; Rook, Josefine; Jakeman, Anthony J.

    2015-01-01

    This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation

  20. Influence of branding on preference-based decision making.

    Science.gov (United States)

    Philiastides, Marios G; Ratcliff, Roger

    2013-07-01

    Branding has become one of the most important determinants of consumer choices. Intriguingly, the psychological mechanisms of how branding influences decision making remain elusive. In the research reported here, we used a preference-based decision-making task and computational modeling to identify which internal components of processing are affected by branding. We found that a process of noisy temporal integration of subjective value information can model preference-based choices reliably and that branding biases are explained by changes in the rate of the integration process itself. This result suggests that branding information and subjective preference are integrated into a single source of evidence in the decision-making process, thereby altering choice behavior.

  1. Comparison of Timed Automata with Discrete Event Simulation for Modeling of Biomarker-Based Treatment Decisions: An Illustration for Metastatic Castration-Resistant Prostate Cancer.

    Science.gov (United States)

    Degeling, Koen; Schivo, Stefano; Mehra, Niven; Koffijberg, Hendrik; Langerak, Rom; de Bono, Johann S; IJzerman, Maarten J

    2017-12-01

    With the advent of personalized medicine, the field of health economic modeling is being challenged and the use of patient-level dynamic modeling techniques might be required. To illustrate the usability of two such techniques, timed automata (TA) and discrete event simulation (DES), for modeling personalized treatment decisions. An early health technology assessment on the use of circulating tumor cells, compared with prostate-specific antigen and bone scintigraphy, to inform treatment decisions in metastatic castration-resistant prostate cancer was performed. Both modeling techniques were assessed quantitatively, in terms of intermediate outcomes (e.g., overtreatment) and health economic outcomes (e.g., net monetary benefit). Qualitatively, among others, model structure, agent interactions, data management (i.e., importing and exporting data), and model transparency were assessed. Both models yielded realistic and similar intermediate and health economic outcomes. Overtreatment was reduced by 6.99 and 7.02 weeks by applying circulating tumor cell as a response marker at a net monetary benefit of -€1033 and -€1104 for the TA model and the DES model, respectively. Software-specific differences were observed regarding data management features and the support for statistical distributions, which were considered better for the DES software. Regarding method-specific differences, interactions were modeled more straightforward using TA, benefiting from its compositional model structure. Both techniques prove suitable for modeling personalized treatment decisions, although DES would be preferred given the current software-specific limitations of TA. When these limitations are resolved, TA would be an interesting modeling alternative if interactions are key or its compositional structure is useful to manage multi-agent complex problems. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights

  2. Automated Vectorization of Decision-Based Algorithms

    Science.gov (United States)

    James, Mark

    2006-01-01

    Virtually all existing vectorization algorithms are designed to only analyze the numeric properties of an algorithm and distribute those elements across multiple processors. This advances the state of the practice because it is the only known system, at the time of this reporting, that takes high-level statements and analyzes them for their decision properties and converts them to a form that allows them to automatically be executed in parallel. The software takes a high-level source program that describes a complex decision- based condition and rewrites it as a disjunctive set of component Boolean relations that can then be executed in parallel. This is important because parallel architectures are becoming more commonplace in conventional systems and they have always been present in NASA flight systems. This technology allows one to take existing condition-based code and automatically vectorize it so it naturally decomposes across parallel architectures.

  3. 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

  4. 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.

  5. 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.

  6. Using Virtual Reality to Assess Ethical Decisions in Road Traffic Scenarios: Applicability of Value-of-Life-Based Models and Influences of Time Pressure

    OpenAIRE

    S?tfeld, Leon R.; Gast, Richard; K?nig, Peter; Pipa, Gordon

    2017-01-01

    Self-driving cars are posing a new challenge to our ethics. By using algorithms to make decisions in situations where harming humans is possible, probable, or even unavoidable, a self-driving car's ethical behavior comes pre-defined. Ad hoc decisions are made in milliseconds, but can be based on extensive research and debates. The same algorithms are also likely to be used in millions of cars at a time, increasing the impact of any inherent biases, and increasing the importance of getting it ...

  7. 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...

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. Simulation-based algorithms for Markov decision processes

    CERN Document Server

    Chang, Hyeong Soo; Fu, Michael C; Marcus, Steven I

    2013-01-01

    Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences.  Many real-world problems modeled by MDPs have huge state and/or action spaces, giving an opening to the curse of dimensionality and so making practical solution of the resulting models intractable.  In other cases, the system of interest is too complex to allow explicit specification of some of the MDP model parameters, but simulation samples are readily available (e.g., for random transitions and costs). For these settings, various sampling and population-based algorithms have been developed to overcome the difficulties of computing an optimal solution in terms of a policy and/or value function.  Specific approaches include adaptive sampling, evolutionary policy iteration, evolutionary random policy search, and model reference adaptive search. This substantially enlarged new edition reflects the latest developments in novel ...

  13. 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.

  14. 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...

  15. Dopamine and Effort-Based Decision Making

    Directory of Open Access Journals (Sweden)

    Irma Triasih Kurniawan

    2011-06-01

    Full Text Available Motivational theories of choice focus on the influence of goal values and strength of reinforcement to explain behavior. By contrast relatively little is known concerning how the cost of an action, such as effort expended, contributes to a decision to act. Effort-based decision making addresses how we make an action choice based on an integration of action and goal values. Here we review behavioral and neurobiological data regarding the representation of effort as action cost, and how this impacts on decision making. Although organisms expend effort to obtain a desired reward there is a striking sensitivity to the amount of effort required, such that the net preference for an action decreases as effort cost increases. We discuss the contribution of the neurotransmitter dopamine (DA towards overcoming response costs and in enhancing an animal’s motivation towards effortful actions. We also consider the contribution of brain structures, including the basal ganglia (BG and anterior cingulate cortex (ACC, in the internal generation of action involving a translation of reward expectation into effortful action.

  16. Web-based modelling of energy, water and matter fluxes to support decision making in mesoscale catchments??the integrative perspective of GLOWA-Danube

    Science.gov (United States)

    Ludwig, R.; Mauser, W.; Niemeyer, S.; Colgan, A.; Stolz, R.; Escher-Vetter, H.; Kuhn, M.; Reichstein, M.; Tenhunen, J.; Kraus, A.; Ludwig, M.; Barth, M.; Hennicker, R.

    The GLOWA-initiative (Global Change of the water cycle), funded by the German Ministry of Research and Education (BMBF), has been established to address the manifold consequences of Global Change on regional water resources in a variety of catchment areas with different natural and cultural characteristics. Within this framework, the GLOWA-Danube project is dealing with the Upper Danube watershed as a representative mesoscale test site (∼75.000 km 2) for mountain-foreland regions in the temperate mid-latitudes. The principle objective is to identify, examine and develop new techniques of coupled distributed modelling for the integration of natural and socio-economic sciences. The transdisciplinary research in GLOWA-Danube develops an integrated decision support system, called DANUBIA, to investigate the sustainability of future water use. GLOWA-Danube, which is scheduled for a total run-time of eight years to operationally implement and establish DANUBIA, comprises a university-based network of experts with water-related competence in the fields of engineering, natural and social sciences. Co-operation with a network of stakeholders in water resources management of the Upper Danube catchment ensures that practical issues and future problems in the water sector of the region can be addressed. In order to synthesize a common understanding between the project partners, a standardized notation of parameters and functions and a platform-independent structure of computational methods and interfaces has been established, by making use of the unified modelling language, an industry standard for the structuring and co-ordination of large projects in software development [Booch et al., The Unified Modelling Language User Guide, Addison-Wesley, Reading, 1999]. DANUBIA is object-oriented, spatially distributed and raster-based at its core. It applies the concept of “proxels” (process pixels) as its basic objects, which have different dimensions depending on the viewing

  17. Climate-Agriculture-Modeling and Decision Tool for Disease (CAMDT-Disease) for seasonal climate forecast-based crop disease risk management in agriculture

    Science.gov (United States)

    Kim, K. H.; Lee, S.; Han, E.; Ines, A. V. M.

    2017-12-01

    Climate-Agriculture-Modeling and Decision Tool (CAMDT) is a decision support system (DSS) tool that aims to facilitate translations of probabilistic seasonal climate forecasts (SCF) to crop responses such as yield and water stress. Since CAMDT is a software framework connecting different models and algorithms with SCF information, it can be easily customized for different types of agriculture models. In this study, we replaced the DSSAT-CSM-Rice model originally incorporated in CAMDT with a generic epidemiological model, EPIRICE, to generate a seasonal pest outlook. The resulting CAMDT-Disease generates potential risks for selected fungal, viral, and bacterial diseases of rice over the next months by translating SCFs into agriculturally-relevant risk information. The integrated modeling procedure of CAMDT-Disease first disaggregates a given SCF using temporal downscaling methods (predictWTD or FResampler1), runs EPIRICE with the downscaled weather inputs, and finally visualizes the EPIRICE outputs as disease risk compared to that of the previous year and the 30-year-climatological average. In addition, the easy-to-use graphical user interface adopted from CAMDT allows users to simulate "what-if" scenarios of disease risks over different planting dates with given SCFs. Our future work includes the simulation of the effect of crop disease on yields through the disease simulation models with the DSSAT-CSM-Rice model, as disease remains one of the most critical yield-reducing factors in the field.

  18. Minimizing Erosion and Agro-Pollutants Transport from Furrow Irrigated Fields to the Nearby Water Body Using Spatially-Explicit Agent Based Model and Decision Optimization Platform

    Science.gov (United States)

    Ghoveisi, H.; Al Dughaishi, U.; Kiker, G.

    2017-12-01

    Maintaining water quality in agricultural watersheds is a worldwide challenge, especially where furrow irrigation is being practiced. The Yakima River Basin watershed in south central Washington State, (USA) is an example of these impacted areas with elevated load of sediments and other agricultural products due to runoff from furrow-irrigated fields. Within the Yakima basin, the Granger Drain watershed (area of 75 km2) is particularly challenged in this regard with more than 400 flood-irrigated individual parcels (area of 21 km2) growing a variety of crops from maize to grapes. Alternatives for improving water quality from furrow-irrigated parcels include vegetated filter strip (VFS) implementation, furrow water application efficiency, polyacrylamide (PAM) application and irrigation scheduling. These alternatives were simulated separately and in combinations to explore potential Best Management Practices (BMPs) for runoff-related-pollution reduction in a spatially explicit, agent based modeling system (QnD:GrangerDrain). Two regulatory scenarios were tested to BMP adoption within individual parcels. A blanket-style regulatory scenario simulated a total of 60 BMP combinations implemented in all 409 furrow-irrigated parcels. A second regulatory scenario simulated the BMPs in 119 furrow-irrigated parcels designated as "hotspots" based on a standard 12 Mg ha-1 seasonal sediment load. The simulated cumulative runoff and sediment loading from all BMP alternatives were ranked using Multiple Criteria Decision Analysis (MCDA), specifically the Stochastic Multi-Attribute Acceptability Analysis (SMAA) method. Several BMP combinations proved successful in reducing loads below a 25 NTU (91 mg L-1) regulatory sediment concentration. The QnD:GrangerDrain simulations and subsequent MCDA ranking revealed that the BMP combinations of 5 m-VFS and high furrow water efficiency were highly ranked alternatives for both the blanket and hotspot scenarios.

  19. 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.

  20. A Knowledge Management and Decision Support Model for Enterprises

    Directory of Open Access Journals (Sweden)

    Patrizia Ribino

    2011-01-01

    Full Text Available We propose a novel knowledge management system (KMS for enterprises. Our system exploits two different approaches for knowledge representation and reasoning: a document-based approach based on data-driven creation of a semantic space and an ontology-based model. Furthermore, we provide an expert system capable of supporting the enterprise decisional processes and a semantic engine which performs intelligent search on the enterprise knowledge bases. The decision support process exploits the Bayesian networks model to improve business planning process when performed under uncertainty.

  1. Enabling Philippine Farmers to Adapt to Climate Variability Using Seasonal Climate and Weather Forecast with a Crop Simulation Model in an SMS-based Farmer Decision Support System

    Science.gov (United States)

    Ebardaloza, J. B. R.; Trogo, R.; Sabido, D. J.; Tongson, E.; Bagtasa, G.; Balderama, O. F.

    2015-12-01

    Corn farms in the Philippines are rainfed farms, hence, it is of utmost importance to choose the start of planting date so that the critical growth stages that are in need of water will fall on dates when there is rain. Most farmers in the Philippines use superstitions and traditions as basis for farming decisions such as when to start planting [1]. Before climate change, superstitions like planting after a feast day of a saint has worked for them but with the recent progression of climate change, farmers now recognize that there is a need for technological intervention [1]. The application discussed in this paper presents a solution that makes use of meteorological station sensors, localized seasonal climate forecast, localized weather forecast and a crop simulation model to provide recommendations to farmers based on the crop cultivar, soil type and fertilizer type used by farmers. It is critical that the recommendations given to farmers are not generic as each farmer would have different needs based on their cultivar, soil, fertilizer, planting schedule and even location [2]. This application allows the farmer to inquire about whether it will rain in the next seven days, the best date to start planting based on the potential yield upon harvest, when to apply fertilizer and by how much, when to water and by how much. Short messaging service (SMS) is the medium chosen for this application because while mobile penetration in the Philippines is as high as 101%, the smart phone penetration is only at 15% [3]. SMS has been selected as it has been identified as the most effective way of reaching farmers with timely agricultural information and knowledge [4,5]. The recommendations while derived from making use of Automated Weather Station (AWS) sensor data, Weather Research Forecasting (WRF) models and DSSAT 4.5 [9], are translated into the local language of the farmers and in a format that is easily understood as recommended in [6,7,8]. A pilot study has been started

  2. 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.

  3. 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

  4. Classifiers based on optimal decision rules

    KAUST Repository

    Amin, Talha

    2013-11-25

    Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

  5. Classifiers based on optimal decision rules

    KAUST Repository

    Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

    2013-01-01

    Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

  6. 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...

  7. 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

  8. Heuristic decision model for intelligent nuclear power systems design

    International Nuclear Information System (INIS)

    Nassersharif, B.; Portal, M.G.; Gaeta, M.J.

    1989-01-01

    The objective of this project was to investigate intelligent nuclear power systems design. A theoretical model of the design process has been developed. A fundamental process in this model is the heuristic decision making for design (i.e., selection of methods, components, materials, etc.). Rule-based expert systems do not provide the completeness that is necessary to generate good design. A new method, based on the fuzzy set theory, has been developed and is presented here. A feedwater system knowledge base (KB) was developed for a prototype software experiment to benchmark the theory

  9. Coal-Mine Liquidation as a Strategic Managerial Decision: a Decision-Making Model Based on the Options Approach / Likwidacja Kopalni Jako Strategiczna Decyzja Menedżerska: Model Decyzyjny Z Wykorzystaniem Podejścia Opcyjnego

    Science.gov (United States)

    Jewartowski, Tomasz; Mizerka, Jacek; Mróz, Cezary

    2015-09-01

    The aim of this paper is to determine the optimal time of coal mine liquidation given the necessity of bearing the costs of post-mining reclamation. In order to consider the volatility of parameters important for making a liquidation decision and the entrepreneur's flexibility in the decision-making process, the real options approach was applied. Mine liquidation, which is inextricably linked to post-mining reclamation, is examined as an American put option on the market value of continuing the mine's operation which plays the role of the underlying asset. In turn, the role of the exercise price is played by expenditures for mine liquidation and post-mining reclamation, which can be avoided if the decision to close the mine is taken before all the deposits are exhausted. The liquidation option is exercised when the value of liquidation and reclamation cost savings significantly exceeds the continuation value. Mine liquidation was additionally made conditional on the value of funds accumulated to finance post-mining reclamation. Artykuł dotyczy ustalenia optymalnego momentu likwidacji kopalni w związku z koniecznością ponoszenia kosztów rekultywacji gruntów pokopalnianych. W celu uwzględnienia zmienności wartości parametrów istotnych dla podjęcia decyzji o likwidacji oraz elastyczności w podejmowaniu decyzji przez przedsiębiorcę, wykorzystano podejście opcyjne. Likwidację kopalni, która jest nierozłącznie związana z rekultywacją terenów pokopalnianych, rozpatruje się jako amerykańską opcję sprzedaży (put) wystawioną na rynkową wartość kontynuacji działalności kopalni pełniącą rolę instrumentu bazowego. Z kolei rolę ceny wykonania odgrywają nakłady na likwidację kopalni i rekultywację terenów pokopalnianych, poniesienia których można uniknąć, gdy decyzja o wstrzymaniu eksploatacji zapadnie przed wyczerpaniem się złoża. Opcja likwidacji jest wykonywana, gdy kwota nakładów na likwidację i rekultywację znacz

  10. Decision model of project financing based on triangular fuzzy AHP%基于三角模糊AHP的项目融资决策模型

    Institute of Scientific and Technical Information of China (English)

    李香花; 王孟钧

    2012-01-01

    A new infrastructure project financing decision model is constructed by systematically analyzing of project financing modes. It uses the hierarchical decomposition method to decompose the complex project financing mode decision problem and its corresponding evaluation indexes. It uses the Delphi method to evaluate these indexes. Because expert advice is characteristic of fuzzy and uncertainty, expert advice is converted into triangular fuzzy numbers by using the triangular fuzzy language variables. And the fuzzy decision judgment matrixes are constructed. Synthesis weights of all alternative models are obtained and the decisions are made by transforming the judge matrixes and calculating their vectors together with Analytical Hierarchy Process (AHP). The practical case shows that the proposed model provides a good method for the urban infrastructure project finance decision making.%通过对项目融资模式进行系统分析,构建了一个全新的基础设施项目融资模式决策模型.运用层次分解法将复杂项目融资模式决策问题进行分解简化,采用德尔菲法专家打分对备选模式对应的分解指标进行评价.针对专家意见具有模糊性和不确定性的特点,运用三角模糊语言变量,将专家意见转换成三角模糊数并构建模糊决策判断矩阵,再结合层次分析法(AHP)对判断矩阵进行模糊变换和向量计算,得到备选模式综合权重并据以做出决策.最后进行实例验证,为城市基础设施项目融资提供决策参考.

  11. SMARTool: A tool for clinical decision support for the management of patients with coronary artery disease based on modeling of atherosclerotic plaque process.

    Science.gov (United States)

    Sakellarios, Antonis I; Rigas, George; Kigka, Vassiliki; Siogkas, Panagiotis; Tsompou, Panagiota; Karanasiou, Georgia; Exarchos, Themis; Andrikos, Ioannis; Tachos, Nikolaos; Pelosi, Gualtriero; Parodi, Oberdan; Fotiaids, Dimitrios I

    2017-07-01

    SMARTool aims to the development of a clinical decision support system (CDSS) for the management and stratification of patients with coronary artery disease (CAD). This will be achieved by performing computational modeling of the main processes of atherosclerotic plaque growth. More specifically, computed tomography coronary angiography (CTCA) is acquired and 3-dimensional (3D) reconstruction is performed for the arterial trees. Then, blood flow and plaque growth modeling is employed simulating the major processes of atherosclerosis, such as the estimation of endothelial shear stress (ESS), the lipids transportation, low density lipoprotein (LDL) oxidation, macrophages migration and plaque development. The plaque growth model integrates information from genetic and biological data of the patients. The SMARTool system enables also the calculation of the virtual functional assessment index (vFAI), an index equivalent to the invasively measured fractional flow reserve (FFR), to provide decision support for patients with stenosed arteries. Finally, it integrates modeling of stent deployment. In this work preliminary results are presented. More specifically, the reconstruction methodology has mean value of Dice Coefficient and Hausdorff Distance is 0.749 and 1.746, respectively, while low ESS and high LDL concentration can predict plaque progression.

  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. 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

  14. 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

  15. 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

  16. Is there a need for hydrological modelling in decision support systems for nuclear emergencies

    International Nuclear Information System (INIS)

    Raskob, W.; Heling, R.; Zheleznyak, M.

    2004-01-01

    This paper discusses the role of hydrological modelling in decision support systems for nuclear emergencies. In particular, most recent developments such as, the radionuclide transport models integrated in to the decision support system RODOS will be explored. Recent progress in the implementation of physically-based distributed hydrological models for operational forecasting in national and supranational centres, may support a closer cooperation between national hydrological services and therefore, strengthen the use of hydrological and radiological models implemented in decision support systems. (authors)

  17. Risk-based decision making for terrorism applications.

    Science.gov (United States)

    Dillon, Robin L; Liebe, Robert M; Bestafka, Thomas

    2009-03-01

    This article describes the anti-terrorism risk-based decision aid (ARDA), a risk-based decision-making approach for prioritizing anti-terrorism measures. The ARDA model was developed as part of a larger effort to assess investments for protecting U.S. Navy assets at risk and determine whether the most effective anti-terrorism alternatives are being used to reduce the risk to the facilities and war-fighting assets. With ARDA and some support from subject matter experts, we examine thousands of scenarios composed of 15 attack modes against 160 facility types on two installations and hundreds of portfolios of 22 mitigation alternatives. ARDA uses multiattribute utility theory to solve some of the commonly identified challenges in security risk analysis. This article describes the process and documents lessons learned from applying the ARDA model for this application.

  18. An ecologically based model of alcohol-consumption decision making: evidence for the discriminative and predictive role of contextual reward and punishment information.

    Science.gov (United States)

    Bogg, Tim; Finn, Peter R

    2009-05-01

    Using insights from Ecological Systems Theory and Reinforcement Sensitivity Theory, the current study assessed the utility of a series of hypothetical role-based alcohol-consumption scenarios that varied in their presentation of rewarding and punishing information. The scenarios, along with measures of impulsive sensation seeking and a self-report of weekly alcohol consumption, were administered to a sample of alcohol-dependent and non-alcohol-dependent college-age individuals (N = 170). The results showed scenario attendance decisions were largely unaffected by alcohol-dependence status and variations in contextual reward and punishment information. In contrast to the attendance findings, the results for the alcohol-consumption decisions showed alcohol-dependent individuals reported a greater frequency of deciding to drink, as well as indicating greater alcohol consumption in the contexts of complementary rewarding or nonpunishing information. Regression results provided evidence for the criterion-related validity of scenario outcomes in an account of diagnostic alcohol problems. The results are discussed in terms of the conceptual and predictive gains associated with an assessment approach to alcohol-consumption decision making that combines situational information organized and balanced through the frameworks of Ecological Systems Theory and Reinforcement Sensitivity Theory.

  19. 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...

  20. The application of GIS based decision-tree models for generating the spatial distribution of hydromorphic organic landscapes in relation to digital terrain data

    DEFF Research Database (Denmark)

    Kheir, Rania Bou; Bøcher, Peder Klith; Greve, Mette Balslev

    2010-01-01

    Accurate information about organic/mineral soil occurrence is a prerequisite for many land resources management applications (including climate change mitigation). This paper aims at investigating the potential of using geomorphometrical analysis and decision tree modeling to predict the geographic......, realistic and practical, and it can be applied to other areas, thereby providing a tool to facilitate the implementation of pedological/hydrological plans for conservation and sustainable management. It is particularly useful when information about soil properties from conventional field surveys is limited....

  1. Clinical data warehousing for evidence based decision making.

    Science.gov (United States)

    Narra, Lekha; Sahama, Tony; Stapleton, Peta

    2015-01-01

    Large volumes of heterogeneous health data silos pose a big challenge when exploring for information to allow for evidence based decision making and ensuring quality outcomes. In this paper, we present a proof of concept for adopting data warehousing technology to aggregate and analyse disparate health data in order to understand the impact various lifestyle factors on obesity. We present a practical model for data warehousing with detailed explanation which can be adopted similarly for studying various other health issues.

  2. Knowledge based decision making: perspective on natural gas production

    Energy Technology Data Exchange (ETDEWEB)

    Ydstie, B. Erik; Stuland, Kjetil M.

    2009-07-01

    Conclusions (drawn by the author): Decarbonization of energy sources - From coal to renewable. Natural Gas Abundantly available - Norway is no. 3 exporter. Natural gas important as - Hydrogen source for chemicals; - Electricity; - End consumer usage (heating etc). Large potential for application of model based decision making; - Where and when to install platforms and drill wells - How to operate platforms and pipeline systems; - How to operate and optimize chemical production; - Optimization of electricity generation systems. (author)

  3. Development of hybrid artificial intelligent based handover decision algorithm

    Directory of Open Access Journals (Sweden)

    A.M. Aibinu

    2017-04-01

    Full Text Available The possibility of seamless handover remains a mirage despite the plethora of existing handover algorithms. The underlying factor responsible for this has been traced to the Handover decision module in the Handover process. Hence, in this paper, the development of novel hybrid artificial intelligent handover decision algorithm has been developed. The developed model is made up of hybrid of Artificial Neural Network (ANN based prediction model and Fuzzy Logic. On accessing the network, the Received Signal Strength (RSS was acquired over a period of time to form a time series data. The data was then fed to the newly proposed k-step ahead ANN-based RSS prediction system for estimation of prediction model coefficients. The synaptic weights and adaptive coefficients of the trained ANN was then used to compute the k-step ahead ANN based RSS prediction model coefficients. The predicted RSS value was later codified as Fuzzy sets and in conjunction with other measured network parameters were fed into the Fuzzy logic controller in order to finalize handover decision process. The performance of the newly developed k-step ahead ANN based RSS prediction algorithm was evaluated using simulated and real data acquired from available mobile communication networks. Results obtained in both cases shows that the proposed algorithm is capable of predicting ahead the RSS value to about ±0.0002 dB. Also, the cascaded effect of the complete handover decision module was also evaluated. Results obtained show that the newly proposed hybrid approach was able to reduce ping-pong effect associated with other handover techniques.

  4. 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...

  5. Multiple attribute decision making model and application to food safety risk evaluation.

    Directory of Open Access Journals (Sweden)

    Lihua Ma

    Full Text Available Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

  6. Improvements to Air Force Strategic Basing Decisions

    Science.gov (United States)

    2016-01-01

    24th Air Force need to have locations in Silicon 36 Valley or Northern Virginia to draw on the existing cyber industrial bases. Similarly, an issue...cross valuation . Cross valuation results in a simpler model than if GBM were allowed to run until it achieved a perfect fit. In ten-fold cross... valuation , the dataset is randomly split into ten mutually exclusive subsets. The model is fit on nine-tenths of the data, and that model is used to 62

  7. Maintenance planning support method for nuclear power plants based on collective decision making

    International Nuclear Information System (INIS)

    Shimizu, Shunichi; Sakurai, Shoji; Takaoka, Kazushi; Kanemoto, Shigeru; Fukutomi, Shigeki

    1992-01-01

    Inspection and maintenance planning in nuclear power plants is conducted by decision making based on experts' collective consensus. However, since a great deal of time and effort is required to reach a consensus among expert judgments, the establishment of effective decision making methods is necessary. Therefore, the authors developed a method for supporting collective decision making, based on a combination of three types of decision making methods; the Characteristic Diagram method, Interpretative Structural Modeling method, and the Analytic Hierarchy Process method. The proposed method enables us to determine the evaluation criteria systematically for collective decision making, and also allows extracting collective decisions using simplified questionnaires. The proposed method can support reaching a consensus of groups effectively through the evaluation of collective decision structural models and their characteristics. In this paper, the effectiveness of the proposed method was demonstrated through its application to the decision making problem concerning whether or not the improved ultrasonic testing equipment should be adopted at nuclear power plants. (author)

  8. 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

  9. 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)

  10. Pavement maintenance optimization model using Markov Decision Processes

    Science.gov (United States)

    Mandiartha, P.; Duffield, C. F.; Razelan, I. S. b. M.; Ismail, A. b. H.

    2017-09-01

    This paper presents an optimization model for selection of pavement maintenance intervention using a theory of Markov Decision Processes (MDP). There are some particular characteristics of the MDP developed in this paper which distinguish it from other similar studies or optimization models intended for pavement maintenance policy development. These unique characteristics include a direct inclusion of constraints into the formulation of MDP, the use of an average cost method of MDP, and the policy development process based on the dual linear programming solution. The limited information or discussions that are available on these matters in terms of stochastic based optimization model in road network management motivates this study. This paper uses a data set acquired from road authorities of state of Victoria, Australia, to test the model and recommends steps in the computation of MDP based stochastic optimization model, leading to the development of optimum pavement maintenance policy.

  11. Risk-Based Decision Making for Deterioration Processes Using POMDP

    DEFF Research Database (Denmark)

    Nielsen, Jannie Sønderkær; Sørensen, John Dalsgaard

    2015-01-01

    This paper proposes a method for risk-based decision making for maintenance of deteriorating components, based on the partially observable Markov decision process (POMDP). Unlike most methods, the decision polices do not need to be stationary and can vary according to seasons and near the end...

  12. Data warehouse based decision support system in nuclear power plants

    International Nuclear Information System (INIS)

    Nadinic, B.

    2004-01-01

    Safety is an important element in business decision making processes in nuclear power plants. Information about component reliability, structures and systems, data recorded during the nuclear power plant's operation and outage periods, as well as experiences from other power plants are located in different database systems throughout the power plant. It would be possible to create a decision support system which would collect data, transform it into a standardized form and store it in a single location in a format more suitable for analyses and knowledge discovery. This single location where the data would be stored would be a data warehouse. Such data warehouse based decision support system could help make decision making processes more efficient by providing more information about business processes and predicting possible consequences of different decisions. Two main functionalities in this decision support system would be an OLAP (On Line Analytical Processing) and a data mining system. An OLAP system would enable the users to perform fast, simple and efficient multidimensional analysis of existing data and identify trends. Data mining techniques and algorithms would help discover new, previously unknown information from the data as well as hidden dependencies between various parameters. Data mining would also enable analysts to create relevant prediction models that could predict behaviour of different systems during operation and inspection results during outages. The basic characteristics and theoretical foundations of such decision support system are described and the reasons for choosing a data warehouse as the underlying structure are explained. The article analyzes obvious business benefits of such system as well as potential uses of OLAP and data mining technologies. Possible implementation methodologies and problems that may arise, especially in the field of data integration, are discussed and analyzed.(author)

  13. 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)

  14. Probabilistic Decision Based Block Partitioning for Future Video Coding

    KAUST Repository

    Wang, Zhao; Wang, Shiqi; Zhang, Jian; Wang, Shanshe; Ma, Siwei

    2017-01-01

    , the mode decision problem is casted into a probabilistic framework to select the final partition based on the confidence interval decision strategy. Experimental results show that the proposed CIET algorithm can speed up QTBT block partitioning structure

  15. 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 ...

  16. 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-.

  17. 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.

  18. Modeling Common-Sense Decisions in Artificial Intelligence

    Science.gov (United States)

    Zak, Michail

    2010-01-01

    A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation

  19. Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems

    Science.gov (United States)

    Chang, Pei-Chann; Fan, Chin-Yuan; Wang, Yen-Wen

    Data base classification suffers from two well known difficulties, i.e., the high dimensionality and non-stationary variations within the large historic data. This paper presents a hybrid classification model by integrating a case based reasoning technique, a Fuzzy Decision Tree (FDT), and Genetic Algorithms (GA) to construct a decision-making system for data classification in various data base applications. The model is major based on the idea that the historic data base can be transformed into a smaller case-base together with a group of fuzzy decision rules. As a result, the model can be more accurately respond to the current data under classifying from the inductions by these smaller cases based fuzzy decision trees. Hit rate is applied as a performance measure and the effectiveness of our proposed model is demonstrated by experimentally compared with other approaches on different data base classification applications. The average hit rate of our proposed model is the highest among others.

  20. 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...

  1. 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...

  2. 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.

  3. 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...

  4. 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

  5. Functional Freedom: A Psychological Model of Freedom in Decision-Making.

    Science.gov (United States)

    Lau, Stephan; Hiemisch, Anette

    2017-07-05

    The freedom of a decision is not yet sufficiently described as a psychological variable. We present a model of functional decision freedom that aims to fill that role. The model conceptualizes functional freedom as a capacity of people that varies depending on certain conditions of a decision episode. It denotes an inner capability to consciously shape complex decisions according to one's own values and needs. Functional freedom depends on three compensatory dimensions: it is greatest when the decision-maker is highly rational, when the structure of the decision is highly underdetermined, and when the decision process is strongly based on conscious thought and reflection. We outline possible research questions, argue for psychological benefits of functional decision freedom, and explicate the model's implications on current knowledge and research. In conclusion, we show that functional freedom is a scientific variable, permitting an additional psychological foothold in research on freedom, and that is compatible with a deterministic worldview.

  6. Modelling the changing cumulative vulnerability to climate-related hazards for river basin management using a GIS-based multicriteria decision approach

    Science.gov (United States)

    Hung, Hung-Chih; Wu, Ju-Yu; Hung, Chih-Hsuan

    2017-04-01

    1. Background Asia-Pacific region is one of the most vulnerable areas of the world to climate-related hazards and extremes due to rapid urbanization and over-development in hazard-prone areas. It is thus increasingly recognized that the management of land use and reduction of hazard risk are inextricably linked. This is especially critical from the perspective of integrated river basin management. A range of studies has targeted existing vulnerability assessments. However, limited attention has been paid to the cumulative effects of multiple vulnerable factors and their dynamics faced by local communities. This study proposes a novel methodology to access the changing cumulative vulnerability to climate-related hazards, and to examine the relationship between the attraction factors relevant to the general process of urbanization and vulnerability variability with a focus on a river basin management unit. 2. Methods and data The methods applied in this study include three steps. First, using Intergovernmental Panel on Climate Change's (IPCC) approach, a Cumulative Vulnerability Assessment Framework (CVAF) is built with a goal to characterize and compare the vulnerability to climate-related hazards within river basin regions based on a composition of multiple indicators. We organize these indicator metrics into three categories: (1) hazard exposure; (2) socioeconomic sensitivity, and (3) adaptive capacity. Second, the CVAF is applied by combining a geographical information system (GIS)-based spatial statistics technique with a multicriteria decision analysis (MCDA) to assess and map the changing cumulative vulnerability, comparing conditions in 1996 and 2006 in Danshui River Basin, Taiwan. Third, to examine the affecting factors of vulnerability changing, we develop a Vulnerability Changing Model (VCM) using four attraction factors to reflect how the process of urban developments leads to vulnerability changing. The factors are transport networks, land uses

  7. 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.

  8. Rationality versus reality: the challenges of evidence-based decision making for health policy makers.

    Science.gov (United States)

    McCaughey, Deirdre; Bruning, Nealia S

    2010-05-26

    Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the EBDM/EBPM process can be

  9. Rationality versus reality: the challenges of evidence-based decision making for health policy makers

    Directory of Open Access Journals (Sweden)

    Bruning Nealia S

    2010-05-01

    Full Text Available Abstract Background Current healthcare systems have extended the evidence-based medicine (EBM approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. Discussion We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM and evidence-based policy making (EBPM because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. Summary In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial

  10. Rationality versus reality: the challenges of evidence-based decision making for health policy makers

    Science.gov (United States)

    2010-01-01

    Background Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. Discussion We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. Summary In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the

  11. 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.

  12. Practical risk-based decision making: Good decisions made efficiently

    International Nuclear Information System (INIS)

    Haire, M.J.; Guthrie, V.; Walker, D.; Singer, R.

    1995-01-01

    The Robotics and Process Systems Division of the Oak Ridge National Laboratory and the Westinghouse Savannah River Company have teamed with JBF Associates, Inc. to address risk-based robotic planning. The objective of the project is to provide systematic, risk-based relative comparisons of competing alternatives for solving clean-up problems at DOE facilities. This paper presents the methodology developed, describes the software developed to efficiently apply the methodology, and discusses the results of initial applications for DOE. The paper also addresses current work in applying the approach to problems in other industries (including an example from the hydrocarbon processing industry)

  13. Ontology based decision system for breast cancer diagnosis

    Science.gov (United States)

    Trabelsi Ben Ameur, Soumaya; Cloppet, Florence; Wendling, Laurent; Sellami, Dorra

    2018-04-01

    In this paper, we focus on analysis and diagnosis of breast masses inspired by expert concepts and rules. Accordingly, a Bag of Words is built based on the ontology of breast cancer diagnosis, accurately described in the Breast Imaging Reporting and Data System. To fill the gap between low level knowledge and expert concepts, a semantic annotation is developed using a machine learning tool. Then, breast masses are classified into benign or malignant according to expert rules implicitly modeled with a set of classifiers (KNN, ANN, SVM and Decision Tree). This semantic context of analysis offers a frame where we can include external factors and other meta-knowledge such as patient risk factors as well as exploiting more than one modality. Based on MRI and DECEDM modalities, our developed system leads a recognition rate of 99.7% with Decision Tree where an improvement of 24.7 % is obtained owing to semantic analysis.

  14. Bayesian averaging over Decision Tree models for trauma severity scoring.

    Science.gov (United States)

    Schetinin, V; Jakaite, L; Krzanowski, W

    2018-01-01

    Health care practitioners analyse possible risks of misleading decisions and need to estimate and quantify uncertainty in predictions. We have examined the "gold" standard of screening a patient's conditions for predicting survival probability, based on logistic regression modelling, which is used in trauma care for clinical purposes and quality audit. This methodology is based on theoretical assumptions about data and uncertainties. Models induced within such an approach have exposed a number of problems, providing unexplained fluctuation of predicted survival and low accuracy of estimating uncertainty intervals within which predictions are made. Bayesian method, which in theory is capable of providing accurate predictions and uncertainty estimates, has been adopted in our study using Decision Tree models. Our approach has been tested on a large set of patients registered in the US National Trauma Data Bank and has outperformed the standard method in terms of prediction accuracy, thereby providing practitioners with accurate estimates of the predictive posterior densities of interest that are required for making risk-aware decisions. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Decision support based on process mining

    NARCIS (Netherlands)

    Aalst, van der W.M.P.; Burstein, F.; Holsapple, C.W.

    2008-01-01

    Process mining techniques allow for the analysis of business processes based on event logs. For example, the audit trails of a workflow management system, the transaction logs of an enterprise resource planning system, and the electronic patient records in a hospital can be used to discover models

  16. Monitoring of intratidal lung mechanics: a Graphical User Interface for a model-based decision support system for PEEP-titration in mechanical ventilation.

    Science.gov (United States)

    Buehler, S; Lozano-Zahonero, S; Schumann, S; Guttmann, J

    2014-12-01

    In mechanical ventilation, a careful setting of the ventilation parameters in accordance with the current individual state of the lung is crucial to minimize ventilator induced lung injury. Positive end-expiratory pressure (PEEP) has to be set to prevent collapse of the alveoli, however at the same time overdistension should be avoided. Classic approaches of analyzing static respiratory system mechanics fail in particular if lung injury already prevails. A new approach of analyzing dynamic respiratory system mechanics to set PEEP uses the intratidal, volume-dependent compliance which is believed to stay relatively constant during one breath only if neither atelectasis nor overdistension occurs. To test the success of this dynamic approach systematically at bedside or in an animal study, automation of the computing steps is necessary. A decision support system for optimizing PEEP in form of a Graphical User Interface (GUI) was targeted. Respiratory system mechanics were analyzed using the gliding SLICE method. The resulting shapes of the intratidal compliance-volume curve were classified into one of six categories, each associated with a PEEP-suggestion. The GUI should include a graphical representation of the results as well as a quality check to judge the reliability of the suggestion. The implementation of a user-friendly GUI was successfully realized. The agreement between modelled and measured pressure data [expressed as root-mean-square (RMS)] tested during the implementation phase with real respiratory data from two patient studies was below 0.2 mbar for data taken in volume controlled mode and below 0.4 mbar for data taken in pressure controlled mode except for two cases with RMS rational decision-making model for PEEP-titration.

  17. 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.

  18. 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.

  19. An agent-based model of farmer decision-making and water quality impacts at the watershed scale under markets for carbon allowances and a second-generation biofuel crop

    Science.gov (United States)

    Ng, Tze Ling; Eheart, J. Wayland; Cai, Ximing; Braden, John B.

    2011-09-01

    An agent-based model of farmers' crop and best management practice (BMP) decisions is developed and linked to a hydrologic-agronomic model of a watershed, to examine farmer behavior, and the attendant effects on stream nitrate load, under the influence of markets for conventional crops, carbon allowances, and a second-generation biofuel crop. The agent-based approach introduces interactions among farmers about new technologies and market opportunities, and includes the updating of forecast expectations and uncertainties using Bayesian inference. The model is applied to a semi-hypothetical example case of farmers in the Salt Creek Watershed in Central Illinois, and a sensitivity analysis is performed to effect a first-order assessment of the plausibility of the results. The results show that the most influential factors affecting farmers' decisions are crop prices, production costs, and yields. The results also show that different farmer behavioral profiles can lead to different predictions of farmer decisions. The farmers who are predicted to be more likely to adopt new practices are those who interact more with other farmers, are less risk averse, quick to adjust their expectations, and slow to reduce their forecast confidence. The decisions of farmers have direct water quality consequences, especially those pertaining to the adoption of the second-generation biofuel crop, which are estimated to lead to reductions in stream nitrate load. The results, though empirically untested, appear plausible and consistent with general farmer behavior. The results demonstrate the usefulness of the coupled agent-based and hydrologic-agronomic models for normative research on watershed management on the water-energy nexus.

  20. Functional Freedom: A Psychological Model of Freedom in Decision-Making

    Science.gov (United States)

    Lau, Stephan; Hiemisch, Anette

    2017-01-01

    The freedom of a decision is not yet sufficiently described as a psychological variable. We present a model of functional decision freedom that aims to fill that role. The model conceptualizes functional freedom as a capacity of people that varies depending on certain conditions of a decision episode. It denotes an inner capability to consciously shape complex decisions according to one’s own values and needs. Functional freedom depends on three compensatory dimensions: it is greatest when the decision-maker is highly rational, when the structure of the decision is highly underdetermined, and when the decision process is strongly based on conscious thought and reflection. We outline possible research questions, argue for psychological benefits of functional decision freedom, and explicate the model’s implications on current knowledge and research. In conclusion, we show that functional freedom is a scientific variable, permitting an additional psychological foothold in research on freedom, and that is compatible with a deterministic worldview. PMID:28678165

  1. Fundamentals of the fuzzy logic-based generalized theory of decisions

    CERN Document Server

    Aliev, Rafik Aziz

    2013-01-01

    Every day decision making and decision making in complex human-centric systems are characterized by imperfect decision-relevant information. Main drawback of the existing decision theories is namely incapability to deal with imperfect information and modeling vague preferences. Actually, a paradigm of non-numerical probabilities in decision making has a long history and arose also in Keynes’s analysis of uncertainty. There is a need for further generalization – a move to decision theories with perception-based imperfect information described in NL. The languages of new decision models for human-centric systems should be not languages based on binary logic but human-centric computational schemes able to operate on NL-described information. Development of new theories is now possible due to an increased computational power of information processing systems which allows for computations with imperfect information, particularly, imprecise and partially true information, which are much more complex than comput...

  2. An Intuitionistic Fuzzy Stochastic Decision-Making Method Based on Case-Based Reasoning and Prospect Theory

    Directory of Open Access Journals (Sweden)

    Peng Li

    2017-01-01

    Full Text Available According to the case-based reasoning method and prospect theory, this paper mainly focuses on finding a way to obtain decision-makers’ preferences and the criterion weights for stochastic multicriteria decision-making problems and classify alternatives. Firstly, we construct a new score function for an intuitionistic fuzzy number (IFN considering the decision-making environment. Then, we aggregate the decision-making information in different natural states according to the prospect theory and test decision-making matrices. A mathematical programming model based on a case-based reasoning method is presented to obtain the criterion weights. Moreover, in the original decision-making problem, we integrate all the intuitionistic fuzzy decision-making matrices into an expectation matrix using the expected utility theory and classify or rank the alternatives by the case-based reasoning method. Finally, two illustrative examples are provided to illustrate the implementation process and applicability of the developed method.

  3. A Decision Model for Multi-market Advertising Budget Allocation Based on Vidale-Wolfe Model%基于Vidale-Wolfe模型的多市场广告预算分配决策模型

    Institute of Scientific and Technical Information of China (English)

    张鹏; 王兴元

    2013-01-01

    Advertising decision problem has been a hotspot concerned by marketing managers and scholars for a long time.More and more enterprises are facing multi-market with the development of society and economy and it becomes a more important problem for enterprises that how to allocate advertising budget to get the best advertising effect in condition of multi-market and fixed total advertising budget.Vidale-Wolfe model is selected as the advertising response model,based on which the decision model for multi-market advertising budget allocation is proposed.As some marketing strategy requires special sales rate demands in some markets.The proposed model consists of two parts:the latter cares about how to keep certain sales rate,while the former does not.The optimization model is constructed.The method to get arguments value and how to solve the model are discussed.An example is given at last.%广告决策问题很长时间以来都是营销经理和学者们关注的热点.随着社会经济发展,越来越多的企业面对多个市场.如何在多个市场、广告总预算固定的状况下,合理分配各个市场广告预算以收到最优广告效果,是一个企业关心的较为重要的问题.经过比较,选择Vidale-Wolfe模型作为广告反应模型,在此基础上建立了多市场广告预算分配决策模型.考虑到一些营销策略对某些市场有特殊销售速率要求,该模型分为无特殊销售速率维持要求的多市场广告预算分配决策模型和有特殊销售速率维持要求的多市场广告预算分配决策模型两类,后者探讨了销售速率变化与达到指定销售速率两种要求下的广告预算最优分配问题,构建了优化模型,提出了模型参数取值与模型求解方法,最后给出了一个算例.

  4. 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

  5. On Rationality of Decision Models Incorporating Emotion-Related Valuing and Hebbian Learning

    NARCIS (Netherlands)

    Treur, J.; Umair, M.

    2011-01-01

    In this paper an adaptive decision model based on predictive loops through feeling states is analysed from the perspective of rationality. Four different variations of Hebbian learning are considered for different types of connections in the decision model. To assess the extent of rationality, a

  6. Modelling Joint Decision Making Processes Involving Emotion-Related Valuing and Mutual Empathic Understanding

    NARCIS (Netherlands)

    Treur, J.

    2011-01-01

    In this paper a social agent model for joint decision making is presented addressing the role of mutually acknowledged empathic understanding in the decision making. The model is based on principles from recent neurological theories on mirror neurons, internal simulation, and emotion-related

  7. PRESCRIPTIVE MODEL FOR THE STRATEGIC DECISION-MAKING PROCESSES FROM THE ROMANIAN ENTERPRISES

    Directory of Open Access Journals (Sweden)

    Razvan STEFANESCU

    2005-01-01

    Full Text Available This paper proposes a prescriptive model for the strategic decision-making from the Romanianenterprises. Within the paper there will be described the phases implied in solving a strategicproblem. Finally, there will be presented a strategic decision from a Romanian enterprise, elaboratedon the base of the model.

  8. Data acquisition in modeling using neural networks and decision trees

    Directory of Open Access Journals (Sweden)

    R. Sika

    2011-04-01

    Full Text Available The paper presents a comparison of selected models from area of artificial neural networks and decision trees in relation with actualconditions of foundry processes. The work contains short descriptions of used algorithms, their destination and method of data preparation,which is a domain of work of Data Mining systems. First part concerns data acquisition realized in selected iron foundry, indicating problems to solve in aspect of casting process modeling. Second part is a comparison of selected algorithms: a decision tree and artificial neural network, that is CART (Classification And Regression Trees and BP (Backpropagation in MLP (Multilayer Perceptron networks algorithms.Aim of the paper is to show an aspect of selecting data for modeling, cleaning it and reducing, for example due to too strong correlationbetween some of recorded process parameters. Also, it has been shown what results can be obtained using two different approaches:first when modeling using available commercial software, for example Statistica, second when modeling step by step using Excel spreadsheetbasing on the same algorithm, like BP-MLP. Discrepancy of results obtained from these two approaches originates from a priorimade assumptions. Mentioned earlier Statistica universal software package, when used without awareness of relations of technologicalparameters, i.e. without user having experience in foundry and without scheduling ranks of particular parameters basing on acquisition, can not give credible basis to predict the quality of the castings. Also, a decisive influence of data acquisition method has been clearly indicated, the acquisition should be conducted according to repetitive measurement and control procedures. This paper is based on about 250 records of actual data, for one assortment for 6 month period, where only 12 data sets were complete (including two that were used for validation of neural network and useful for creating a model. It is definitely too

  9. Modelling financial risk in open pit mine projects: Implications for strategic decision-making

    OpenAIRE

    Abdel Sabour, S.A.; Wood, G.

    2009-01-01

    Strategic decisions in the mining industry are made under multiple technical and market uncertainties. Therefore, to reach the best possible decision, based on information available, it is necessary to integrate uncertainty about the input variables and model financial risk of the project's merit measures. However, this rovides few useful insights to decision-makers unless accompanied by modeling management responses to uncertainty resolutions. It is widely acknowledged that conventional deci...

  10. 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...

  11. An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

    Directory of Open Access Journals (Sweden)

    Bo Sun

    2012-01-01

    Full Text Available According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negotiation and independent negotiation is established, and the heuristic rules applied to global and local maintenance decision making is proposed. Based on Contract Net Protocol and the heuristic rules, the maintenance decision making algorithm is put forward. Finally, a fleet consisting of 10 aircrafts on a 3-wave continuous mission is illustrated to verify this method. Simulation results indicate that this method can improve the availability of the fleet, meet mission demands, rationalize the utilization of support resources and provide support for online maintenance decision making among a mission oriented fleet.

  12. An environmentally sustainable decision model for urban solid waste management

    International Nuclear Information System (INIS)

    Costi, P.; Minciardi, R.; Robba, M.; Rovatti, M.; Sacile, R.

    2004-01-01

    The aim of this work is to present the structure and the application of a decision support system (DSS) designed to help decision makers of a municipality in the development of incineration, disposal, treatment and recycling integrated programs. Specifically, within a MSW management system, several treatment plants and facilities can generally be found: separators, plants for production of refuse derived fuel (RDF), incinerators with energy recovery, plants for treatment of organic material, and sanitary landfills. The main goal of the DSS is to plan the MSW management, defining the refuse flows that have to be sent to recycling or to different treatment or disposal plants, and suggesting the optimal number, the kinds, and the localization of the plants that have to be active. The DSS is based on a decision model that requires the solution of a constrained non-linear optimization problem, where some decision variables are binary and other ones are continuous. The objective function takes into account all possible economic costs, whereas constraints arise from technical, normative, and environmental issues. Specifically, pollution and impacts, induced by the overall solid waste management system, are considered through the formalization of constraints on incineration emissions and on negative effects produced by disposal or other particular treatments

  13. 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.

  14. Anytime decision making based on unconstrained influence diagrams

    DEFF Research Database (Denmark)

    Luque, Manuel; Nielsen, Thomas Dyhre; Jensen, Finn Verner

    2016-01-01

    . This paper addresses this problem by proposing an anytime algorithm that at any time provides a qualified recommendation for the first decisions of the problem. The algorithm performs a heuristic-based search in a decision tree representation of the problem. We provide a framework for analyzing......Unconstrained influence diagrams extend the language of influence diagrams to cope with decision problems in which the order of the decisions is unspecified. Thus, when solving an unconstrained influence diagram we not only look for an optimal policy for each decision, but also for a so-called step......-policy specifying the next decision given the observations made so far. However, due to the complexity of the problem, temporal constraints can force the decision maker to act before the solution algorithm has finished, and, in particular, before an optimal policy for the first decision has been computed...

  15. Decision Support Systems and the Conflict Model of Decision Making: A Stimulus for New Computer-Assisted Careers Guidance Systems.

    Science.gov (United States)

    Ballantine, R. Malcolm

    Decision Support Systems (DSSs) are computer-based decision aids to use when making decisions which are partially amenable to rational decision-making procedures but contain elements where intuitive judgment is an essential component. In such situations, DSSs are used to improve the quality of decision-making. The DSS approach is based on Simon's…

  16. Artificial intelligence based decision support for trumpeter swan management

    Science.gov (United States)

    Sojda, Richard S.

    2002-01-01

    The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988

  17. [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.

  18. 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.

  19. 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.

  20. 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.

  1. Decision tree-based modelling for identification of potential interactions between type 2 diabetes risk factors: a decade follow-up in a Middle East prospective cohort study.

    Science.gov (United States)

    Ramezankhani, Azra; Hadavandi, Esmaeil; Pournik, Omid; Shahrabi, Jamal; Azizi, Fereidoun; Hadaegh, Farzad

    2016-12-01

    The current study was undertaken for use of the decision tree (DT) method for development of different prediction models for incidence of type 2 diabetes (T2D) and for exploring interactions between predictor variables in those models. Prospective cohort study. Tehran Lipid and Glucose Study (TLGS). A total of 6647 participants (43.4% men) aged >20 years, without T2D at baselines ((1999-2001) and (2002-2005)), were followed until 2012. 2 series of models (with and without 2-hour postchallenge plasma glucose (2h-PCPG)) were developed using 3 types of DT algorithms. The performances of the models were assessed using sensitivity, specificity, area under the ROC curve (AUC), geometric mean (G-Mean) and F-Measure. T2D was primary outcome which defined if fasting plasma glucose (FPG) was ≥7 mmol/L or if the 2h-PCPG was ≥11.1 mmol/L or if the participant was taking antidiabetic medication. During a median follow-up of 9.5 years, 729 new cases of T2D were identified. The Quick Unbiased Efficient Statistical Tree (QUEST) algorithm had the highest sensitivity and G-Mean among all the models for men and women. The models that included 2h-PCPG had sensitivity and G-Mean of (78% and 0.75%) and (78% and 0.78%) for men and women, respectively. Both models achieved good discrimination power with AUC above 0.78. FPG, 2h-PCPG, waist-to-height ratio (WHtR) and mean arterial blood pressure (MAP) were the most important factors to incidence of T2D in both genders. Among men, those with an FPG≤4.9 mmol/L and 2h-PCPG≤7.7 mmol/L had the lowest risk, and those with an FPG>5.3 mmol/L and 2h-PCPG>4.4 mmol/L had the highest risk for T2D incidence. In women, those with an FPG≤5.2 mmol/L and WHtR≤0.55 had the lowest risk, and those with an FPG>5.2 mmol/L and WHtR>0.56 had the highest risk for T2D incidence. Our study emphasises the utility of DT for exploring interactions between predictor variables. Published by the BMJ Publishing Group Limited. For permission

  2. Nuclear emergency response planning based on participatory decision analytic approaches

    International Nuclear Information System (INIS)

    Sinkko, K.

    2004-10-01

    This work was undertaken in order to develop methods and techniques for evaluating systematically and comprehensively protective action strategies in the case of a nuclear or radiation emergency. This was done in a way that the concerns and issues of all key players related to decisions on protective actions could be aggregated into decision- making transparently and in an equal manner. An approach called facilitated workshop, based on the theory of Decision Analysis, was tailored and tested in the planning of actions to be taken. The work builds on case studies in which it was assumed that a hypothetical accident in a nuclear power plant had led to a release of considerable amounts of radionuclides and therefore different types of protective actions should be considered. Altogether six workshops were organised in which all key players were represented, i.e., the authorities, expert organisations, industry and agricultural producers. The participants were those responsible for preparing advice or presenting matters for those responsible for the formal decision-making. Many preparatory meetings were held with various experts to prepare information for the workshops. It was considered essential that the set-up strictly follow the decision- making process to which the key players are accustomed. Key players or stakeholders comprise responsible administrators and organisations, politicians as well as representatives of the citizens affected and other persons who will and are likely to take part in decision-making in nuclear emergencies. The realistic nature and the disciplined process of a facilitated workshop and commitment to decision-making yielded up insight in many radiation protection issues. The objectives and attributes which are considered in a decision on protective actions were discussed in many occasions and were defined for different accident scenario to come. In the workshops intervention levels were derived according justification and optimisation

  3. Decision Making Based On Management Information System and Decision Support System

    Directory of Open Access Journals (Sweden)

    Şükrü Ada

    2015-04-01

    Full Text Available Information hasbecome an essentialresource for managing modern organizations. This is so because today’sbusiness environment is volatile, dynamic, turbulent and necessitates the burgeoning demand for accurate, relevant, complete,timely and economical information needed to drive the decision-making process in order to accentuate organizational abilities to manage opportunities and threat. MIS work on online mode with an average processing speed. Generally, it is used by low level management. Decision support system are powerful tool that assist corporate executives, administrators and other senior officials in making decision regarding the problem. Management Information Systems is a useful tool that provided organized and summarized information in a proper time to decision makers and enable making accurate decision for managers in organizations. This paper will discuss the concept, characteristics, types of MIS, the MIS model, and in particular it will highlight the impact and role of MIS on decision making.

  4. 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

  5. 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.

  6. The Application of Time-Delay Dependent H∞ Control Model in Manufacturing Decision Optimization

    Directory of Open Access Journals (Sweden)

    Haifeng Guo

    2015-01-01

    Full Text Available This paper uses a time-delay dependent H∞ control model to analyze the effect of manufacturing decisions on the process of transmission from resources to capability. We establish a theoretical framework of manufacturing management process based on three terms: resource, manufacturing decision, and capability. Then we build a time-delay H∞ robust control model to analyze the robustness of manufacturing management. With the state feedback controller between manufacturing resources and decision, we find that there is an optimal decision to adjust the process of transmission from resources to capability under uncertain environment. Finally, we provide an example to prove the robustness of this model.

  7. Effects of dynamic agricultural decision making in an ecohydrological model

    Science.gov (United States)

    Reichenau, T. G.; Krimly, T.; Schneider, K.

    2012-04-01

    Due to various interdependencies between the cycles of water, carbon, nitrogen, and energy the impacts of climate change on ecohydrological systems can only be investigated in an integrative way. Furthermore, the human intervention in the environmental processes makes the system even more complex. On the one hand human impact affects natural systems. On the other hand the changing natural systems have a feedback on human decision making. One of the most important examples for this kind of interaction can be found in the agricultural sector. Management dates (planting, fertilization, harvesting) are chosen based on meteorological conditions and yield expectations. A faster development of crops under a warmer climate causes shorter cropping seasons. The choice of crops depends on their profitability, which is mainly determined by market prizes, the agro-political framework, and the (climate dependent) crop yield. This study investigates these relations for the district Günzburg located in the Upper Danube catchment in southern Germany. The modeling system DANUBIA was used to perform dynamically coupled simulations of plant growth, surface and soil hydrological processes, soil nitrogen transformations, and agricultural decision making. The agro-economic model simulates decisions on management dates (based on meteorological conditions and the crops' development state), on fertilization intensities (based on yield expectations), and on choice of crops (based on profitability). The environmental models included in DANUBIA are to a great extent process based to enable its use in a climate change scenario context. Scenario model runs until 2058 were performed using an IPCC A1B forcing. In consecutive runs, dynamic crop management, dynamic crop selection, and a changing agro-political framework were activated. Effects of these model features on hydrological and ecological variables were analyzed separately by comparing the results to a model run with constant crop

  8. 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

  9. 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...

  10. Information integration in perceptual and value-based decisions

    OpenAIRE

    Tsetsos, K.

    2012-01-01

    Research on the psychology and neuroscience of simple, evidence-based choices has led to an impressive progress in capturing the underlying mental processes as optimal mechanisms that make the fastest decision for a specified accuracy. The idea that decision-making is an optimal process stands in contrast with findings in more complex, motivation-based decisions, focussed on multiple goals with trade-offs. Here, a number of paradoxical and puzzling choice behaviours have been r...

  11. 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...

  12. Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets.

    Science.gov (United States)

    Doubravsky, Karel; Dohnal, Mirko

    2015-01-01

    Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.

  13. Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets.

    Directory of Open Access Journals (Sweden)

    Karel Doubravsky

    Full Text Available Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (rechecked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.

  14. 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.

  15. 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.

  16. 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.

  17. Maintenance Decision Based on Data Fusion of Aero Engines

    Directory of Open Access Journals (Sweden)

    Huawei Wang

    2013-01-01

    Full Text Available Maintenance has gained a great importance as a support function for ensuring aero engine reliability and availability. Cost-effectiveness and risk control are two basic criteria for accurate maintenance. Given that aero engines have much condition monitoring data, this paper presents a new condition-based maintenance decision system that employs data fusion for improving accuracy of reliability evaluation. Bayesian linear model has been applied, so that the performance degradation evaluation of aero engines could be realized. A reliability evaluation model has been presented based on gamma process, which achieves the accurate evaluation by information fusion. In reliability evaluation model, the shape parameter is estimated by the performance degradation evaluation result, and the scale parameter is estimated by failure, inspection, and repair information. What is more, with such reliability evaluation as input variables and by using particle swarm optimization (PSO, a stochastic optimization of maintenance decision for aircraft engines has been presented, in which the effectiveness and the accuracy are demonstrated by a numerical example.

  18. A naturalistic decision making model for simulated human combatants

    International Nuclear Information System (INIS)

    HUNTER, KEITH O.; HART, WILLIAM E.; FORSYTHE, JAMES C.

    2000-01-01

    The authors describe a naturalistic behavioral model for the simulation of small unit combat. This model, Klein's recognition-primed decision making (RPD) model, is driven by situational awareness rather than a rational process of selecting from a set of action options. They argue that simulated combatants modeled with RPD will have more flexible and realistic responses to a broad range of small-scale combat scenarios. Furthermore, they note that the predictability of a simulation using an RPD framework can be easily controlled to provide multiple evaluations of a given combat scenario. Finally, they discuss computational issues for building an RPD-based behavior engine for fully automated combatants in small conflict scenarios, which are being investigated within Sandia's Next Generation Site Security project

  19. 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,…

  20. Evidence-based surgery: Dissemination, communication, decision aids

    NARCIS (Netherlands)

    Knops, A.M.

    2013-01-01

    Surgeons are expected to make treatment decisions that are based on the best available evidence. Moreover, they are called to recognise that important decisions should also be shared with patients. While dissemination of evidence-based surgery and communication of evidence to patients have been

  1. Solving the Problem of Multiple-Criteria Building Design Decisions with respect to the Fire Safety of Occupants: An Approach Based on Probabilistic Modelling

    Directory of Open Access Journals (Sweden)

    Egidijus Rytas Vaidogas

    2015-01-01

    Full Text Available The design of buildings may include a comparison of alternative architectural and structural solutions. They can be developed at different levels of design process. The alternative design solutions are compared and ranked by applying methods of multiple-criteria decision-making (MCDM. Each design is characterised by a number of criteria used in a MCDM problem. The paper discusses how to choose MCDM criteria expressing fire safety related to alternative designs. Probability of a successful evacuation of occupants from a building fire and difference between evacuation time and time to untenable conditions are suggested as the most important criteria related to fire safety. These two criteria are treated as uncertain quantities expressed by probability distributions. Monte Carlo simulation of fire and evacuation processes is natural means for an estimation of these distributions. The presence of uncertain criteria requires applying stochastic MCDM methods for ranking alternative designs. An application of the safety-related criteria is illustrated by an example which analyses three alternative architectural floor plans prepared for a reconstruction of a medical building. A MCDM method based on stochastic simulation is used to solve the example problem.

  2. 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.

  3. 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.

  4. 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

  5. Randomness in the network inhibits cooperation based on the bounded rational collective altruistic decision

    International Nuclear Information System (INIS)

    Ohdaira, Tetsushi

    2014-01-01

    Previous studies discussing cooperation employ the best decision that every player knows all information regarding the payoff matrix and selects the strategy of the highest payoff. Therefore, they do not discuss cooperation based on the altruistic decision with limited information (bounded rational altruistic decision). In addition, they do not cover the case where every player can submit his/her strategy several times in a match of the game. This paper is based on Ohdaira's reconsideration of the bounded rational altruistic decision, and also employs the framework of the prisoner's dilemma game (PDG) with sequential strategy. The distinction between this study and the Ohdaira's reconsideration is that the former covers the model of multiple groups, but the latter deals with the model of only two groups. Ohdaira's reconsideration shows that the bounded rational altruistic decision facilitates much more cooperation in the PDG with sequential strategy than Ohdaira and Terano's bounded rational second-best decision does. However, the detail of cooperation of multiple groups based on the bounded rational altruistic decision has not been resolved yet. This study, therefore, shows how randomness in the network composed of multiple groups affects the increase of the average frequency of mutual cooperation (cooperation between groups) based on the bounded rational altruistic decision of multiple groups. We also discuss the results of the model in comparison with related studies which employ the best decision. (paper)

  6. Randomness in the network inhibits cooperation based on the bounded rational collective altruistic decision

    Science.gov (United States)

    Ohdaira, Tetsushi

    2014-07-01

    Previous studies discussing cooperation employ the best decision that every player knows all information regarding the payoff matrix and selects the strategy of the highest payoff. Therefore, they do not discuss cooperation based on the altruistic decision with limited information (bounded rational altruistic decision). In addition, they do not cover the case where every player can submit his/her strategy several times in a match of the game. This paper is based on Ohdaira's reconsideration of the bounded rational altruistic decision, and also employs the framework of the prisoner's dilemma game (PDG) with sequential strategy. The distinction between this study and the Ohdaira's reconsideration is that the former covers the model of multiple groups, but the latter deals with the model of only two groups. Ohdaira's reconsideration shows that the bounded rational altruistic decision facilitates much more cooperation in the PDG with sequential strategy than Ohdaira and Terano's bounded rational second-best decision does. However, the detail of cooperation of multiple groups based on the bounded rational altruistic decision has not been resolved yet. This study, therefore, shows how randomness in the network composed of multiple groups affects the increase of the average frequency of mutual cooperation (cooperation between groups) based on the bounded rational altruistic decision of multiple groups. We also discuss the results of the model in comparison with related studies which employ the best decision.

  7. Behavioural modelling of irrigation decision making under water scarcity

    Science.gov (United States)

    Foster, T.; Brozovic, N.; Butler, A. P.

    2013-12-01

    Providing effective policy solutions to aquifer depletion caused by abstraction for irrigation is a key challenge for socio-hydrology. However, most crop production functions used in hydrological models do not capture the intraseasonal nature of irrigation planning, or the importance of well yield in land and water use decisions. Here we develop a method for determining stochastic intraseasonal water use that is based on observed farmer behaviour but is also theoretically consistent with dynamically optimal decision making. We use the model to (i) analyse the joint land and water use decision by farmers; (ii) to assess changes in behaviour and production risk in response to water scarcity; and (iii) to understand the limits of applicability of current methods in policy design. We develop a biophysical model of water-limited crop yield building on the AquaCrop model. The model is calibrated and applied to case studies of irrigated corn production in Nebraska and Texas. We run the model iteratively, using long-term climate records, to define two formulations of the crop-water production function: (i) the aggregate relationship between total seasonal irrigation and yield (typical of current approaches); and (ii) the stochastic response of yield and total seasonal irrigation to the choice of an intraseasonal soil moisture target and irrigated area. Irrigated area (the extensive margin decision) and per-area irrigation intensity (the intensive margin decision) are then calculated for different seasonal water restrictions (corresponding to regulatory policies) and well yield constraints on intraseasonal abstraction rates (corresponding to aquifer system limits). Profit- and utility-maximising decisions are determined assuming risk neutrality and varying degrees of risk aversion, respectively. Our results demonstrate that the formulation of the production function has a significant impact on the response to water scarcity. For low well yields, which are the major concern

  8. 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

  9. Mitigation of negative ecological and socio-economic impacts of the Diama dam on the Senegal River Delta wetland (Mauritania), using a model based decision support system

    Science.gov (United States)

    Duvail, S.; Hamerlynck, O.

    construction of the Diama dam in 1986 and the floodplain and estuarine areas on the Mauritanian bank were affected severely by the absence of floods. In 1994, managed flood releases were initiated in the Bell basin (4000 ha) of the Diawling National Park, as part of a rehabilitation effort. The basin was designated as a joint management area between traditional users and the Park authority and a revised management plan was developed through a participatory approach based on a topographical, hydro-climatic, ecological and socio-economic data. Hydraulic modelling was developed as a tool to support stakeholder negotiations on the desired characteristics of the managed flood releases. Initially, a water balance model was developed. The data were then integrated into a one-dimensional hydraulic model, MIKE 11 (DHI, 2000). When associated with a Digital Elevation Model and a Geographic Information System, (Arc View), the model provided a dynamic description of floods. Flood extent, water depth and flood duration data were combined with ecological and socio-economic data. The water requirements of the different stakeholders were converted to flood scenarios and the benefits and constraints analysed. A consensus scenario was reached through a participatory process. The volume of flood release required to restore the delta does not affect hydro-power generation, navigation or intensive irrigation, for which the dams in the basin were constructed. Hydraulic modelling provided useful inputs to stakeholder discussions and allows investigation of untested flood scenarios.

  10. Detecting Structural Metadata with Decision Trees and Transformation-Based Learning

    National Research Council Canada - National Science Library

    Kim, Joungbum; Schwarm, Sarah E; Ostendorf, Mari

    2004-01-01

    .... Specifically, combinations of decision trees and language models are used to predict sentence ends and interruption points and given these events transformation based learning is used to detect edit...

  11. Science-based natural resource management decisions: what are they?

    Science.gov (United States)

    T.J. Mills; T.M. Quigley; F.J. Everest

    2001-01-01

    While many people interested in natural resources management propose science-based decisions, it is not clear what “science-based” means. Science-based decisions are those that result from the full and complete consideration of the relevant science information. We offer five guidelines to focus the scientist’s contributions to science-based decisionmaking and use the...

  12. The role of decision analytic modeling in the health economic assessment of spinal intervention.

    Science.gov (United States)

    Edwards, Natalie C; Skelly, Andrea C; Ziewacz, John E; Cahill, Kevin; McGirt, Matthew J

    2014-10-15

    Narrative review. To review the common tenets, strengths, and weaknesses of decision modeling for health economic assessment and to review the use of decision modeling in the spine literature to date. For the majority of spinal interventions, well-designed prospective, randomized, pragmatic cost-effectiveness studies that address the specific decision-in-need are lacking. Decision analytic modeling allows for the estimation of cost-effectiveness based on data available to date. Given the rising demands for proven value in spine care, the use of decision analytic modeling is rapidly increasing by clinicians and policy makers. This narrative review discusses the general components of decision analytic models, how decision analytic models are populated and the trade-offs entailed, makes recommendations for how users of spine intervention decision models might go about appraising the models, and presents an overview of published spine economic models. A proper, integrated, clinical, and economic critical appraisal is necessary in the evaluation of the strength of evidence provided by a modeling evaluation. As is the case with clinical research, all options for collecting health economic or value data are not without their limitations and flaws. There is substantial heterogeneity across the 20 spine intervention health economic modeling studies summarized with respect to study design, models used, reporting, and general quality. There is sparse evidence for populating spine intervention models. Results mostly showed that interventions were cost-effective based on $100,000/quality-adjusted life-year threshold. Spine care providers, as partners with their health economic colleagues, have unique clinical expertise and perspectives that are critical to interpret the strengths and weaknesses of health economic models. Health economic models must be critically appraised for both clinical validity and economic quality before altering health care policy, payment strategies, or

  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. A Game-Chain-Based Approach for Decision Making

    OpenAIRE

    An, Tingyu; Watanabe, tsunami

    2009-01-01

    Nowadays, with the rapid development of information society, decision-making problems become more and more complicated especially in large scale systems such as infrastructure, environmental and industrial fields, which are usually accompanied by psychological competition between involved parties in a complicated, uncertain and dynamic situation. From a holistic perspective of system, a specific decision-making method which is described as game-chain-based decision making has been proposed in...

  15. Validating the predictions of case-based decision theory

    OpenAIRE

    Radoc, Benjamin

    2015-01-01

    Real-life decision-makers typically do not know all possible outcomes arising from alternative courses of action. Instead, when people face a problem, they may rely on the recollection of their past personal experience: the situation, the action taken, and the accompanying consequence. In addition, the applicability of a past experience in decision-making may depend on how similar the current problem is to situations encountered previously. Case-based decision theory (CBDT), proposed by Itzha...

  16. 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

  17. 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.

  18. CUDT: A CUDA Based Decision Tree Algorithm

    Directory of Open Access Journals (Sweden)

    Win-Tsung Lo

    2014-01-01

    Full Text Available Decision tree is one of the famous classification methods in data mining. Many researches have been proposed, which were focusing on improving the performance of decision tree. However, those algorithms are developed and run on traditional distributed systems. Obviously the latency could not be improved while processing huge data generated by ubiquitous sensing node in the era without new technology help. In order to improve data processing latency in huge data mining, in this paper, we design and implement a new parallelized decision tree algorithm on a CUDA (compute unified device architecture, which is a GPGPU solution provided by NVIDIA. In the proposed system, CPU is responsible for flow control while the GPU is responsible for computation. We have conducted many experiments to evaluate system performance of CUDT and made a comparison with traditional CPU version. The results show that CUDT is 5∼55 times faster than Weka-j48 and is 18 times speedup than SPRINT for large data set.

  19. Utility-maximizing model of household time use for independent, shared, and allocated activities incorporating group decision mechanisms

    NARCIS (Netherlands)

    Zhang, J.; Timmermans, H.J.P.; Borgers, A.W.J.

    2002-01-01

    Existing activity-based models of transport demand typically assume an individual decision-making process. The focus on theories of individual decision making may be partially due to the lack of behaviorally oriented modeling methodologies for group decision making. Therefore, an attempt has been

  20. Robust Inventory System Optimization Based on Simulation and Multiple Criteria Decision Making

    Directory of Open Access Journals (Sweden)

    Ahmad Mortazavi

    2014-01-01

    Full Text Available Inventory management in retailers is difficult and complex decision making process which is related to the conflict criteria, also existence of cyclic changes and trend in demand is inevitable in many industries. In this paper, simulation modeling is considered as efficient tool for modeling of retailer multiproduct inventory system. For simulation model optimization, a novel multicriteria and robust surrogate model is designed based on multiple attribute decision making (MADM method, design of experiments (DOE, and principal component analysis (PCA. This approach as a main contribution of this paper, provides a framework for robust multiple criteria decision making under uncertainty.

  1. 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...

  2. Multi-criteria weighted order based maintenance decision making

    NARCIS (Netherlands)

    Dhanisetty, V.S.V.; Verhagen, W.J.C.; Curran, R.

    2017-01-01

    Decision making in daily maintenance requires consideration of multiple factors. The importance of each of the factors fluctuates depending on the repair scenario and the needs of the maintainer. In order to include the prioritisation of multiple criteria, a weighted decision making model is

  3. CorRECTreatment: a web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree.

    Science.gov (United States)

    Suner, A; Karakülah, G; Dicle, O; Sökmen, S; Çelikoğlu, C C

    2015-01-01

    The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratiodecisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.

  4. Models and theories of prescribing decisions: A review and suggested a new model.

    Science.gov (United States)

    Murshid, Mohsen Ali; Mohaidin, Zurina

    2017-01-01

    To date, research on the prescribing decisions of physician lacks sound theoretical foundations. In fact, drug prescribing by doctors is a complex phenomenon influenced by various factors. Most of the existing studies in the area of drug prescription explain the process of decision-making by physicians via the exploratory approach rather than theoretical. Therefore, this review is an attempt to suggest a value conceptual model that explains the theoretical linkages existing between marketing efforts, patient and pharmacist and physician decision to prescribe the drugs. The paper follows an inclusive review approach and applies the previous theoretical models of prescribing behaviour to identify the relational factors. More specifically, the report identifies and uses several valuable perspectives such as the 'persuasion theory - elaboration likelihood model', the stimuli-response marketing model', the 'agency theory', the theory of planned behaviour,' and 'social power theory,' in developing an innovative conceptual paradigm. Based on the combination of existing methods and previous models, this paper suggests a new conceptual model of the physician decision-making process. This unique model has the potential for use in further research.

  5. Cost effectiveness of ovarian reserve testing in in vitro fertilization: a Markov decision-analytic model

    NARCIS (Netherlands)

    Moolenaar, Lobke M.; Broekmans, Frank J. M.; van Disseldorp, Jeroen; Fauser, Bart C. J. M.; Eijkemans, Marinus J. C.; Hompes, Peter G. A.; van der Veen, Fulco; Mol, Ben Willem J.

    2011-01-01

    To compare the cost effectiveness of ovarian reserve testing in in vitro fertilization (IVF). A Markov decision model based on data from the literature and original patient data. Decision analytic framework. Computer-simulated cohort of subfertile women aged 20 to 45 years who are eligible for IVF.

  6. Cost effectiveness of ovarian reserve testing in in vitro fertilization : a Markov decision-analytic model

    NARCIS (Netherlands)

    Moolenaar, Lobke M.; Broekmans, Frank J. M.; van Disseldorp, Jeroen; Fauser, Bart C. J. M.; Eijkemans, Marinus J. C.; Hompes, Peter G. A.; van der Veen, Fulco; Mol, Ben Willem J.

    2011-01-01

    Objective: To compare the cost effectiveness of ovarian reserve testing in in vitro fertilization (IVF). Design: A Markov decision model based on data from the literature and original patient data. Setting: Decision analytic framework. Patient(s): Computer-simulated cohort of subfertile women aged

  7. Assessing the Utility of the Willingness/Prototype Model in Predicting Help-Seeking Decisions

    Science.gov (United States)

    Hammer, Joseph H.; Vogel, David L.

    2013-01-01

    Prior research on professional psychological help-seeking behavior has operated on the assumption that the decision to seek help is based on intentional and reasoned processes. However, research on the dual-process prototype/willingness model (PWM; Gerrard, Gibbons, Houlihan, Stock, & Pomery, 2008) suggests health-related decisions may also…

  8. Mild cognitive impairment is associated with poorer decision-making in community-based older persons.

    Science.gov (United States)

    Han, S Duke; Boyle, Patricia A; James, Bryan D; Yu, Lei; Bennett, David A

    2015-04-01

    To test the hypothesis that mild cognitive impairment (MCI) is associated with poorer financial and healthcare decision-making. Community-based epidemiological cohort study. Communities throughout northeastern Illinois. Older persons without dementia from the Rush Memory and Aging Project (N = 730). All participants underwent a detailed clinical evaluation and decision-making assessment using a measure that closely approximates materials used in real-world financial and healthcare settings. This allowed for measurement of total decision-making and financial and healthcare decision-making. Regression models were used to examine whether MCI was associated with a lower level of decision-making. In subsequent analyses, the relationship between specific cognitive systems (episodic memory, semantic memory, working memory, perceptual speed, visuospatial ability) and decision-making was explored in participants with MCI. MCI was associated with lower total, financial, and healthcare decision-making scores after accounting for the effects of age, education, and sex. The effect of MCI on total decision-making was equivalent to the effect of more than 10 additional years of age. Additional models showed that, when considering multiple cognitive systems, perceptual speed accounted for the most variance in decision-making in participants with MCI. Persons with MCI may have poorer financial and healthcare decision-making in real-world situations, and perceptual speed may be an important contributor to poorer decision-making in persons with MCI. © 2015, Copyright the Authors Journal compilation © 2015, The American Geriatrics Society.

  9. 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

  10. Model Based Temporal Reasoning

    Science.gov (United States)

    Rabin, Marla J.; Spinrad, Paul R.; Fall, Thomas C.

    1988-03-01

    Systems that assess the real world must cope with evidence that is uncertain, ambiguous, and spread over time. Typically, the most important function of an assessment system is to identify when activities are occurring that are unusual or unanticipated. Model based temporal reasoning addresses both of these requirements. The differences among temporal reasoning schemes lies in the methods used to avoid computational intractability. If we had n pieces of data and we wanted to examine how they were related, the worst case would be where we had to examine every subset of these points to see if that subset satisfied the relations. This would be 2n, which is intractable. Models compress this; if several data points are all compatible with a model, then that model represents all those data points. Data points are then considered related if they lie within the same model or if they lie in models that are related. Models thus address the intractability problem. They also address the problem of determining unusual activities if the data do not agree with models that are indicated by earlier data then something out of the norm is taking place. The models can summarize what we know up to that time, so when they are not predicting correctly, either something unusual is happening or we need to revise our models. The model based reasoner developed at Advanced Decision Systems is thus both intuitive and powerful. It is currently being used on one operational system and several prototype systems. It has enough power to be used in domains spanning the spectrum from manufacturing engineering and project management to low-intensity conflict and strategic assessment.

  11. In silico prediction of toxicity of phenols to Tetrahymena pyriformis by using genetic algorithm and decision tree-based modeling approach.

    Science.gov (United States)

    Abbasitabar, Fatemeh; Zare-Shahabadi, Vahid

    2017-04-01

    Risk assessment of chemicals is an important issue in environmental protection; however, there is a huge lack of experimental data for a large number of end-points. The experimental determination of toxicity of chemicals involves high costs and time-consuming process. In silico tools such as quantitative structure-toxicity relationship (QSTR) models, which are constructed on the basis of computational molecular descriptors, can predict missing data for toxic end-points for existing or even not yet synthesized chemicals. Phenol derivatives are known to be aquatic pollutants. With this background, we aimed to develop an accurate and reliable QSTR model for the prediction of toxicity of 206 phenols to Tetrahymena pyriformis. A multiple linear regression (MLR)-based QSTR was obtained using a powerful descriptor selection tool named Memorized_ACO algorithm. Statistical parameters of the model were 0.72 and 0.68 for R training 2 and R test 2 , respectively. To develop a high-quality QSTR model, classification and regression tree (CART) was employed. Two approaches were considered: (1) phenols were classified into different modes of action using CART and (2) the phenols in the training set were partitioned to several subsets by a tree in such a manner that in each subset, a high-quality MLR could be developed. For the first approach, the statistical parameters of the resultant QSTR model were improved to 0.83 and 0.75 for R training 2 and R test 2 , respectively. Genetic algorithm was employed in the second approach to obtain an optimal tree, and it was shown that the final QSTR model provided excellent prediction accuracy for the training and test sets (R training 2 and R test 2 were 0.91 and 0.93, respectively). The mean absolute error for the test set was computed as 0.1615. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. 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

  13. Feasibility of web-based decision aids in neurological patients

    NARCIS (Netherlands)

    van Til, Janine Astrid; Drossaert, Constance H.C.; Renzenbrink, Gerbert J.; Snoek, Govert J.; Dijkstra, Evelien; Stiggelbout, Anne M.; IJzerman, Maarten Joost

    2010-01-01

    Decision aids (DAs) may be helpful in improving patients' participation in medical decision-making. We investigated the potential for web-based DAs in a rehabilitation population. Two self-administered DAs focused on the treatment of acquired ankle-foot impairment in stroke and the treatment of

  14. School-Based Decision-Making: The Canadian Perspective.

    Science.gov (United States)

    Peters, Frank

    1997-01-01

    In Canada, school-based decision making is a political expedient to co-opt public support for public education at the same time as financial resources to schools are being curtailed. School councils are advisory in nature and have no statutory position in either school or school-system decisions. (17 references) (MLF)

  15. Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

    Science.gov (United States)

    Dolan, James G

    2010-01-01

    Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

  16. Protocol-based care: the standardisation of decision-making?

    Science.gov (United States)

    Rycroft-Malone, Jo; Fontenla, Marina; Seers, Kate; Bick, Debra

    2009-05-01

    To explore how protocol-based care affects clinical decision-making. In the context of evidence-based practice, protocol-based care is a mechanism for facilitating the standardisation of care and streamlining decision-making through rationalising the information with which to make judgements and ultimately decisions. However, whether protocol-based care does, in the reality of practice, standardise decision-making is unknown. This paper reports on a study that explored the impact of protocol-based care on nurses' decision-making. Theoretically informed by realistic evaluation and the promoting action on research implementation in health services framework, a case study design using ethnographic methods was used. Two sites were purposively sampled; a diabetic and endocrine unit and a cardiac medical unit. Within each site, data collection included observation, postobservation semi-structured interviews with staff and patients, field notes, feedback sessions and document review. Data were inductively and thematically analysed. Decisions made by nurses in both sites were varied according to many different and interacting factors. While several standardised care approaches were available for use, in reality, a variety of information sources informed decision-making. The primary approach to knowledge exchange and acquisition was person-to-person; decision-making was a social activity. Rarely were standardised care approaches obviously referred to; nurses described following a mental flowchart, not necessarily linked to a particular guideline or protocol. When standardised care approaches were used, it was reported that they were used flexibly and particularised. While the logic of protocol-based care is algorithmic, in the reality of clinical practice, other sources of information supported nurses' decision-making process. This has significant implications for the political goal of standardisation. The successful implementation and judicious use of tools such as

  17. 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.

  18. 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…

  19. 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...

  20. 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

  1. 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

  2. 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

  3. Knowledge Management Portal: A Simplified Model to Help Decision Makers

    International Nuclear Information System (INIS)

    Ogawa, I.; Hernandes Tabares, R.

    2015-01-01

    The aim of this work is to present a simplified model that could help the nuclear industry to keep the expertise of safeguards professionals in touch with the state of the art, and also to have available information in the Portal of Knowledge Management. It can also provide indicators and general data for decision makers. Authors have developed the concept based on their own experience through systems running in hydroelectric and gas fired plants, and one exclusive system that manage all courses in one University. It is under development a Portal of Knowledge Management for NPP dealing with information obtained of Strategic Plans, Budgets and Economics, Operation Performance, Maintenance and Surveillance Plans, Training and Education Programs, QA Programs, Operational Experience, Safety Culture, and Engineering of Human Factors. This model will provide indicators for decision makers. Training and education module is prepared according to profile of each individual and his attributes, tasks and capabilities, and training and education programmes. The system could apply self-assessment questionnaires; immersive learning using media (video) classes, and test applications using questions randomly selected from data bank, as well as could make applications to certificate people. All these data are analyzed and generate indicators about strongest and weakness points. Managers could have indication of individual's deficiency even though in training programmes on a real time basis. Another tool that could be applied to the model is the remote operation of supervision equipment. The model is developed using web-based tools, like ASP.NET encrypted by 128 bits, and web site https. Finally, it is important to stress that the model can be customized according to industry preference. (author)

  4. 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.

  5. 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.

  6. Risk-Based Decision Support of Water Resource Management Alternatives

    National Research Council Canada - National Science Library

    West, Paul D; Trainor, Timothy E

    2006-01-01

    .... A model is presented that combines a new risk assessment methodology with traditional decision-making tools to enable systems engineers to capture the full spectrum of operational risks during the design process...

  7. Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

    Directory of Open Access Journals (Sweden)

    Ajay Kumar Saxena

    2002-05-01

    Full Text Available Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives postulated by various groups emphasized the need of an intelligent group decision support system approach in this field. In this paper, an Integrated Multimedia based Intelligent Group Decision Support System (IM1GDSS is presented, and its main components are analyzed and discussed. In particular attention is focused on the Data Base, Model Base, Central Black Board (CBB and Multicriteria Futuristic Decision Process (MFDP module. The model base interacts with Electrical Power Network Load Forecasting and Planning (EPNLFP Module; Resource Optimization, Modeling and Simulation (ROMAS Module; Electrical Power Network Control and Evaluation Process (EPNCAEP Module, and MFDP Module through CBB for strategic planning, management control, operational planning and transaction processing. The richness of multimedia channels adds a totally new dimension in a group decision making for Electrical Power Network. The proposed IMIGDSS is a user friendly, highly interactive group decision making system, based on efficient intelligent and multimedia communication support for group discussions, retrieval of content and multi criteria decision analysis.

  8. Using the ACT-R architecture to specify 39 quantitative process models of decision making

    Directory of Open Access Journals (Sweden)

    Julian N. Marewski

    2011-08-01

    Full Text Available Hypotheses about decision processes are often formulated qualitatively and remain silent about the interplay of decision, memorial, and other cognitive processes. At the same time, existing decision models are specified at varying levels of detail, making it difficult to compare them. We provide a methodological primer on how detailed cognitive architectures such as ACT-R allow remedying these problems. To make our point, we address a controversy, namely, whether noncompensatory or compensatory processes better describe how people make decisions from the accessibility of memories. We specify 39 models of accessibility-based decision processes in ACT-R, including the noncompensatory recognition heuristic and various other popular noncompensatory and compensatory decision models. Additionally, to illustrate how such models can be tested, we conduct a model comparison, fitting the models to one experiment and letting them generalize to another. Behavioral data are best accounted for by race models. These race models embody the noncompensatory recognition heuristic and compensatory models as a race between competing processes, dissolving the dichotomy between existing decision models.

  9. Reward optimization in the primate brain: a probabilistic model of decision making under uncertainty.

    Directory of Open Access Journals (Sweden)

    Yanping Huang

    Full Text Available A key problem in neuroscience is understanding how the brain makes decisions under uncertainty. Important insights have been gained using tasks such as the random dots motion discrimination task in which the subject makes decisions based on noisy stimuli. A descriptive model known as the drift diffusion model has previously been used to explain psychometric and reaction time data from such tasks but to fully explain the data, one is forced to make ad-hoc assumptions such as a time-dependent collapsing decision boundary. We show that such assumptions are unnecessary when decision making is viewed within the framework of partially observable Markov decision processes (POMDPs. We propose an alternative model for decision making based on POMDPs. We show that the motion discrimination task reduces to the problems of (1 computing beliefs (posterior distributions over the unknown direction and motion strength from noisy observations in a bayesian manner, and (2 selecting actions based on these beliefs to maximize the expected sum of future rewards. The resulting optimal policy (belief-to-action mapping is shown to be equivalent to a collapsing decision threshold that governs the switch from evidence accumulation to a discrimination decision. We show that the model accounts for both accuracy and reaction time as a function of stimulus strength as well as different speed-accuracy conditions in the random dots task.

  10. 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.

  11. 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

  12. Accelerated bridge construction (ABC) decision making and economic modeling tool.

    Science.gov (United States)

    2011-12-01

    In this FHWA-sponsored pool funded study, a set of decision making tools, based on the Analytic Hierarchy Process (AHP) was developed. This tool set is prepared for transportation specialists and decision-makers to determine if ABC is more effective ...

  13. Probabilistic Decision Based Block Partitioning for Future Video Coding

    KAUST Repository

    Wang, Zhao

    2017-11-29

    In the latest Joint Video Exploration Team development, the quadtree plus binary tree (QTBT) block partitioning structure has been proposed for future video coding. Compared to the traditional quadtree structure of High Efficiency Video Coding (HEVC) standard, QTBT provides more flexible patterns for splitting the blocks, which results in dramatically increased combinations of block partitions and high computational complexity. In view of this, a confidence interval based early termination (CIET) scheme is proposed for QTBT to identify the unnecessary partition modes in the sense of rate-distortion (RD) optimization. In particular, a RD model is established to predict the RD cost of each partition pattern without the full encoding process. Subsequently, the mode decision problem is casted into a probabilistic framework to select the final partition based on the confidence interval decision strategy. Experimental results show that the proposed CIET algorithm can speed up QTBT block partitioning structure by reducing 54.7% encoding time with only 1.12% increase in terms of bit rate. Moreover, the proposed scheme performs consistently well for the high resolution sequences, of which the video coding efficiency is crucial in real applications.

  14. 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.

  15. A decision support system-based procedure for evaluation and ...

    Indian Academy of Sciences (India)

    with an overview of the web-based Decision Support System (DSS) developed to facilitate its wide adop- tion. .... contributes significant catchment management and water supply functions .... experience in engagement and facilitation methods.

  16. Multi-robot Cooperation Behavior Decision Based on Psychological Values

    Directory of Open Access Journals (Sweden)

    Jian JIANG

    2014-01-01

    Full Text Available The method based on psychology concept has been proved to be a successful tool used for human-robot interaction. But its related research in multi-robot cooperation has remained scarce until recent studies. To solve the problem, a decision-making mechanism based on psychological values is presented to be regarded as the basis of the multi-robot cooperation. Robots give birth to psychological values based on the estimations of environment, teammates and themselves. The mapping relationship between psychological values and cooperation tendency threshold values is set up with artificial neural network. Robots can make decision on the bases of these threshold values in cooperation scenes. Experiments show that the multi-robot cooperation method presented in the paper not only can ensure the rationality of robots’ decision-making, but also can ensure the speediness of robots’ decision-making.

  17. SADA: Ecological Risk Based Decision Support System for Selective Remediation

    Science.gov (United States)

    Spatial Analysis and Decision Assistance (SADA) is freeware that implements terrestrial ecological risk assessment and yields a selective remediation design using its integral geographical information system, based on ecological and risk assessment inputs. Selective remediation ...

  18. 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.

  19. 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...

  20. 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.

  1. Models and theories of prescribing decisions: A review and suggested a new model

    Science.gov (United States)

    Mohaidin, Zurina

    2017-01-01

    To date, research on the prescribing decisions of physician lacks sound theoretical foundations. In fact, drug prescribing by doctors is a complex phenomenon influenced by various factors. Most of the existing studies in the area of drug prescription explain the process of decision-making by physicians via the exploratory approach rather than theoretical. Therefore, this review is an attempt to suggest a value conceptual model that explains the theoretical linkages existing between marketing efforts, patient and pharmacist and physician decision to prescribe the drugs. The paper follows an inclusive review approach and applies the previous theoretical models of prescribing behaviour to identify the relational factors. More specifically, the report identifies and uses several valuable perspectives such as the ‘persuasion theory - elaboration likelihood model’, the stimuli–response marketing model’, the ‘agency theory’, the theory of planned behaviour,’ and ‘social power theory,’ in developing an innovative conceptual paradigm. Based on the combination of existing methods and previous models, this paper suggests a new conceptual model of the physician decision-making process. This unique model has the potential for use in further research. PMID:28690701

  2. Models and theories of prescribing decisions: A review and suggested a new model

    Directory of Open Access Journals (Sweden)

    Ali Murshid M

    2017-06-01

    Full Text Available To date, research on the prescribing decisions of physician lacks sound theoretical foundations. In fact, drug prescribing by doctors is a complex phenomenon influenced by various factors. Most of the existing studies in the area of drug prescription explain the process of decision-making by physicians via the exploratory approach rather than theoretical. Therefore, this review is an attempt to suggest a value conceptual model that explains the theoretical linkages existing between marketing efforts, patient and pharmacist and physician decision to prescribe the drugs. The paper follows an inclusive review approach and applies the previous theoretical models of prescribing behaviour to identify the relational factors. More specifically, the report identifies and uses several valuable perspectives such as the ‘persuasion theory - elaboration likelihood model’, the stimuli–response marketing model’, the ‘agency theory’, the theory of planned behaviour,’ and ‘social power theory,’ in developing an innovative conceptual paradigm. Based on the combination of existing methods and previous models, this paper suggests a new conceptual model of the physician decision-making process. This unique model has the potential for use in further research.

  3. 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...

  4. A Decision Analytic Approach to Exposure-Based Chemical ...

    Science.gov (United States)

    The manufacture of novel synthetic chemicals has increased in volume and variety, but often the environmental and health risks are not fully understood in terms of toxicity and, in particular, exposure. While efforts to assess risks have generally been effective when sufficient data are available, the hazard and exposure data necessary to assess risks adequately are unavailable for the vast majority of chemicals in commerce. The US Environmental Protection Agency has initiated the ExpoCast Program to develop tools for rapid chemical evaluation based on potential for exposure. In this context, a model is presented in which chemicals are evaluated based on inherent chemical properties and behaviorally-based usage characteristics over the chemical’s life cycle. These criteria are assessed and integrated within a decision analytic framework, facilitating rapid assessment and prioritization for future targeted testing and systems modeling. A case study outlines the prioritization process using 51 chemicals. The results show a preliminary relative ranking of chemicals based on exposure potential. The strength of this approach is the ability to integrate relevant statistical and mechanistic data with expert judgment, allowing for an initial tier assessment that can further inform targeted testing and risk management strategies. The National Exposure Research Laboratory′s (NERL′s) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in suppor

  5. PREMISES FOR A MODEL OF DECISION – MAKING ON THE FINANCING OF A PROJECT

    Directory of Open Access Journals (Sweden)

    Popovici Ioana

    2010-07-01

    Full Text Available The classical theory of finance is based on the premises of rationality and maximizing profits that accompany economic decision-making. Complementarily, the modern theory of behavioral finance studies the effect of emotional and psychological factors of decision- maker on the choice of financing sources for economic activities. In opposition with the classical perspective, the contemporary theory of finance brings up to the stage various aspects of decision making, including elements of strategic behavior towards risk. All these contradictory elements are used as premises for modeling the decision making process of financing a project.

  6. 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.

  7. 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

  8. Effects of tailored neck-shoulder pain treatment based on a decision model guided by clinical assessments and standardized functional tests. A study protocol of a randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Björklund Martin

    2012-05-01

    Full Text Available Abstract Background A major problem with rehabilitation interventions for neck pain is that the condition may have multiple causes, thus a single treatment approach is seldom efficient. The present study protocol outlines a single blinded randomised controlled trial evaluating the effect of tailored treatment for neck-shoulder pain. The treatment is based on a decision model guided by standardized clinical assessment and functional tests with cut-off values. Our main hypothesis is that the tailored treatment has better short, intermediate and long-term effects than either non-tailored treatment or treatment-as-usual (TAU on pain and function. We sub-sequentially hypothesize that tailored and non-tailored treatment both have better effect than TAU. Methods/Design 120 working women with minimum six weeks of nonspecific neck-shoulder pain aged 20–65, are allocated by minimisation with the factors age, duration of pain, pain intensity and disability in to the groups tailored treatment (T, non-tailored treatment (NT or treatment-as-usual (TAU. Treatment is given to the groups T and NT for 11 weeks (27 sessions evenly distributed. An extensive presentation of the tests and treatment decision model is provided. The main treatment components are manual therapy, cranio-cervical flexion exercise and strength training, EMG-biofeedback training, treatment for cervicogenic headache, neck motor control training. A decision algorithm based on the baseline assessment determines the treatment components given to each participant of T- and NT-groups. Primary outcome measures are physical functioning (Neck Disability Index and average pain intensity last week (Numeric Rating Scale. Secondary outcomes are general improvement (Patient Global Impression of Change scale, symptoms (Profile Fitness Mapping neck questionnaire, capacity to work in the last 6 weeks (quality and quantity and pressure pain threshold of m. trapezius. Primary and secondary outcomes will

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

    Science.gov (United States)

    Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, Samuel; Mzoughi, Olfa; Toumi, Mondher

    2014-01-01

    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). A model was built to assess policy scenarios' impact on the pharmaceutical budgets of seven member states of the EU, namely France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. The following scenarios were tested: expanding the UK policies to EU, changing time to market access, modifying generic price and penetration, shifting the distribution chain of biosimilars (retail/hospital). Applying the UK policy resulted in dramatic savings for Germany (10 times the base case forecast) and substantial additional savings for France and Portugal (2 and 4 times the base case forecast, respectively). Delaying time to market was found be to a very powerful tool to reduce pharmaceutical expenditure. Applying the EU transparency directive (6-month process for pricing and reimbursement) increased pharmaceutical expenditure for all countries (from 1.1 to 4 times the base case forecast), except in Germany (additional savings). Decreasing the price of generics and boosting the penetration rate, as well as shifting distribution of biosimilars through hospital chain were also key methods to reduce pharmaceutical expenditure. Change in the level of reimbursement rate to 100% in all countries led to an important increase in the pharmaceutical budget. Forecasting pharmaceutical expenditure is a critical exercise to inform policy decision makers. The most important leverages identified by the model on pharmaceutical budget were driven by generic and biosimilar prices, penetration rate, and distribution. Reducing, even slightly, the prices of

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

    Science.gov (United States)

    Rémuzat, Cécile; Urbinati, Duccio; Kornfeld, Åsa; Vataire, Anne-Lise; Cetinsoy, Laurent; Aballéa, 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 scenarios’ impact on the pharmaceutical budgets of seven member states of the EU, namely France, Germany, Greece, Hungary, Poland, Portugal, and the United Kingdom. The following scenarios were tested: expanding the UK policies to EU, changing time to market access, modifying generic price and penetration, shifting the distribution chain of biosimilars (retail/hospital). Results Applying the UK policy resulted in dramatic savings for Germany (10 times the base case forecast) and substantial additional savings for France and Portugal (2 and 4 times the base case forecast, respectively). Delaying time to market was found be to a very powerful tool to reduce pharmaceutical expenditure. Applying the EU transparency directive (6-month process for pricing and reimbursement) increased pharmaceutical expenditure for all countries (from 1.1 to 4 times the base case forecast), except in Germany (additional savings). Decreasing the price of generics and boosting the penetration rate, as well as shifting distribution of biosimilars through hospital chain were also key methods to reduce pharmaceutical expenditure. Change in the level of reimbursement rate to 100% in all countries led to an important increase in the pharmaceutical budget. Conclusions Forecasting pharmaceutical expenditure is a critical exercise to inform policy decision makers. The most important leverages identified by the model on pharmaceutical budget were driven by generic and biosimilar prices, penetration rate

  11. Permutation based decision making under fuzzy environment using Tabu search

    Directory of Open Access Journals (Sweden)

    Mahdi Bashiri

    2012-04-01

    Full Text Available One of the techniques, which are used for Multiple Criteria Decision Making (MCDM is the permutation. In the classical form of permutation, it is assumed that weights and decision matrix components are crisp. However, when group decision making is under consideration and decision makers could not agree on a crisp value for weights and decision matrix components, fuzzy numbers should be used. In this article, the fuzzy permutation technique for MCDM problems has been explained. The main deficiency of permutation is its big computational time, so a Tabu Search (TS based algorithm has been proposed to reduce the computational time. A numerical example has illustrated the proposed approach clearly. Then, some benchmark instances extracted from literature are solved by proposed TS. The analyses of the results show the proper performance of the proposed method.

  12. The Impact of Weights on the Quality of Agricultural Producers' Multicriteria Decision Models

    Directory of Open Access Journals (Sweden)

    Agata Sielska

    2015-01-01

    Full Text Available Decisions regarding agricultural production involve multiple goals. A multicriteria approach allows decision makers to consider more aspects of the decision scenario, although it also leads to other problems, such as difficulties with the selection of goals or criteria, as well as assigning them appropriate weights. It is argued that not only do goals vary depending on the decision-makers' socioeconomic features, but their relative importance changes as well. A simulation study has been conducted based on the Farm Accountancy Data Network (FADN database. We use the distance-to-the-negative-solution maximization model. Seven sets of criteria and different sets of weights are considered. The main purpose of the study is to determine the impact of weights on the quality of the model. Quality is assessed by comparing the optimal and observed values of the decision variables. The results lead to the conclusion that the differences between the quality of various models are small. (original abstract

  13. The rational choice model in family decision making at the end of life.

    Science.gov (United States)

    Karasz, Alison; Sacajiu, Galit; Kogan, Misha; Watkins, Liza

    2010-01-01

    Most end-of-life decisions are made by family members. Current ethical guidelines for family decision making are based on a hierarchical model that emphasizes the patient's wishes over his or her best interests. Evidence suggests that the model poorly reflects the strategies and priorities of many families. Researchers observed and recorded 26 decision-making meetings between hospital staff and family members. Semi-structured follow-up interviews were conducted. Transcriptions were analyzed using qualitative techniques. For both staff and families, consideration of a patient's best interests generally took priority over the patient's wishes. Staff generally introduced discussion of the patient's wishes for rhetorical purposes, such as persuasion. Competing moral frameworks, which de-emphasized the salience of patients' autonomy and "right to choose," played a role in family decision making. The priority given to the patients' wishes in the hierarchical model does not reflect the priorities of staff and families in making decisions about end-of-life care.

  14. Frame-based safety analysis approach for decision-based errors

    International Nuclear Information System (INIS)

    Fan, Chin-Feng; Yihb, Swu

    1997-01-01

    A frame-based approach is proposed to analyze decision-based errors made by automatic controllers or human operators due to erroneous reference frames. An integrated framework, Two Frame Model (TFM), is first proposed to model the dynamic interaction between the physical process and the decision-making process. Two important issues, consistency and competing processes, are raised. Consistency between the physical and logic frames makes a TFM-based system work properly. Loss of consistency refers to the failure mode that the logic frame does not accurately reflect the state of the controlled processes. Once such failure occurs, hazards may arise. Among potential hazards, the competing effect between the controller and the controlled process is the most severe one, which may jeopardize a defense-in-depth design. When the logic and physical frames are inconsistent, conventional safety analysis techniques are inadequate. We propose Frame-based Fault Tree; Analysis (FFTA) and Frame-based Event Tree Analysis (FETA) under TFM to deduce the context for decision errors and to separately generate the evolution of the logical frame as opposed to that of the physical frame. This multi-dimensional analysis approach, different from the conventional correctness-centred approach, provides a panoramic view in scenario generation. Case studies using the proposed techniques are also given to demonstrate their usage and feasibility

  15. Validating evidence based decision making in health care

    DEFF Research Database (Denmark)

    Nüssler, Emil Karl; Eskildsen, Jacob Kjær; Håkonsson, Dorthe Døjbak

    Surgeons who perform prolapse surgeries face the dilemma of choosing to use mesh, with its assumed benefits, and the risks associated with mesh. In this paper, we examine whether decisions to use mesh is evidence based. Based on data of 30,398 patients from the Swedish National Quality Register o...... are highly influenced by the geographical placement of surgeons. Therfore, decisions to use mesh are boundedly rationality, rather than rational.......Surgeons who perform prolapse surgeries face the dilemma of choosing to use mesh, with its assumed benefits, and the risks associated with mesh. In this paper, we examine whether decisions to use mesh is evidence based. Based on data of 30,398 patients from the Swedish National Quality Register...... of Gynecological Surgery we examine factors related to decisions to use mesh. Our results indicate that decisions to use mesh are not evidence based, and cannot be explained neither by FDA safety communications, nor by medical conditions usually assumed to predict its usage. Instead, decisions to use mesh...

  16. 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

  17. 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.

  18. The boundaries of instance-based learning theory for explaining decisions from experience.

    Science.gov (United States)

    Gonzalez, Cleotilde

    2013-01-01

    Most demonstrations of how people make decisions in risky situations rely on decisions from description, where outcomes and their probabilities are explicitly stated. But recently, more attention has been given to decisions from experience where people discover these outcomes and probabilities through exploration. More importantly, risky behavior depends on how decisions are made (from description or experience), and although prospect theory explains decisions from description, a comprehensive model of decisions from experience is yet to be found. Instance-based learning theory (IBLT) explains how decisions are made from experience through interactions with dynamic environments (Gonzalez et al., 2003). The theory has shown robust explanations of behavior across multiple tasks and contexts, but it is becoming unclear what the theory is able to explain and what it does not. The goal of this chapter is to start addressing this problem. I will introduce IBLT and a recent cognitive model based on this theory: the IBL model of repeated binary choice; then I will discuss the phenomena that the IBL model explains and those that the model does not. The argument is for the theory's robustness but also for clarity in terms of concrete effects that the theory can or cannot account for. Copyright © 2013 Elsevier B.V. All rights reserved.

  19. Improving societal acceptance of rad waste management policy decisions: an approach based on complex intelligence

    International Nuclear Information System (INIS)

    Rao, Suman

    2008-01-01

    In today's context elaborate public participation exercises are conducted around the world to elicit and incorporate societal risk perceptions into nuclear policy Decision-Making. However, on many occasions, such as in the case of rad waste management, the society remains unconvinced about these decisions. This naturally leads to the questions: are techniques for incorporating societal risk perceptions into the rad waste policy decision making processes sufficiently mature? How could societal risk perceptions and legal normative principles be better integrated in order to render the decisions more equitable and convincing to society? Based on guidance from socio-psychological research this paper postulates that a critical factor for gaining/improving societal acceptance is the quality and adequacy of criteria for option evaluation that are used in the policy decision making. After surveying three rad waste public participation cases, the paper identifies key lacunae in criteria abstraction processes as currently practiced. A new policy decision support model CIRDA: Complex Intelligent Risk Discourse Abstraction model that is based on the heuristic of Risk-Risk Analysis is proposed to overcome these lacunae. CIRDA's functionality of rad waste policy decision making is modelled as a policy decision-making Abstract Intelligent Agent and the agent program/abstraction mappings are presented. CIRDA is then applied to a live (U.K.) rad waste management case and the advantages of this method as compared to the Value Tree Method as practiced in the GB case are demonstrated. (author)

  20. Computing with Words in Decision support Systems: An overview on Models and Applications

    Directory of Open Access Journals (Sweden)

    Luis Martinez

    2010-10-01

    Full Text Available Decision making is inherent to mankind, as human beings daily face situations in which they should choose among different alternatives by means of reasoning and mental processes. Many of these decision problems are under uncertain environments with vague and imprecise information. This type of information is usually modelled by linguistic information because of the common use of language by the experts involved in the given decision situations, originating linguistic decision making. The use of linguistic information in decision making demands processes of Computing with Words to solve the related decision problems. Different methodologies and approaches have been proposed to accomplish such processes in an accurate and interpretable way. The good performance of linguistic computing dealing with uncertainty has caused a spread use of it in different types of decision based applications. This paper overviews the more significant and extended linguistic computing models due to its key role in linguistic decision making and a wide range of the most recent applications of linguistic decision support models.

  1. 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

  2. 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

  3. Assessing testamentary and decision-making capacity: Approaches and models.

    Science.gov (United States)

    Purser, Kelly; Rosenfeld, Tuly

    2015-09-01

    The need for better and more accurate assessments of testamentary and decision-making capacity grows as Australian society ages and incidences of mentally disabling conditions increase. Capacity is a legal determination, but one on which medical opinion is increasingly being sought. The difficulties inherent within capacity assessments are exacerbated by the ad hoc approaches adopted by legal and medical professionals based on individual knowledge and skill, as well as the numerous assessment paradigms that exist. This can negatively affect the quality of assessments, and results in confusion as to the best way to assess capacity. This article begins by assessing the nature of capacity. The most common general assessment models used in Australia are then discussed, as are the practical challenges associated with capacity assessment. The article concludes by suggesting a way forward to satisfactorily assess legal capacity given the significant ramifications of getting it wrong.

  4. 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...

  5. Qualitative modeling of the decision-making process using electrooculography.

    Science.gov (United States)

    Zargari Marandi, Ramtin; Sabzpoushan, S H

    2015-12-01

    A novel method based on electrooculography (EOG) has been introduced in this work to study the decision-making process. An experiment was designed and implemented wherein subjects were asked to choose between two items from the same category that were presented within a limited time. The EOG and voice signals of the subjects were recorded during the experiment. A calibration task was performed to map the EOG signals to their corresponding gaze positions on the screen by using an artificial neural network. To analyze the data, 16 parameters were extracted from the response time and EOG signals of the subjects. Evaluation and comparison of the parameters, together with subjects' choices, revealed functional information. On the basis of this information, subjects switched their eye gazes between items about three times on average. We also found, according to statistical hypothesis testing-that is, a t test, t(10) = 71.62, SE = 1.25, p < .0001-that the correspondence rate of a subjects' gaze at the moment of selection with the selected item was significant. Ultimately, on the basis of these results, we propose a qualitative choice model for the decision-making task.

  6. A multistage decision support framework to guide tree species management under climate change via habitat suitability and colonization models, and a knowledge-based scoring system

    Science.gov (United States)

    Anantha M. Prasad; Louis R. Iverson; Stephen N. Matthews; Matthew P. Peters

    2016-01-01

    Context. No single model can capture the complex species range dynamics under changing climates--hence the need for a combination approach that addresses management concerns. Objective. A multistage approach is illustrated to manage forested landscapes under climate change. We combine a tree species habitat model--DISTRIB II, a species colonization model--SHIFT, and...

  7. Water distribution network segmentation based on group multi-criteria decision approach

    Directory of Open Access Journals (Sweden)

    Marcele Elisa Fontana

    Full Text Available Abstract A correct Network Segmentation (NS is necessary to perform proper maintenance activities in water distribution networks (WDN. For this, usually, isolation valves are allocating near the ends of pipes, blocking the flow of water. However, the allocation of valves increases costs substantially for the water supply companies. Additionally, other criteria should be taking account to analyze the benefits of the valves allocation. Thus, the problem is to define an alternative of NS which shows a good compromise in these different criteria. Moreover, usually, in this type of decision, there is more than one decision-maker involved, who can have different viewpoints. Therefore, this paper presents a model to support group decision-making, based on a multi-criteria method, in order to support the decision making procedure in the NS problem. As result, the model is able to find a solution that shows the best compromise regarding the benefits, costs, and the decision makers' preferences.

  8. Bases for Decisions on Final Disposal in Finland

    International Nuclear Information System (INIS)

    Avolahti, Jaana

    2001-01-01

    The disposal of the spent nuclear fuel is approaching one of the significant milestones in Finland. Social debate on the nuclear waste management is going on aiming at a decision of principle on future directions of spent fuel management. The research so far has required no political decision. This current situation is preceded by preparations for two decades carried out by Posiva Oy who took over the programme managed earlier by Teollisuuden Voinia Oy, one of the country's nuclear power companies. The preparations comprise site investigations, technical concept development, research into long-term safety and an environmental impact assessment. The work carried out by Posiva is under regular assessment by the authorities. Research programmes are drawn up every year and reports are published for open review. The preparations in the next years to come aim at starting the construction of the repository in 2010 and the disposal operations are planned to be started in 2020. Various stakeholders in Finland are involved in the decision-making process on the disposal of spent nuclear fuel. The process started when Posiva as an implementer applied for the Government's Decision in Principle in 1999. The Government made a favourable decision in December 2000 on the basis of different considerations. Among the important bases were the preceding favourable decisions made by the proposed siting municipality and the regulatory authority for radiation safety. At the moment the members of the Parliament are discussing the principles of the disposal in order to be able to vote on the Government's decision in the springtime. This paper discusses similarities and differences between the decisions made so far as regards the deep repository. The objective is to present the significance of the decisions from the point of view of an implementer of the repository. The Decision in Principle does not give any consent to start constructing the repository. Licenses for construction and

  9. Tactical decision games - developing scenario-based training for decision-making in distributed teams

    NARCIS (Netherlands)

    Lauche, K.; Crichton, M.; Bayerl, P.S.

    2009-01-01

    Team training should reflect the increasing complexity of decision-making environments. Guidelines for scenario-based training were adopted for a distributed setting and tested in a pilot training session with a distributed team in the offshore oil industry. Participants valued the scenario as

  10. 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...

  11. EEG feature selection method based on decision tree.

    Science.gov (United States)

    Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

    2015-01-01

    This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

  12. 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.

  13. 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

  14. CLIPS based decision support system for water distribution networks

    Directory of Open Access Journals (Sweden)

    K. Sandeep

    2011-10-01

    Full Text Available The difficulty in knowledge representation of a water distribution network (WDN problem has contributed to the limited use of artificial intelligence (AI based expert systems (ES in the management of these networks. This paper presents a design of a Decision Support System (DSS that facilitates "on-demand'' knowledge generation by utilizing results of simulation runs of a suitably calibrated and validated hydraulic model of an existing aged WDN corresponding to emergent or even hypothetical but likely scenarios. The DSS augments the capability of a conventional expert system by integrating together the hydraulic modelling features with heuristics based knowledge of experts under a common, rules based, expert shell named CLIPS (C Language Integrated Production System. In contrast to previous ES, the knowledge base of the DSS has been designed to be dynamic by superimposing CLIPS on Structured Query Language (SQL. The proposed ES has an inbuilt calibration module that enables calibration of an existing (aged WDN for the unknown, and unobservable, Hazen-Williams C-values. In addition, the daily run and simulation modules of the proposed ES further enable the CLIPS inference engine to evaluate the network performance for any emergent or suggested test scenarios. An additional feature of the proposed design is that the DSS integrates computational platforms such as MATLAB, open source Geographical Information System (GIS, and a relational database management system (RDBMS working under the umbrella of the Microsoft Visual Studio based common user interface. The paper also discusses implementation of the proposed framework on a case study and clearly demonstrates the utility of the application as an able aide for effective management of the study network.

  15. The Exploratory Modeling Workbench : An open source toolkit for exploratory modeling, scenario discovery, and (multi-objective) robust decision making

    NARCIS (Netherlands)

    Kwakkel, J.H.

    2017-01-01

    There is a growing interest in model-based decision support under deep uncertainty, reflected in a variety of approaches being put forward in the literature. A key idea shared among these is the use of models for exploratory rather than predictive purposes. Exploratory modeling aims at exploring

  16. Development of a clinical decision model for thyroid nodules

    Directory of Open Access Journals (Sweden)

    Eberhardt John

    2009-08-01

    Full Text Available Abstract Background Thyroid nodules represent a common problem brought to medical attention. Four to seven percent of the United States adult population (10–18 million people has a palpable thyroid nodule, however the majority (>95% of thyroid nodules are benign. While, fine needle aspiration remains the most cost effective and accurate diagnostic tool for thyroid nodules in current practice, over 20% of patients undergoing FNA of a thyroid nodule have indeterminate cytology (follicular neoplasm with associated malignancy risk prevalence of 20–30%. These patients require thyroid lobectomy/isthmusectomy purely for the purpose of attaining a definitive diagnosis. Given that the majority (70–80% of these patients have benign surgical pathology, thyroidectomy in these patients is conducted principally with diagnostic intent. Clinical models predictive of malignancy risk are needed to support treatment decisions in patients with thyroid nodules in order to reduce morbidity associated with unnecessary diagnostic surgery. Methods Data were analyzed from a completed prospective cohort trial conducted over a 4-year period involving 216 patients with thyroid nodules undergoing ultrasound (US, electrical impedance scanning (EIS and fine needle aspiration cytology (FNA prior to thyroidectomy. A Bayesian model was designed to predict malignancy in thyroid nodules based on multivariate dependence relationships between independent covariates. Ten-fold cross-validation was performed to estimate classifier error wherein the data set was randomized into ten separate and unique train and test sets consisting of a training set (90% of records and a test set (10% of records. A receiver-operating-characteristics (ROC curve of these predictions and area under the curve (AUC were calculated to determine model robustness for predicting malignancy in thyroid nodules. Results Thyroid nodule size, FNA cytology, US and EIS characteristics were highly predictive of

  17. A new fit-for-purpose model testing framework: Decision Crash Tests

    Science.gov (United States)

    Tolson, Bryan; Craig, James

    2016-04-01

    Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model