Combining the Generic Entity-Attribute-Value Model and Terminological Models into a Common Ontology to Enable Data Integration and Decision Support.

Science.gov (United States)

Bouaud, Jacques; Guézennec, Gilles; Séroussi, Brigitte

2018-01-01

The integration of clinical information models and termino-ontological models into a unique ontological framework is highly desirable for it facilitates data integration and management using the same formal mechanisms for both data concepts and information model components. This is particularly true for knowledge-based decision support tools that aim to take advantage of all facets of semantic web technologies in merging ontological reasoning, concept classification, and rule-based inferences. We present an ontology template that combines generic data model components with (parts of) existing termino-ontological resources. The approach is developed for the guideline-based decision support module on breast cancer management within the DESIREE European project. The approach is based on the entity attribute value model and could be extended to other domains.

Traits and states: Integrating personality and affect into a model of criminal decision making

NARCIS (Netherlands)

van Gelder, J.L.; de Vries, R.E.

2012-01-01

We propose and test a model of criminal decision making that integrates the individual differences perspective with research and theorizing on proximal factors. The individual differences perspective is operationalized using the recent HEXACO personality structure. This structure incorporates the

Continuous track paths reveal additive evidence integration in multistep decision making.

Science.gov (United States)

Buc Calderon, Cristian; Dewulf, Myrtille; Gevers, Wim; Verguts, Tom

2017-10-03

Multistep decision making pervades daily life, but its underlying mechanisms remain obscure. We distinguish four prominent models of multistep decision making, namely serial stage, hierarchical evidence integration, hierarchical leaky competing accumulation (HLCA), and probabilistic evidence integration (PEI). To empirically disentangle these models, we design a two-step reward-based decision paradigm and implement it in a reaching task experiment. In a first step, participants choose between two potential upcoming choices, each associated with two rewards. In a second step, participants choose between the two rewards selected in the first step. Strikingly, as predicted by the HLCA and PEI models, the first-step decision dynamics were initially biased toward the choice representing the highest sum/mean before being redirected toward the choice representing the maximal reward (i.e., initial dip). Only HLCA and PEI predicted this initial dip, suggesting that first-step decision dynamics depend on additive integration of competing second-step choices. Our data suggest that potential future outcomes are progressively unraveled during multistep decision making.

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...

"An integrative formal model of motivation and decision making: The MGPM*": Correction to Ballard et al. (2016).

Science.gov (United States)

2017-02-01

Reports an error in "An integrative formal model of motivation and decision making: The MGPM*" by Timothy Ballard, Gillian Yeo, Shayne Loft, Jeffrey B. Vancouver and Andrew Neal ( Journal of Applied Psychology , 2016[Sep], Vol 101[9], 1240-1265). Equation A3 contained an error. This correct equation is provided in the erratum. (The following abstract of the original article appeared in record 2016-28692-001.) We develop and test an integrative formal model of motivation and decision making. The model, referred to as the extended multiple-goal pursuit model (MGPM*), is an integration of the multiple-goal pursuit model (Vancouver, Weinhardt, & Schmidt, 2010) and decision field theory (Busemeyer & Townsend, 1993). Simulations of the model generated predictions regarding the effects of goal type (approach vs. avoidance), risk, and time sensitivity on prioritization. We tested these predictions in an experiment in which participants pursued different combinations of approach and avoidance goals under different levels of risk. The empirical results were consistent with the predictions of the MGPM*. Specifically, participants pursuing 1 approach and 1 avoidance goal shifted priority from the approach to the avoidance goal over time. Among participants pursuing 2 approach goals, those with low time sensitivity prioritized the goal with the larger discrepancy, whereas those with high time sensitivity prioritized the goal with the smaller discrepancy. Participants pursuing 2 avoidance goals generally prioritized the goal with the smaller discrepancy. Finally, all of these effects became weaker as the level of risk increased. We used quantitative model comparison to show that the MGPM* explained the data better than the original multiple-goal pursuit model, and that the major extensions from the original model were justified. The MGPM* represents a step forward in the development of a general theory of decision making during multiple-goal pursuit. (PsycINFO Database Record (c

Decision Making in Rangelands: An Integrated Modeling Approach to Resilience and Change

Science.gov (United States)

Galvin, K. A.; Ojima, D. S.; Boone, R. B.

2007-12-01

Rangelands comprise approximately 25% of the earth's surface and these landscapes support more than 20 million people and most of the world's charismatic megafauna. Most of the people who live in these regions of the world herd domestic livestock and some do limited cultivation so they are dependent directly on the environment for their livelihoods. But change is rapidly changing the environments upon which these people depend through such factors as population pressures, land use and land tenure changes, climate variability, and policy changes which fragment their resources and thus their ability to earn a living. How can we understand change in this linked human-environment system? The study of complex biophysical and human systems can be greatly assisted by appropriate simulation models that integrate what is known about ecological and human decision-making processes. We have developed an integrated modeling system for Kajiado, Kenya where land use management decisions have implications for economics and the ecosystem. In this paper we look at how land use decisions, that is, livestock movement patterns have implications for societal economics and ecosystem services. Research that focuses on local behavior is important because it is at that level where fundamental decisions are made regarding events like extreme climate and changes such as land tenure policy and it is here where resilience is manifested. The notion that broad recommendation domains can be identified for a broad set of people and large regions coping with change is becoming increasingly hard to trust given the spatial and temporal heterogeneity of the systems we are looking at, and the complexity of the world we now live in. Why is this important? The only way the research community is going to make great progress in attaining objectives that do confer resilience (on social and ecological systems) is through much better targeting ability, a large part of which seem to be intimately entwined with

An integrated model of decision-making in health contexts: the role of science education in health education

Science.gov (United States)

Arnold, Julia C.

2018-03-01

Health education is to foster health literacy, informed decision-making and to promote health behaviour. To date, there are several models that seek to explain health behaviour (e.g. the Theory of Planned Behaviour or the Health Belief Model). These models include motivational factors (expectancies and values) that play a role in decision-making in health contexts. In this theoretical paper, it is argued that none of these models makes consequent use of expectancy-value pairs. It is further argued that in order to make these models fruitful for science education and for informed decision-making, models should systematically incorporate knowledge as part of the decision-making process. To fill this gap, this theoretical paper introduces The Integrated Model of Decision-Making in Health Contexts. This model includes three types of knowledge (system health knowledge, action-related health knowledge and effectiveness health knowledge) as influencing factors for motivational factors (perceived health threat, attitude towards health action, attitude towards health outcome and subjective norm) that are formed of expectancy-value pairs and lead to decisions. The model's potential for health education in science education as well as research implications is discussed.

Comparing the Applicability of Commonly Used Hydrological Ecosystem Services Models for Integrated Decision-Support

Directory of Open Access Journals (Sweden)

Anna Lüke

2018-01-01

Full Text Available Different simulation models are used in science and practice in order to incorporate hydrological ecosystem services in decision-making processes. This contribution compares three simulation models, the Soil and Water Assessment Tool, a traditional hydrological model and two ecosystem services models, the Integrated Valuation of Ecosystem Services and Trade-offs model and the Resource Investment Optimization System model. The three models are compared on a theoretical and conceptual basis as well in a comparative case study application. The application of the models to a study area in Nicaragua reveals that a practical benefit to apply these models for different questions in decision-making generally exists. However, modelling of hydrological ecosystem services is associated with a high application effort and requires input data that may not always be available. The degree of detail in temporal and spatial variability in ecosystem service provision is higher when using the Soil and Water Assessment Tool compared to the two ecosystem service models. In contrast, the ecosystem service models have lower requirements on input data and process knowledge. A relationship between service provision and beneficiaries is readily produced and can be visualized as a model output. The visualization is especially useful for a practical decision-making context.

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.

Integrated decision making for the optimal bioethanol supply chain

International Nuclear Information System (INIS)

Corsano, Gabriela; Fumero, Yanina; Montagna, Jorge M.

2014-01-01

Highlights: • Optimal allocation, design and production planning of integrated ethanol plants is considered. • Mixed Integer Programming model is presented for solving the integration problem. • Different tradeoffs can be assessed and analyzed. • The modeling framework represents an useful tool for guiding decision making. - Abstract: Bioethanol production poses different challenges that require an integrated approach. Usually previous works have focused on specific perspectives of the global problem. On the contrary, bioethanol, in particular, and biofuels, in general, requires an integrated decision making framework that takes into account the needs and concerns of the different members involved in its supply chain. In this work, a Mixed Integer Linear Programming (MILP) model for the optimal allocation, design and production planning of integrated ethanol/yeast plants is considered. The proposed formulation addresses the relations between different aspects of the bioethanol supply chain and provides an efficient tool to assess the global operation of the supply chain taking into account different points of view. The model proposed in this work simultaneously determines the structure of a three-echelon supply chain (raw material sites, production facilities and customer zones), the design of each installed plant and operational considerations through production campaigns. Yeast production is considered in order to reduce the negative environmental impact caused by bioethanol residues. Several cases are presented in order to assess the approach capabilities and to evaluate the tradeoffs among all the decisions

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.

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

Integrated assessment of the global warming problem: A decision-analytical approach

International Nuclear Information System (INIS)

Van Lenthe, J.; Hendrickx, L.; Vlek, C.A.J.

1994-12-01

The multi-disciplinary character of the global warming problem asks for an integrated assessment approach for ordering and combining the various physical, ecological, economical, and sociological results. The Netherlands initiated their own National Research Program (NRP) on Global Air Pollution and Climate Change (NRP). The first phase (NRP-1) identified the integration theme as one of five central research themes. The second phase (NRP-2) shows a growing concern for integrated assessment issues. The current two-year research project 'Characterizing the risks: a comparative analysis of the risks of global warming and of relevant policy options, which started in September 1993, comes under the integrated assessment part of the Dutch NRP. The first part of the interim report describes the search for an integrated assessment methodology. It starts with emphasizing the need for integrated assessment at a relatively high level of aggregation and from a policy point of view. The conclusion will be that a decision-analytical approach might fit the purpose of a policy-oriented integrated modeling of the global warming problem. The discussion proceeds with an account on decision analysis and its explicit incorporation and analysis of uncertainty. Then influence diagrams, a relatively recent development in decision analysis, are introduced as a useful decision-analytical approach for integrated assessment. Finally, a software environment for creating and analyzing complex influence diagram models is discussed. The second part of the interim report provides a first, provisional integrated modeling of the global warming problem, emphasizing on the illustration of the decision-analytical approach. Major problem elements are identified and an initial problem structure is developed. The problem structure is described in terms of hierarchical influence diagrams. At some places the qualitative structure is filled with quantitative data

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.

An Integrated Modeling and Data Management Strategy for Cellulosic Biomass Production Decisions

Energy Technology Data Exchange (ETDEWEB)

David J. Muth Jr.; K. Mark Bryden; Joshua B. Koch

2012-07-01

Emerging cellulosic bioenergy markets can provide land managers with additional options for crop production decisions. Integrating dedicated bioenergy crops such as perennial grasses and short rotation woody species within the agricultural landscape can have positive impacts on several environmental processes including increased soil organic matter in degraded soils, reduced sediment loading in watersheds, lower green house gas (GHG) fluxes, and reduced nutrient loading in watersheds. Implementing this type of diverse bioenergy production system in a way that maximizes potential environmental benefits requires a dynamic integrated modeling and data management strategy. This paper presents a strategy for designing diverse bioenergy cropping systems within the existing row crop production landscape in the midwestern United States. The integrated model developed quantifies a wide range environmental processes including soil erosion from wind and water, soil organic matter changes, and soil GHG fluxes within a geospatial data management framework. This framework assembles and formats information from multiple spatial and temporal scales. The data assembled includes yield and productivity data from harvesting equipment at the 1m scale, surface topography data from LiDAR mapping at the less than 1m scale, soil data from US soil survey databases at the 10m to 100m scale, and climate data at the county scale. These models and data tools are assembled into an integrated computational environment that is used to determine sustainable removal rates for agricultural residues for bioenergy production at the sub-field scale under a wide range of land management practices. Using this integrated model, innovative management practices including cover cropping are then introduced and evaluated for their impact on bioenergy production and important environmental processes. The impacts of introducing dedicated energy crops onto high-risk landscape positions currently being manage in

A Practical Review of Integrated Urban Water Models: Applications as Decision Support Tools and Beyond

Science.gov (United States)

Mosleh, L.; Negahban-Azar, M.

2017-12-01

The integrated urban water management has become a necessity due to the high rate of urbanization, water scarcity, and climate variability. Climate and demographic changes, shifting the social attitude toward the water usage, and insufficiencies in system resilience increase the pressure on the water resources. Alongside with the water management, modeling urban water systems have progressed from traditional view to comprise alternatives such as decentralized water and wastewater systems, fit-for-purpose practice, graywater/rainwater reuse, and green infrastructure. While there are review papers available focusing on the technical part of the models, they seem to be more beneficial for model developers. Some of the models analyze a number of scenarios considering factors such as climate change and demography and their future impacts. However, others only focus on quality and quantity of water in a supply/demand approach. For example, optimizing the size of water or waste water store, characterizing the supply and quantity of urban stormwater and waste water, and link source of water to demand. A detailed and practical comparison of such models has become a necessity for the practitioner and policy makers. This research compares more than 7 most commonly used integrated urban water cycle models and critically reviews their capabilities, input requirements, output and their applications. The output of such detailed comparison will help the policy makers for the decision process in the built environment to compare and choose the best models that meet their goals. The results of this research show that we need a transition from developing/using integrated water cycle models to integrated system models which incorporate urban water infrastructures and ecological and economic factors. Such models can help decision makers to reflect other important criteria but with the focus on urban water management. The research also showed that there is a need in exploring

Spiking Phineas Gage: a neurocomputational theory of cognitive-affective integration in decision making.

Science.gov (United States)

Wagar, Brandon M; Thagard, Paul

2004-01-01

The authors present a neurological theory of how cognitive information and emotional information are integrated in the nucleus accumbens during effective decision making. They describe how the nucleus accumbens acts as a gateway to integrate cognitive information from the ventromedial prefrontal cortex and the hippocampus with emotional information from the amygdala. The authors have modeled this integration by a network of spiking artificial neurons organized into separate areas and used this computational model to simulate 2 kinds of cognitive-affective integration. The model simulates successful performance by people with normal cognitive-affective integration. The model also simulates the historical case of Phineas Gage as well as subsequent patients whose ability to make decisions became impeded by damage to the ventromedial prefrontal cortex.

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

Decision support for integrated water-energy planning.

Energy Technology Data Exchange (ETDEWEB)

Tidwell, Vincent Carroll; Malczynski, Leonard A.; Kobos, Peter Holmes; Castillo, Cesar; Hart, William Eugene; Klise, Geoffrey T.

2009-10-01

Currently, electrical power generation uses about 140 billion gallons of water per day accounting for over 39% of all freshwater withdrawals thus competing with irrigated agriculture as the leading user of water. Coupled to this water use is the required pumping, conveyance, treatment, storage and distribution of the water which requires on average 3% of all electric power generated. While water and energy use are tightly coupled, planning and management of these fundamental resources are rarely treated in an integrated fashion. Toward this need, a decision support framework has been developed that targets the shared needs of energy and water producers, resource managers, regulators, and decision makers at the federal, state and local levels. The framework integrates analysis and optimization capabilities to identify trade-offs, and 'best' alternatives among a broad list of energy/water options and objectives. The decision support framework is formulated in a modular architecture, facilitating tailored analyses over different geographical regions and scales (e.g., national, state, county, watershed, NERC region). An interactive interface allows direct control of the model and access to real-time results displayed as charts, graphs and maps. Ultimately, this open and interactive modeling framework provides a tool for evaluating competing policy and technical options relevant to the energy-water nexus.

Analysis of decision fusion algorithms in handling uncertainties for integrated health monitoring systems

Science.gov (United States)

Zein-Sabatto, Saleh; Mikhail, Maged; Bodruzzaman, Mohammad; DeSimio, Martin; Derriso, Mark; Behbahani, Alireza

2012-06-01

It has been widely accepted that data fusion and information fusion methods can improve the accuracy and robustness of decision-making in structural health monitoring systems. It is arguably true nonetheless, that decision-level is equally beneficial when applied to integrated health monitoring systems. Several decisions at low-levels of abstraction may be produced by different decision-makers; however, decision-level fusion is required at the final stage of the process to provide accurate assessment about the health of the monitored system as a whole. An example of such integrated systems with complex decision-making scenarios is the integrated health monitoring of aircraft. Thorough understanding of the characteristics of the decision-fusion methodologies is a crucial step for successful implementation of such decision-fusion systems. In this paper, we have presented the major information fusion methodologies reported in the literature, i.e., probabilistic, evidential, and artificial intelligent based methods. The theoretical basis and characteristics of these methodologies are explained and their performances are analyzed. Second, candidate methods from the above fusion methodologies, i.e., Bayesian, Dempster-Shafer, and fuzzy logic algorithms are selected and their applications are extended to decisions fusion. Finally, fusion algorithms are developed based on the selected fusion methods and their performance are tested on decisions generated from synthetic data and from experimental data. Also in this paper, a modeling methodology, i.e. cloud model, for generating synthetic decisions is presented and used. Using the cloud model, both types of uncertainties; randomness and fuzziness, involved in real decision-making are modeled. Synthetic decisions are generated with an unbiased process and varying interaction complexities among decisions to provide for fair performance comparison of the selected decision-fusion algorithms. For verification purposes

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)

Integrated assessment of the global warming problem. A decision-analytical approach

International Nuclear Information System (INIS)

Van Lenthe, J.; Hendrickx, L.; Vlek, C.A.J.

1995-01-01

The project on the title subject aims at developing a policy-oriented methodology for the integrated assessment of the global warming problem. Decision analysis in general and influence diagrams in particular appear to constitute an appropriate integrated assessment methodology. The influence-diagram approach is illustrated at a preliminary integrated modeling of the global warming problem. In next stages of the research, attention will be shifted from the methodology of integrated assessment to the contents of integrated models. 4 figs., 5 refs

An integrated ethical approach to bioethical decision-making: A proposed model for ministers

Directory of Open Access Journals (Sweden)

Magdalena C. de Lange

2012-10-01

Full Text Available This article outlined a model for guidance in ‘doing’ bioethics in a Reformed context. The proposed model suggested that in order to arrive at responsible ethical decisions, one must refer to both contextual elements and theory. The theoretical grounding for this model was based on the integration of a deontological and virtue ethics approach, arguing that virtue enables persons to know and desire the right moral ends and motivates them to carry out appropriate action toward achieving these ends. An integrative model opens up the possibility whereby bioethics as a systematic tool provides the individual decision-maker with the critical-reflective skills and justification for the ultimate choice that is lacking in the general decision-making processes. This could lead to clearer thinking and increased confidence in the justification of decisions within the Reformed tradition. The proposed hermeneutical perspective on ethical decision-making represents a shift in views about the nature of knowledge and the process of how we come to know. The key to this hermeneutical approach is to acknowledge the dialectic between the universal and the subjectivity of human relations. Working in specific religious communities, one needs to take cognisance of the fact that knowledge is situated in the context of human relationships in which the interpreter participates when articulating the meaning of bioethical experiences. Another aspect that is anticipated lies in the realisation that people struggling with bioethical dilemmas should not be viewed as isolated individuals, but as members of a broader faith community. ‘n Geïntegreerde etiese benadering tot bioetiese besluitneming: Voorgestelde model vir predikante. Hierdie artikel het ‘n model geskets wat moontlike riglyne aantoon vir die  beoefening  van  bioetiek  binne  ‘n  Gereformeerde  konteks.  Die  voorgestelde  model argumenteer dat verwysing na beide kontekstuele elemente en teorie

An integrated modeling approach to support management decisions of coupled groundwater-agricultural systems under multiple uncertainties

Science.gov (United States)

Hagos Subagadis, Yohannes; Schütze, Niels; Grundmann, Jens

2015-04-01

The planning and implementation of effective water resources management strategies need an assessment of multiple (physical, environmental, and socio-economic) issues, and often requires new research in which knowledge of diverse disciplines are combined in a unified methodological and operational frameworks. Such integrative research to link different knowledge domains faces several practical challenges. Such complexities are further compounded by multiple actors frequently with conflicting interests and multiple uncertainties about the consequences of potential management decisions. A fuzzy-stochastic multiple criteria decision analysis tool was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management. It integrated physical process-based models, fuzzy logic, expert involvement and stochastic simulation within a general framework. Subsequently, the proposed new approach is applied to a water-scarce coastal arid region water management problem in northern Oman, where saltwater intrusion into a coastal aquifer due to excessive groundwater extraction for irrigated agriculture has affected the aquifer sustainability, endangering associated socio-economic conditions as well as traditional social structure. Results from the developed method have provided key decision alternatives which can serve as a platform for negotiation and further exploration. In addition, this approach has enabled to systematically quantify both probabilistic and fuzzy uncertainties associated with the decision problem. Sensitivity analysis applied within the developed tool has shown that the decision makers' risk aversion and risk taking attitude may yield in different ranking of decision alternatives. The developed approach can be applied to address the complexities and uncertainties inherent in water resources systems to support management decisions, while serving as a platform for stakeholder participation.

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.

The Dilution Effect and Information Integration in Perceptual Decision Making.

Science.gov (United States)

Hotaling, Jared M; Cohen, Andrew L; Shiffrin, Richard M; Busemeyer, Jerome R

2015-01-01

In cognitive science there is a seeming paradox: On the one hand, studies of human judgment and decision making have repeatedly shown that people systematically violate optimal behavior when integrating information from multiple sources. On the other hand, optimal models, often Bayesian, have been successful at accounting for information integration in fields such as categorization, memory, and perception. This apparent conflict could be due, in part, to different materials and designs that lead to differences in the nature of processing. Stimuli that require controlled integration of information, such as the quantitative or linguistic information (commonly found in judgment studies), may lead to suboptimal performance. In contrast, perceptual stimuli may lend themselves to automatic processing, resulting in integration that is closer to optimal. We tested this hypothesis with an experiment in which participants categorized faces based on resemblance to a family patriarch. The amount of evidence contained in the top and bottom halves of each test face was independently manipulated. These data allow us to investigate a canonical example of sub-optimal information integration from the judgment and decision making literature, the dilution effect. Splitting the top and bottom halves of a face, a manipulation meant to encourage controlled integration of information, produced farther from optimal behavior and larger dilution effects. The Multi-component Information Accumulation model, a hybrid optimal/averaging model of information integration, successfully accounts for key accuracy, response time, and dilution effects.

The Dilution Effect and Information Integration in Perceptual Decision Making.

Directory of Open Access Journals (Sweden)

Jared M Hotaling

Full Text Available In cognitive science there is a seeming paradox: On the one hand, studies of human judgment and decision making have repeatedly shown that people systematically violate optimal behavior when integrating information from multiple sources. On the other hand, optimal models, often Bayesian, have been successful at accounting for information integration in fields such as categorization, memory, and perception. This apparent conflict could be due, in part, to different materials and designs that lead to differences in the nature of processing. Stimuli that require controlled integration of information, such as the quantitative or linguistic information (commonly found in judgment studies, may lead to suboptimal performance. In contrast, perceptual stimuli may lend themselves to automatic processing, resulting in integration that is closer to optimal. We tested this hypothesis with an experiment in which participants categorized faces based on resemblance to a family patriarch. The amount of evidence contained in the top and bottom halves of each test face was independently manipulated. These data allow us to investigate a canonical example of sub-optimal information integration from the judgment and decision making literature, the dilution effect. Splitting the top and bottom halves of a face, a manipulation meant to encourage controlled integration of information, produced farther from optimal behavior and larger dilution effects. The Multi-component Information Accumulation model, a hybrid optimal/averaging model of information integration, successfully accounts for key accuracy, response time, and dilution effects.

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.

Mental model mapping as a new tool to analyse the use of information in decision-making in integrated water management

Science.gov (United States)

Kolkman, M. J.; Kok, M.; van der Veen, A.

The solution of complex, unstructured problems is faced with policy controversy and dispute, unused and misused knowledge, project delay and failure, and decline of public trust in governmental decisions. Mental model mapping (also called concept mapping) is a technique to analyse these difficulties on a fundamental cognitive level, which can reveal experiences, perceptions, assumptions, knowledge and subjective beliefs of stakeholders, experts and other actors, and can stimulate communication and learning. This article presents the theoretical framework from which the use of mental model mapping techniques to analyse this type of problems emerges as a promising technique. The framework consists of the problem solving or policy design cycle, the knowledge production or modelling cycle, and the (computer) model as interface between the cycles. Literature attributes difficulties in the decision-making process to communication gaps between decision makers, stakeholders and scientists, and to the construction of knowledge within different paradigm groups that leads to different interpretation of the problem situation. Analysis of the decision-making process literature indicates that choices, which are made in all steps of the problem solving cycle, are based on an individual decision maker’s frame of perception. This frame, in turn, depends on the mental model residing in the mind of the individual. Thus we identify three levels of awareness on which the decision process can be analysed. This research focuses on the third level. Mental models can be elicited using mapping techniques. In this way, analysing an individual’s mental model can shed light on decision-making problems. The steps of the knowledge production cycle are, in the same manner, ultimately driven by the mental models of the scientist in a specific discipline. Remnants of this mental model can be found in the resulting computer model. The characteristics of unstructured problems (complexity

The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Human Space Flight Missions

Science.gov (United States)

Kerstman, Eric L.; Minard, Charles; FreiredeCarvalho, Mary H.; Walton, Marlei E.; Myers, Jerry G., Jr.; Saile, Lynn G.; Lopez, Vilma; Butler, Douglas J.; Johnson-Throop, Kathy A.

2011-01-01

This slide presentation reviews the Integrated Medical Model (IMM) and its use as a risk assessment and decision support tool for human space flight missions. The IMM is an integrated, quantified, evidence-based decision support tool useful to NASA crew health and mission planners. It is intended to assist in optimizing crew health, safety and mission success within the constraints of the space flight environment for in-flight operations. It uses ISS data to assist in planning for the Exploration Program and it is not intended to assist in post flight research. The IMM was used to update Probability Risk Assessment (PRA) for the purpose of updating forecasts for the conditions requiring evacuation (EVAC) or Loss of Crew Life (LOC) for the ISS. The IMM validation approach includes comparison with actual events and involves both qualitative and quantitaive approaches. The results of these comparisons are reviewed. Another use of the IMM is to optimize the medical kits taking into consideration the specific mission and the crew profile. An example of the use of the IMM to optimize the medical kits is reviewed.

The systems integration operations/logistics model as a decision-support tool

International Nuclear Information System (INIS)

Miller, C.; Vogel, L.W.; Joy, D.S.

1989-01-01

Congress has enacted legislation specifying Yucca Mountain, Nevada, for characterization as the candidate site for the disposal of spent fuel and high-level wastes and has authorized a monitored retrievable storage (MRS) facility if one is warranted. Nevertheless, the exact configuration of the facilities making up the Federal Waste Management System (FWMS) was not specified. This has left the Office of Civilian Radioactive Waste Management (OCRWM) the responsibility for assuring the design of a safe and reliable disposal system. In order to assist in the analysis of potential configuration alternatives, operating strategies, and other factors for the FWMS and its various elements, a decision-support tool known as the systems integration operations/logistics model (SOLMOD) was developed. SOLMOD is a discrete event simulation model that emulates the movement and interaction of equipment and radioactive waste as it is processed through the FWMS - from pickup at reactor pools to emplacement. The model can be used to measure the impacts of different operating schedules and rules, system configurations, and equipment and other resource availabilities on the performance of processes comprising the FWMS and how these factors combine to determine overall system performance. SOLMOD can assist in identifying bottlenecks and can be used to assess capacity utilization of specific equipment and staff as well as overall system resilience

Child welfare organizations: Do specialization and service integration impact placement decisions?

Science.gov (United States)

Smith, Carrie; Fluke, John; Fallon, Barbara; Mishna, Faye; Decker Pierce, Barbara

2018-02-01

The objective of this study was to contribute to the understanding of the child welfare organization by testing the hypothesis that the characteristics of organizations influence decisions made by child protection staff for vulnerable children. The influence of two aspects of organizational structure on the decision to place a child in out-of-home care were examined: service integration and worker specialization. A theoretical framework that integrated the Decision-Making Ecology Framework (Baumann et al., 2011) and Yoo et al. (2007) conceptual framework of organizational constructs as predictors of service effectiveness was tested. Secondary data analysis of the Ontario Incidence Study of Reported Child Abuse and Neglect - 2013 (OIS-2013) was conducted. A subsample of 4949 investigations from 16 agencies was included in this study. Given the nested structure of the data, multi-level modelling was used to test the relative contribution of case and organizational factors to the decision to place. Despite the reported differences among child welfare organizations and research that has demonstrated variance in the placement decision as a result of organizational factors, the structure of the organization (i.e., worker specialization and service integration) showed no predictive power in the final models. The lack of variance may be explained by the relatively low frequency of placements during the investigation phase of service, the hierarchical impact of the factors of the DME and the limited information available regarding the structure of child welfare organizations in Ontario. Suggestions for future research are provided. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrating geographically isolated wetlands into land management decisions

Science.gov (United States)

Golden, Heather E.; Creed, Irena F.; Ali, Genevieve; Basu, Nandita; Neff, Brian; Rains, Mark C.; McLaughlin, Daniel L.; Alexander, Laurie C.; Ameli, Ali A.; Christensen, Jay R.; Evenson, Grey R.; Jones, Charles N.; Lane, Charles R.; Lang, Megan

2017-01-01

Wetlands across the globe provide extensive ecosystem services. However, many wetlands – especially those surrounded by uplands, often referred to as geographically isolated wetlands (GIWs) – remain poorly protected. Protection and restoration of wetlands frequently requires information on their hydrologic connectivity to other surface waters, and their cumulative watershed‐scale effects. The integration of measurements and models can supply this information. However, the types of measurements and models that should be integrated are dependent on management questions and information compatibility. We summarize the importance of GIWs in watersheds and discuss what wetland connectivity means in both science and management contexts. We then describe the latest tools available to quantify GIW connectivity and explore crucial next steps to enhancing and integrating such tools. These advancements will ensure that appropriate tools are used in GIW decision making and maintaining the important ecosystem services that these wetlands support.

Integrating environmental monitoring with cumulative effects management and decision making.

Science.gov (United States)

Cronmiller, Joshua G; Noble, Bram F

2018-05-01

Cumulative effects (CE) monitoring is foundational to emerging regional and watershed CE management frameworks, yet monitoring is often poorly integrated with CE management and decision-making processes. The challenges are largely institutional and organizational, more so than scientific or technical. Calls for improved integration of monitoring with CE management and decision making are not new, but there has been limited research on how best to integrate environmental monitoring programs to ensure credible CE science and to deliver results that respond to the more immediate questions and needs of regulatory decision makers. This paper examines options for the integration of environmental monitoring with CE frameworks. Based on semistructured interviews with practitioners, regulators, and other experts in the Lower Athabasca, Alberta, Canada, 3 approaches to monitoring system design are presented. First, a distributed monitoring system, reflecting the current approach in the Lower Athabasca, where monitoring is delegated to different external programs and organizations; second, a 1-window system in which monitoring is undertaken by a single, in-house agency for the purpose of informing management and regulatory decision making; third, an independent system driven primarily by CE science and understanding causal relationships, with knowledge adopted for decision support where relevant to specific management questions. The strengths and limitations of each approach are presented. A hybrid approach may be optimal-an independent, nongovernment, 1-window model for CE science, monitoring, and information delivery-capitalizing on the strengths of distributed, 1-window, and independent monitoring systems while mitigating their weaknesses. If governments are committed to solving CE problems, they must invest in the long-term science needed to do so; at the same time, if science-based monitoring programs are to be sustainable over the long term, they must be responsive to

An integrated crop model and GIS decision support system for assisting agronomic decision making under climate change.

Science.gov (United States)

Kadiyala, M D M; Nedumaran, S; Singh, Piara; S, Chukka; Irshad, Mohammad A; Bantilan, M C S

2015-07-15

The semi-arid tropical (SAT) regions of India are suffering from low productivity which may be further aggravated by anticipated climate change. The present study analyzes the spatial variability of climate change impacts on groundnut yields in the Anantapur district of India and examines the relative contribution of adaptation strategies. For this purpose, a web based decision support tool that integrates crop simulation model and Geographical Information System (GIS) was developed to assist agronomic decision making and this tool can be scalable to any location and crop. The climate change projections of five global climate models (GCMs) relative to the 1980-2010 baseline for Anantapur district indicates an increase in rainfall activity to the tune of 10.6 to 25% during Mid-century period (2040-69) with RCP 8.5. The GCMs also predict warming exceeding 1.4 to 2.4°C by 2069 in the study region. The spatial crop responses to the projected climate indicate a decrease in groundnut yields with four GCMs (MPI-ESM-MR, MIROC5, CCSM4 and HadGEM2-ES) and a contrasting 6.3% increase with the GCM, GFDL-ESM2M. The simulation studies using CROPGRO-Peanut model reveals that groundnut yields can be increased on average by 1.0%, 5.0%, 14.4%, and 20.2%, by adopting adaptation options of heat tolerance, drought tolerant cultivars, supplemental irrigation and a combination of drought tolerance cultivar and supplemental irrigation respectively. The spatial patterns of relative benefits of adaptation options were geographically different and the greatest benefits can be achieved by adopting new cultivars having drought tolerance and with the application of one supplemental irrigation at 60days after sowing. Copyright © 2015 Elsevier B.V. All rights reserved.

Integrating uncertainty into public energy research and development decisions

Science.gov (United States)

Anadón, Laura Díaz; Baker, Erin; Bosetti, Valentina

2017-05-01

Public energy research and development (R&D) is recognized as a key policy tool for transforming the world's energy system in a cost-effective way. However, managing the uncertainty surrounding technological change is a critical challenge for designing robust and cost-effective energy policies. The design of such policies is particularly important if countries are going to both meet the ambitious greenhouse-gas emissions reductions goals set by the Paris Agreement and achieve the required harmonization with the broader set of objectives dictated by the Sustainable Development Goals. The complexity of informing energy technology policy requires, and is producing, a growing collaboration between different academic disciplines and practitioners. Three analytical components have emerged to support the integration of technological uncertainty into energy policy: expert elicitations, integrated assessment models, and decision frameworks. Here we review efforts to incorporate all three approaches to facilitate public energy R&D decision-making under uncertainty. We highlight emerging insights that are robust across elicitations, models, and frameworks, relating to the allocation of public R&D investments, and identify gaps and challenges that remain.

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.

Improving Land Use/Land Cover Classification by Integrating Pixel Unmixing and Decision Tree Methods

Directory of Open Access Journals (Sweden)

Chao Yang

2017-11-01

Full Text Available Decision tree classification is one of the most efficient methods for obtaining land use/land cover (LULC information from remotely sensed imageries. However, traditional decision tree classification methods cannot effectively eliminate the influence of mixed pixels. This study aimed to integrate pixel unmixing and decision tree to improve LULC classification by removing mixed pixel influence. The abundance and minimum noise fraction (MNF results that were obtained from mixed pixel decomposition were added to decision tree multi-features using a three-dimensional (3D Terrain model, which was created using an image fusion digital elevation model (DEM, to select training samples (ROIs, and improve ROI separability. A Landsat-8 OLI image of the Yunlong Reservoir Basin in Kunming was used to test this proposed method. Study results showed that the Kappa coefficient and the overall accuracy of integrated pixel unmixing and decision tree method increased by 0.093% and 10%, respectively, as compared with the original decision tree method. This proposed method could effectively eliminate the influence of mixed pixels and improve the accuracy in complex LULC classifications.

Intelligent Model Management in a Forest Ecosystem Management Decision Support System

Science.gov (United States)

Donald Nute; Walter D. Potter; Frederick Maier; Jin Wang; Mark Twery; H. Michael Rauscher; Peter Knopp; Scott Thomasma; Mayukh Dass; Hajime Uchiyama

2002-01-01

Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust, intelligent, goal-driven decision support system that integrates tools in each of these categories. NED-2 uses a blackboard...

An Integrated Decision-Making Model for the Location of a PV Solar Plant

Directory of Open Access Journals (Sweden)

Amy H. I. Lee

2015-09-01

Full Text Available Due to the increasing demand for electricity, the depletion of fossil fuels and the increase in environmental consciousness, generating power from renewable energy resources has become necessary. How to select the most appropriate site is a critical and foremost decision that must be made when setting up a renewable energy plant. This research proposes a two-stage framework for evaluating the suitability of renewable energy plant site alternatives. In the first stage, a fuzzy analytic hierarchy process (FAHP is adopted to set the assurance region (AR of the quantitative factors, and the AR is incorporated into data envelopment analysis (DEA to assess the efficiencies of plant site candidates. A few sites are selected for further analysis. In the second stage, experts are invited to evaluate the qualitative characteristics of the selected sites, and FAHP is used to calculate the priorities of these sites. Solar energy is one of the most promising renewable energy sources, because of its abundance, inexhaustibility, safety and cleanliness. Based on the proposed integrated decision-making model, a case study for selecting the most appropriate photovoltaic (PV solar plant site is examined.

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

Shared Decision-Making for Nursing Practice: An Integrative Review.

Science.gov (United States)

Truglio-Londrigan, Marie; Slyer, Jason T

2018-01-01

Shared decision-making has received national and international interest by providers, educators, researchers, and policy makers. The literature on shared decision-making is extensive, dealing with the individual components of shared decision-making rather than a comprehensive process. This view of shared decision-making leaves healthcare providers to wonder how to integrate shared decision-making into practice. To understand shared decision-making as a comprehensive process from the perspective of the patient and provider in all healthcare settings. An integrative review was conducted applying a systematic approach involving a literature search, data evaluation, and data analysis. The search included articles from PubMed, CINAHL, the Cochrane Central Register of Controlled Trials, and PsycINFO from 1970 through 2016. Articles included quantitative experimental and non-experimental designs, qualitative, and theoretical articles about shared decision-making between all healthcare providers and patients in all healthcare settings. Fifty-two papers were included in this integrative review. Three categories emerged from the synthesis: (a) communication/ relationship building; (b) working towards a shared decision; and (c) action for shared decision-making. Each major theme contained sub-themes represented in the proposed visual representation for shared decision-making. A comprehensive understanding of shared decision-making between the nurse and the patient was identified. A visual representation offers a guide that depicts shared decision-making as a process taking place during a healthcare encounter with implications for the continuation of shared decisions over time offering patients an opportunity to return to the nurse for reconsiderations of past shared decisions.

An Integrated Psychosocial Model of Relatives' Decision About Deceased Organ Donation (IMROD): Joining Pieces of the Puzzle

Science.gov (United States)

López, Jorge S.; Soria-Oliver, Maria; Aramayona, Begoña; García-Sánchez, Rubén; Martínez, José M.; Martín, María J.

2018-01-01

Organ transplantation remains currently limited because the demand for organs far exceeds the supply. Though organ procurement is a complex process involving social, organizational, and clinical factors, one of the most relevant limitations of organ availability is family refusal to donate organs of a deceased relative. In the past decades, a remarkable corpus of evidence about the factors conditioning relatives' consent has been generated. However, research in the field has been carried out mainly by means of merely empirical approaches, and only partial attempts have been made to integrate the existing empirical evidence within conceptual and theoretically based frameworks. Accordingly, this work articulates the proposal of an Integrated Psychosocial Model of Relatives' Organ Donation (IMROD) which offers a systematic view of the factors and psychosocial processes involved in family decision and their interrelations. Relatives' experience is conceptualized as a decision process about the possibility of vicariously performing an altruistic behavior that takes place under one of the most stressful experiences of one's lifetime and in the context of interaction with different healthcare professionals. Drawing on this, in the proposed model, the influence of the implied factors and their interrelations/interactions are structured and interpreted according to their theoretically based relation with processes like rational/heuristic decision-making, uncertainty, stress, bereavement, emotional reactions, sense of reciprocity, sense of freedom to decide, and attitudes/intentions toward one's own and the deceased's organ donation. Our model also develops a processual perspective and suggests different decisional scenarios that may be reached as a result of the combinations of the considered factors. Each of these scenarios may imply different balances between factors that enhance or hinder donation, such as different levels of uncertainty and potential decisional conflict

An Integrated Psychosocial Model of Relatives' Decision About Deceased Organ Donation (IMROD): Joining Pieces of the Puzzle.

Science.gov (United States)

López, Jorge S; Soria-Oliver, Maria; Aramayona, Begoña; García-Sánchez, Rubén; Martínez, José M; Martín, María J

2018-01-01

Organ transplantation remains currently limited because the demand for organs far exceeds the supply. Though organ procurement is a complex process involving social, organizational, and clinical factors, one of the most relevant limitations of organ availability is family refusal to donate organs of a deceased relative. In the past decades, a remarkable corpus of evidence about the factors conditioning relatives' consent has been generated. However, research in the field has been carried out mainly by means of merely empirical approaches, and only partial attempts have been made to integrate the existing empirical evidence within conceptual and theoretically based frameworks. Accordingly, this work articulates the proposal of an Integrated Psychosocial Model of Relatives' Organ Donation (IMROD) which offers a systematic view of the factors and psychosocial processes involved in family decision and their interrelations. Relatives' experience is conceptualized as a decision process about the possibility of vicariously performing an altruistic behavior that takes place under one of the most stressful experiences of one's lifetime and in the context of interaction with different healthcare professionals. Drawing on this, in the proposed model, the influence of the implied factors and their interrelations/interactions are structured and interpreted according to their theoretically based relation with processes like rational/heuristic decision-making, uncertainty, stress, bereavement, emotional reactions, sense of reciprocity, sense of freedom to decide, and attitudes/intentions toward one's own and the deceased's organ donation. Our model also develops a processual perspective and suggests different decisional scenarios that may be reached as a result of the combinations of the considered factors. Each of these scenarios may imply different balances between factors that enhance or hinder donation, such as different levels of uncertainty and potential decisional conflict

An Integrated Psychosocial Model of Relatives' Decision About Deceased Organ Donation (IMROD: Joining Pieces of the Puzzle

Directory of Open Access Journals (Sweden)

Jorge S. López

2018-04-01

Full Text Available Organ transplantation remains currently limited because the demand for organs far exceeds the supply. Though organ procurement is a complex process involving social, organizational, and clinical factors, one of the most relevant limitations of organ availability is family refusal to donate organs of a deceased relative. In the past decades, a remarkable corpus of evidence about the factors conditioning relatives' consent has been generated. However, research in the field has been carried out mainly by means of merely empirical approaches, and only partial attempts have been made to integrate the existing empirical evidence within conceptual and theoretically based frameworks. Accordingly, this work articulates the proposal of an Integrated Psychosocial Model of Relatives' Organ Donation (IMROD which offers a systematic view of the factors and psychosocial processes involved in family decision and their interrelations. Relatives' experience is conceptualized as a decision process about the possibility of vicariously performing an altruistic behavior that takes place under one of the most stressful experiences of one's lifetime and in the context of interaction with different healthcare professionals. Drawing on this, in the proposed model, the influence of the implied factors and their interrelations/interactions are structured and interpreted according to their theoretically based relation with processes like rational/heuristic decision-making, uncertainty, stress, bereavement, emotional reactions, sense of reciprocity, sense of freedom to decide, and attitudes/intentions toward one's own and the deceased's organ donation. Our model also develops a processual perspective and suggests different decisional scenarios that may be reached as a result of the combinations of the considered factors. Each of these scenarios may imply different balances between factors that enhance or hinder donation, such as different levels of uncertainty and potential

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

DEFF Research Database (Denmark)

Dong, Yan; Miraglia, Simona; Manzo, Stefano

2018-01-01

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

A System Dynamics Model for Integrated Decision Making: The Durham-Orange Light Rail Project

Science.gov (United States)

EPA’s Sustainable and Healthy Communities Research Program (SHC) is conducting transdisciplinary research to inform and empower decision-makers. EPA tools and approaches are being developed to enable communities to effectively weigh and integrate human health, socioeconomic, envi...

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

Multiple methods for multiple futures: Integrating qualitative scenario planning and quantitative simulation modeling for natural resource decision making

Science.gov (United States)

Symstad, Amy J.; Fisichelli, Nicholas A.; Miller, Brian W.; Rowland, Erika; Schuurman, Gregor W.

2017-01-01

Scenario planning helps managers incorporate climate change into their natural resource decision making through a structured “what-if” process of identifying key uncertainties and potential impacts and responses. Although qualitative scenarios, in which ecosystem responses to climate change are derived via expert opinion, often suffice for managers to begin addressing climate change in their planning, this approach may face limits in resolving the responses of complex systems to altered climate conditions. In addition, this approach may fall short of the scientific credibility managers often require to take actions that differ from current practice. Quantitative simulation modeling of ecosystem response to climate conditions and management actions can provide this credibility, but its utility is limited unless the modeling addresses the most impactful and management-relevant uncertainties and incorporates realistic management actions. We use a case study to compare and contrast management implications derived from qualitative scenario narratives and from scenarios supported by quantitative simulations. We then describe an analytical framework that refines the case study’s integrated approach in order to improve applicability of results to management decisions. The case study illustrates the value of an integrated approach for identifying counterintuitive system dynamics, refining understanding of complex relationships, clarifying the magnitude and timing of changes, identifying and checking the validity of assumptions about resource responses to climate, and refining management directions. Our proposed analytical framework retains qualitative scenario planning as a core element because its participatory approach builds understanding for both managers and scientists, lays the groundwork to focus quantitative simulations on key system dynamics, and clarifies the challenges that subsequent decision making must address.

Integrated Risk-Informed Decision-Making for an ALMR PRISM

Energy Technology Data Exchange (ETDEWEB)

Muhlheim, Michael David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Belles, Randy [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Denning, Richard S. [Self Employed

2016-05-01

Decision-making is the process of identifying decision alternatives, assessing those alternatives based on predefined metrics, selecting an alternative (i.e., making a decision), and then implementing that alternative. The generation of decisions requires a structured, coherent process, or a decision-making process. The overall objective for this work is that the generalized framework is adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or no human intervention. The overriding goal of automation is to replace or supplement human decision makers with reconfigurable decision-making modules that can perform a given set of tasks rationally, consistently, and reliably. Risk-informed decision-making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The probabilistic portion of the decision-making engine of the supervisory control system is based on the control actions associated with an ALMR PRISM. Newly incorporated into the probabilistic models are the prognostic/diagnostic models developed by Pacific Northwest National Laboratory. These allow decisions to incorporate the health of components into the decision–making process. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic portion of the decision-making engine uses thermal-hydraulic modeling and components for an advanced liquid-metal reactor Power Reactor Inherently Safe Module. The deterministic multi

Advancing Alternative Analysis: Integration of Decision Science

DEFF Research Database (Denmark)

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

2016-01-01

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

The interrogation decision-making model: A general theoretical framework for confessions.

Science.gov (United States)

Yang, Yueran; Guyll, Max; Madon, Stephanie

2017-02-01

This article presents a new model of confessions referred to as the interrogation decision-making model . This model provides a theoretical umbrella with which to understand and analyze suspects' decisions to deny or confess guilt in the context of a custodial interrogation. The model draws upon expected utility theory to propose a mathematical account of the psychological mechanisms that not only underlie suspects' decisions to deny or confess guilt at any specific point during an interrogation, but also how confession decisions can change over time. Findings from the extant literature pertaining to confessions are considered to demonstrate how the model offers a comprehensive and integrative framework for organizing a range of effects within a limited set of model parameters. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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

Bangkok's mass rapid transit system's commuter decision-making process in using integrated smartcards

Directory of Open Access Journals (Sweden)

Peerakan Kaewwongwattana

2016-05-01

Full Text Available This paper studied the decision-making process to use an integrated smartcard ticketing system by Bangkok metropolitan transit commuters. A second-order Confirmatory Factor Analysis using LISREL 9.10 was undertaken on Bangkok commuter's decision-making process on the use of an integrated smartcard system. The sample consisted of 300 Bangkok commuters obtained by accidental sampling using questionnaires with a 5-point Likert scale. The tools in the research questionnaires used scale estimation that achieved a confidence value of 0.84. The research instruments used rating scales measuring information search, alternative choices, and use decision on the 15 variables in the decision-making process which had factor loadings between 0.49 and 0.89 weight elements when sorted in descending order and overall had a high level. Use decision, alternative choices and information search had a factor of 0.89, 0.65 and 0.49, respectively. There was a good fit of the decision-making model to the empirical data (chi-square = 34.55, probability (p = 0.94, df = 49, RMSEA = 0.00, GFI = 0.98, AGFI = 0.96, SRMR = 0.04.

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.

Real-Time Decision Making and Aggressive Behavior in Youth: A Heuristic Model of Response Evaluation and Decision (RED).

Science.gov (United States)

Fontaine, Reid Griffith; Dodge, Kenneth A

2006-11-01

Considerable scientific and intervention attention has been paid to judgment and decision-making systems associated with aggressive behavior in youth. However, most empirical studies have investigated social-cognitive correlates of stable child and adolescent aggressiveness, and less is known about real-time decision making to engage in aggressive behavior. A model of real-time decision making must incorporate both impulsive actions and rational thought. The present paper advances a process model (response evaluation and decision; RED) of real-time behavioral judgments and decision making in aggressive youths with mathematic representations that may be used to quantify response strength. These components are a heuristic to describe decision making, though it is doubtful that individuals always mentally complete these steps. RED represents an organization of social-cognitive operations believed to be active during the response decision step of social information processing. The model posits that RED processes can be circumvented through impulsive responding. This article provides a description and integration of thoughtful, rational decision making and nonrational impulsivity in aggressive behavioral interactions.

Effects of stochastic interest rates in decision making under risk: A Markov decision process model for forest management

Science.gov (United States)

Mo Zhou; Joseph Buongiorno

2011-01-01

Most economic studies of forest decision making under risk assume a fixed interest rate. This paper investigated some implications of this stochastic nature of interest rates. Markov decision process (MDP) models, used previously to integrate stochastic stand growth and prices, can be extended to include variable interest rates as well. This method was applied to...

Comparison of Multi-Criteria Decision Support Methods for Integrated Rehabilitation Prioritization

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Franz Tscheikner-Gratl

2017-01-01

Full Text Available The decisions taken in rehabilitation planning for the urban water networks will have a long lasting impact on the functionality and quality of future services provided by urban infrastructure. These decisions can be assisted by different approaches ranging from linear depreciation for estimating the economic value of the network over using a deterioration model to assess the probability of failure or the technical service life to sophisticated multi-criteria decision support systems. Subsequently, the aim of this paper is to compare five available multi-criteria decision-making (MCDM methods (ELECTRE, AHP, WSM, TOPSIS, and PROMETHEE for the application in an integrated rehabilitation management scheme for a real world case study and analyze them with respect to their suitability to be used in integrated asset management of water systems. The results of the different methods are not equal. This occurs because the chosen score scales, weights and the resulting distributions of the scores within the criteria do not have the same impact on all the methods. Independently of the method used, the decision maker must be familiar with its strengths but also weaknesses. Therefore, in some cases, it would be rational to use one of the simplest methods. However, to check for consistency and increase the reliability of the results, the application of several methods is encouraged.

Integrated catchment modelling in a Semi-arid area

CSIR Research Space (South Africa)

Bugan, Richard DH

2010-09-01

Full Text Available , will increasingly need water quality and quantity management tools to be able to make informed decisions. Integrated catchment modelling (ICM) is regarded as being a valuable tool for integrated water resource management. It enables officials and scientists to make...

Consumer's Online Shopping Influence Factors and Decision-Making Model

Science.gov (United States)

Yan, Xiangbin; Dai, Shiliang

Previous research on online consumer behavior has mostly been confined to the perceived risk which is used to explain those barriers for purchasing online. However, perceived benefit is another important factor which influences consumers’ decision when shopping online. As a result, an integrated consumer online shopping decision-making model is developed which contains three elements—Consumer, Product, and Web Site. This model proposed relative factors which influence the consumers’ intention during the online shopping progress, and divided them into two different dimensions—mentally level and material level. We tested those factors with surveys, from both online volunteers and offline paper surveys with more than 200 samples. With the help of SEM, the experimental results show that the proposed model and method can be used to analyze consumer’s online shopping decision-making process effectively.

An IT perspective on integrated environmental modelling: The SIAT case

NARCIS (Netherlands)

Verweij, P.J.F.M.; Knapen, M.J.R.; Winter, de W.P.; Wien, J.J.F.; Roller, te J.A.; Sieber, S.; Jansen, J.M.L.

2010-01-01

Policy makers have a growing interest in integrated assessments of policies. The Integrated Assessment Modelling (IAM) community is reacting to this interest by extending the application of model development from pure scientific analysis towards application in decision making or policy context by

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)

A mixed integer program to model spatial wildfire behavior and suppression placement decisions

Science.gov (United States)

Erin J. Belval; Yu Wei; Michael. Bevers

2015-01-01

Wildfire suppression combines multiple objectives and dynamic fire behavior to form a complex problem for decision makers. This paper presents a mixed integer program designed to explore integrating spatial fire behavior and suppression placement decisions into a mathematical programming framework. Fire behavior and suppression placement decisions are modeled using...

Rationality and Integration in a Family Childrearing Decision.

Science.gov (United States)

Diana, Mark S.

This paper illuminates how concepts of rationality developed by Diesing in l962 are reflected in parents' childrearing decisions. After examining technical (TR), economic (ER), social (SR), legal (LR), and political (PR) rationalities or decision-making styles, consideration is given to integrative effects and the influence of parents' friends and…

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...

Organizational buying behavior: An integrated model

Directory of Open Access Journals (Sweden)

Rakić Beba

2002-01-01

Full Text Available Organizational buying behavior is decision making process by which formal organizations establish the need for purchased products and services, and identify, evaluate, and choose among alternative brands and suppliers. Understanding the buying decision processes is essential to developing the marketing programs of companies that sell to organizations, or to 'industrial customers'. In business (industrial marketing, exchange relationships between the organizational selling center and the organizational buying center are crucial. Integrative model of organizational buying behavior offers a systematic framework in analyzing the complementary factors and what effect they have on the behavior of those involved in making buying decisions.

Adolescent Sexual Decision-Making: An Integrative Review.

Science.gov (United States)

Hulton, Linda J.

2001-10-03

PURPOSE: The purpose of this integrative review was to summarize the present literature to identify factors associated with adolescent sexual decision-making. Thirty-eight salient research studies were selected as a basis of this review from the databases of Medline, CINAHL, and Psychinfo using the Cooper methodology. CONCLUSIONS: Two categories of decision-making were identified: 1) The research on factors related to the decisions that adolescents make to become sexually active or to abstain from sexual activity; 2) The research on factors related to contraceptive decision-making. The most consistent findings were that the factors of gender differences, cognitive development, perception of benefits, parental influences, social influences, and sexual knowledge were important variables in the decision-making processes of adolescents. IMPLICATIONS: Practice implications for nursing suggest that clinicians should assess adolescent sexual decision-making in greater detail and address the social and psychological context in which sexual experiences occur. Nurses must be aware of the differences between adolescent and adult decision-making processes and incorporate knowledge of growth and development into intervention strategies. Moreover, to the degree that adolescent sexual decision-making proves to be less than rational, interventions designed to improve competent sexual decision-making are needed.

The National Danish Water Resources Model - using an integrated groundwater - surface water model for decision support and WFD implementation in a changing climate

Science.gov (United States)

Lajer Hojberg, Anker; Hinsby, Klaus; Jørgen Henriksen, Hans; Troldborg, Lars

2014-05-01

Integrated and sustainable water resources management and development of river basin management plans according to the Water Framework Directive is getting increasingly complex especially when taking projected climate change into account. Furthermore, uncertainty in future developments and incomplete knowledge of the physical system introduces a high degree of uncertainty in the decision making process. Knowledge based decision making is therefore vital for formulation of robust management plans and to allow assessment of the inherent uncertainties. The Department of Hydrology at the Geological Survey of Denmark and Greenland started in 1996 to develop a mechanistically, transient and spatially distributed groundwater-surface water model - the DK-model - for the assessment of groundwater quantitative status accounting for interactions with surface water and anthropogenic changes, such as extraction strategies and land use, as well as climate change. The model has been subject to continuous update building on hydrogeological knowledge established by the regional water authorities and other national research institutes. With the on-going improvement of the DK-model it is now increasingly applied both by research projects and for decision support e.g. in implementation of the Water Framework Directive or to support other decisions related to protection of water resources (quantitative and chemical status), ecosystems and the built environment. At present, the DK-model constitutes the backbone of a strategic modelling project funded by the Danish Environmental Protection Agency, with the aim of developing a modelling complex that will provide the foundation of the implementation of the Water Framework Directive. Since 2003 the DK-model has been used in more than 25 scientific papers and even more public reports. In the poster and the related review paper we describe the most important applications in both science and policy, where the DK-model has been used either

An Integrated Decision Support System with Hydrological Processes and Socio-economic Assessments

Science.gov (United States)

Yu, Yang; Disse, Markus; Yu, Ruide

2017-04-01

The debate over the effectiveness of Integrated Water Resources Management (IWRM) in practice has lasted for years. As the complexity and scope of IWRM increases, the difficulties of hydrological modeling is shifting from the model itself into the links with other cognate sciences, to understand the interactions among water, earth, ecosystem and humans. This work presents the design and development of a decision support system (DSS) that links the outputs of hydrological models with real-time decision making on social-economic assessments and land use changes. Discharge and glacier geometry changes were simulated with hydrological model WASA. Irrigation and ecological water were simulated by a new commercial software MIKE HYDRO. Groundwater was simulated by MODFLOW. All the outputs of theses hydrological models were integrated as inputs into the DSS in three types of links: regression equations, stationary data inputs, or dynamic data inputs into DSS as the models running parallel in the simulation periods. Within DSS, three types of logics were established: equations, conditional statements and fuzzy logics. The programming was realized in C++. The implementation of DSS takes place in the Tarim River Basin. With the mainstream of 1,321km and located in an arid area in northwest China, the Tarim River is China's longest inland river. The Tarim basin on the northern edge of the Taklamakan desert is an extremely arid region. In this region, agricultural water consumption and allocation management are crucial to address the conflicts among irrigation water users from upstream to downstream. Since 2011, the German Ministry of Science and Education BMBF established the Sino-German SuMaRiO project, for the sustainable management of river oases along the Tarim River. Project SuMaRiO focus on realizable management strategies, considering social, economic and ecological criteria. This will have positive effects for nearly 10 million inhabitants of different ethnic groups

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)

The dynamics of multimodal integration: The averaging diffusion model.

Science.gov (United States)

Turner, Brandon M; Gao, Juan; Koenig, Scott; Palfy, Dylan; L McClelland, James

2017-12-01

We combine extant theories of evidence accumulation and multi-modal integration to develop an integrated framework for modeling multimodal integration as a process that unfolds in real time. Many studies have formulated sensory processing as a dynamic process where noisy samples of evidence are accumulated until a decision is made. However, these studies are often limited to a single sensory modality. Studies of multimodal stimulus integration have focused on how best to combine different sources of information to elicit a judgment. These studies are often limited to a single time point, typically after the integration process has occurred. We address these limitations by combining the two approaches. Experimentally, we present data that allow us to study the time course of evidence accumulation within each of the visual and auditory domains as well as in a bimodal condition. Theoretically, we develop a new Averaging Diffusion Model in which the decision variable is the mean rather than the sum of evidence samples and use it as a base for comparing three alternative models of multimodal integration, allowing us to assess the optimality of this integration. The outcome reveals rich individual differences in multimodal integration: while some subjects' data are consistent with adaptive optimal integration, reweighting sources of evidence as their relative reliability changes during evidence integration, others exhibit patterns inconsistent with optimality.

[Prediction of regional soil quality based on mutual information theory integrated with decision tree algorithm].

Science.gov (United States)

Lin, Fen-Fang; Wang, Ke; Yang, Ning; Yan, Shi-Guang; Zheng, Xin-Yu

2012-02-01

In this paper, some main factors such as soil type, land use pattern, lithology type, topography, road, and industry type that affect soil quality were used to precisely obtain the spatial distribution characteristics of regional soil quality, mutual information theory was adopted to select the main environmental factors, and decision tree algorithm See 5.0 was applied to predict the grade of regional soil quality. The main factors affecting regional soil quality were soil type, land use, lithology type, distance to town, distance to water area, altitude, distance to road, and distance to industrial land. The prediction accuracy of the decision tree model with the variables selected by mutual information was obviously higher than that of the model with all variables, and, for the former model, whether of decision tree or of decision rule, its prediction accuracy was all higher than 80%. Based on the continuous and categorical data, the method of mutual information theory integrated with decision tree could not only reduce the number of input parameters for decision tree algorithm, but also predict and assess regional soil quality effectively.

Advancing Alternative Analysis: Integration of Decision Science.

Science.gov (United States)

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

2017-06-13

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

Advancing coupled human-earth system models: The integrated Earth System Model Project

Science.gov (United States)

Thomson, A. M.; Edmonds, J. A.; Collins, W.; Thornton, P. E.; Hurtt, G. C.; Janetos, A. C.; Jones, A.; Mao, J.; Chini, L. P.; Calvin, K. V.; Bond-Lamberty, B. P.; Shi, X.

2012-12-01

As human and biogeophysical models develop, opportunities for connections between them evolve and can be used to advance our understanding of human-earth systems interaction in the context of a changing climate. One such integration is taking place with the Community Earth System Model (CESM) and the Global Change Assessment Model (GCAM). A multi-disciplinary, multi-institution team has succeeded in integrating the GCAM integrated assessment model of human activity into CESM to dynamically represent the feedbacks between changing climate and human decision making, in the context of greenhouse gas mitigation policies. The first applications of this capability have focused on the feedbacks between climate change impacts on terrestrial ecosystem productivity and human decisions affecting future land use change, which are in turn connected to human decisions about energy systems and bioenergy production. These experiments have been conducted in the context of the RCP4.5 scenario, one of four pathways of future radiative forcing being used in CMIP5, which constrains future human-induced greenhouse gas emissions from energy and land activities to stabilize radiative forcing at 4.5 W/m2 (~650 ppm CO2 -eq) by 2100. When this pathway is run in GCAM with the climate feedback on terrestrial productivity from CESM, there are implications for both the land use and energy system changes required for stabilization. Early findings indicate that traditional definitions of radiative forcing used in scenario development are missing a critical component of the biogeophysical consequences of land use change and their contribution to effective radiative forcing. Initial full coupling of the two global models has important implications for how climate impacts on terrestrial ecosystems changes the dynamics of future land use change for agriculture and forestry, particularly in the context of a climate mitigation policy designed to reduce emissions from land use as well as energy systems

The Arithmetic of Emotion: Integration of Incidental and Integral Affect in Judgments and Decisions

Directory of Open Access Journals (Sweden)

Daniel eVastfjall

2016-03-01

Full Text Available Research has demonstrated that two types of affect have an influence on judgment and decision making: incidental affect (affect unrelated to a judgment or decision such as a mood and integral affect (affect that is part of the perceiver’s internal representation of the option or target under consideration. So far, these two lines of research have seldom crossed so that knowledge concerning their combined effects is largely missing. To fill this gap, the present review highlights differences and similarities between integral and incidental affect. Further, common and unique mechanisms that enable these two types of affect to influence judgment and choices are identified. Finally, some basic principles for affect integration when the two sources co-occur are outlined. These principles are discussed in relation to existing work that has focused on incidental or integral affect but not both.

Integrated Decision Tools for Sustainable Watershed/Ground Water and Crop Health using Predictive Weather, Remote Sensing, and Irrigation Decision Tools

Science.gov (United States)

Jones, A. S.; Andales, A.; McGovern, C.; Smith, G. E. B.; David, O.; Fletcher, S. J.

2017-12-01

US agricultural and Govt. lands have a unique co-dependent relationship, particularly in the Western US. More than 30% of all irrigated US agricultural output comes from lands sustained by the Ogallala Aquifer in the western Great Plains. Six US Forest Service National Grasslands reside within the aquifer region, consisting of over 375,000 ha (3,759 km2) of USFS managed lands. Likewise, National Forest lands are the headwaters to many intensive agricultural regions. Our Ogallala Aquifer team is enhancing crop irrigation decision tools with predictive weather and remote sensing data to better manage water for irrigated crops within these regions. An integrated multi-model software framework is used to link irrigation decision tools, resulting in positive management benefits on natural water resources. Teams and teams-of-teams can build upon these multi-disciplinary multi-faceted modeling capabilities. For example, the CSU Catalyst for Innovative Partnerships program has formed a new multidisciplinary team that will address "Rural Wealth Creation" focusing on the many integrated links between economic, agricultural production and management, natural resource availabilities, and key social aspects of govt. policy recommendations. By enhancing tools like these with predictive weather and other related data (like in situ measurements, hydrologic models, remotely sensed data sets, and (in the near future) linking to agro-economic and life cycle assessment models) this work demonstrates an integrated data-driven future vision of inter-meshed dynamic systems that can address challenging multi-system problems. We will present the present state of the work and opportunities for future involvement.

Building a maintenance policy through a multi-criterion decision-making model

Science.gov (United States)

Faghihinia, Elahe; Mollaverdi, Naser

2012-08-01

A major competitive advantage of production and service systems is establishing a proper maintenance policy. Therefore, maintenance managers should make maintenance decisions that best fit their systems. Multi-criterion decision-making methods can take into account a number of aspects associated with the competitiveness factors of a system. This paper presents a multi-criterion decision-aided maintenance model with three criteria that have more influence on decision making: reliability, maintenance cost, and maintenance downtime. The Bayesian approach has been applied to confront maintenance failure data shortage. Therefore, the model seeks to make the best compromise between these three criteria and establish replacement intervals using Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE II), integrating the Bayesian approach with regard to the preference of the decision maker to the problem. Finally, using a numerical application, the model has been illustrated, and for a visual realization and an illustrative sensitivity analysis, PROMETHEE GAIA (the visual interactive module) has been used. Use of PROMETHEE II and PROMETHEE GAIA has been made with Decision Lab software. A sensitivity analysis has been made to verify the robustness of certain parameters of the model.

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.

An Integrated Decision-Making Model for Transformer Condition Assessment Using Game Theory and Modified Evidence Combination Extended by D Numbers

Directory of Open Access Journals (Sweden)

Lingjie Sun

2016-08-01

Full Text Available The power transformer is one of the most critical and expensive components for the stable operation of the power system. Hence, how to obtain the health condition of transformer is of great importance for power utilities. Multi-attribute decision-making (MADM, due to its ability of solving multi-source information problems, has become a quite effective tool to evaluate the health condition of transformers. Currently, the analytic hierarchy process (AHP and Dempster–Shafer theory are two popular methods to solve MADM problems; however, these techniques rarely consider one-sidedness of the single weighting method and the exclusiveness hypothesis of the Dempster–Shafer theory. To overcome these limitations, this paper introduces a novel decision-making model, which integrates the merits of fuzzy set theory, game theory and modified evidence combination extended by D numbers, to evaluate the health condition of transformers. A four-level framework, which includes three factors and seventeen sub-factors, is put forward to facilitate the evaluation model. The model points out the following: First, the fuzzy set theory is employed to obtain the original basic probability assignments for all indices. Second, the subjective and objective weights of indices, which are calculated by fuzzy AHP and entropy weight, respectively, are integrated to generate the comprehensive weights based on game theory. Finally, based on the above two steps, the modified evidence combination extended by D numbers, which avoids the limitation of the exclusiveness hypothesis in the application of Dempster–Shafer theory, is proposed to obtain the final assessment results of transformers. Case studies are given to demonstrate the proposed modeling process. The results show the effectiveness and engineering practicability of the model in transformer condition assessment.

Multiobjective decision-making in integrated water management

NARCIS (Netherlands)

Wind, H.G.; Pouwels, I.H.M.; Pouwels, I.H.M.; Witter, V.J.

1995-01-01

Traditionally, decision-making by water authorities in the Netherlands is largely based on intuition. Their tasks were, after all, relatively few and straight-forward. The growing number of tasks, together with the new integrated approach on water management issues, however, induces water

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.

Integral-Value Models for Outcomes over Continuous Time

DEFF Research Database (Denmark)

Harvey, Charles M.; Østerdal, Lars Peter

Models of preferences between outcomes over continuous time are important for individual, corporate, and social decision making, e.g., medical treatment, infrastructure development, and environmental regulation. This paper presents a foundation for such models. It shows that conditions on prefere...... on preferences between real- or vector-valued outcomes over continuous time are satisfied if and only if the preferences are represented by a value function having an integral form......Models of preferences between outcomes over continuous time are important for individual, corporate, and social decision making, e.g., medical treatment, infrastructure development, and environmental regulation. This paper presents a foundation for such models. It shows that conditions...

Rational misbehavior? Evaluating an integrated dual-process model of criminal decision making

NARCIS (Netherlands)

van Gelder, J.L.; de Vries, R.E.

2014-01-01

Objectives: Test the hypothesis that dispositional self-control and morality relate to criminal decision making via different mental processing modes, a 'hot' affective mode and a 'cool' cognitive one. Methods: Structural equation modeling in two studies under separate samples of undergraduate

A Decision Support System for integrated tourism development: Rethinking tourism policies and management strategies

Czech Academy of Sciences Publication Activity Database

Bousset, J. P.; Skuras, D.; Těšitel, Jan; Marsat, J. B.; Petrou, A.; Fiallo-Pantziou, E.; Kušová, Drahomíra; Bartoš, Michael

2007-01-01

Roč. 9, č. 4 (2007), s. 387-404 ISSN 1461-6688 Grant - others:-(XE) QLK5-CT-2000-01211-SPRITE Institutional research plan: CEZ:AV0Z60870520 Keywords : Integrated tourism * policy formulation * participatory approaches * simulation models * decision support system Subject RIV: AE - Management ; Administration

Decision-Making Under Risk: Integrating Perspectives From Biology, Economics, and Psychology.

Science.gov (United States)

Mishra, Sandeep

2014-08-01

Decision-making under risk has been variably characterized and examined in many different disciplines. However, interdisciplinary integration has not been forthcoming. Classic theories of decision-making have not been amply revised in light of greater empirical data on actual patterns of decision-making behavior. Furthermore, the meta-theoretical framework of evolution by natural selection has been largely ignored in theories of decision-making under risk in the human behavioral sciences. In this review, I critically examine four of the most influential theories of decision-making from economics, psychology, and biology: expected utility theory, prospect theory, risk-sensitivity theory, and heuristic approaches. I focus especially on risk-sensitivity theory, which offers a framework for understanding decision-making under risk that explicitly involves evolutionary considerations. I also review robust empirical evidence for individual differences and environmental/situational factors that predict actual risky decision-making that any general theory must account for. Finally, I offer steps toward integrating various theoretical perspectives and empirical findings on risky decision-making. © 2014 by the Society for Personality and Social Psychology, Inc.

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.

IDESSA: An Integrative Decision Support System for Sustainable Rangeland Management in Southern African Savannas

Science.gov (United States)

Meyer, Hanna; Authmann, Christian; Dreber, Niels; Hess, Bastian; Kellner, Klaus; Morgenthal, Theunis; Nauss, Thomas; Seeger, Bernhard; Tsvuura, Zivanai; Wiegand, Kerstin

2017-04-01

Bush encroachment is a syndrome of land degradation that occurs in many savannas including those of southern Africa. The increase in density, cover or biomass of woody vegetation often has negative effects on a range of ecosystem functions and services, which are hardly reversible. However, despite its importance, neither the causes of bush encroachment, nor the consequences of different resource management strategies to combat or mitigate related shifts in savanna states are fully understood. The project "IDESSA" (An Integrative Decision Support System for Sustainable Rangeland Management in Southern African Savannas) aims to improve the understanding of the complex interplays between land use, climate patterns and vegetation dynamics and to implement an integrative monitoring and decision-support system for the sustainable management of different savanna types. For this purpose, IDESSA follows an innovative approach that integrates local knowledge, botanical surveys, remote-sensing and machine-learning based time-series of atmospheric and land-cover dynamics, spatially explicit simulation modeling and analytical database management. The integration of the heterogeneous data will be implemented in a user oriented database infrastructure and scientific workflow system. Accessible via web-based interfaces, this database and analysis system will allow scientists to manage and analyze monitoring data and scenario computations, as well as allow stakeholders (e. g. land users, policy makers) to retrieve current ecosystem information and seasonal outlooks. We present the concept of the project and show preliminary results of the realization steps towards the integrative savanna management and decision-support system.

Integrated Visualization Environment for Science Mission Modeling, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — NASA is emphasizing the use of larger, more integrated models in conjunction with systems engineering tools and decision support systems. These tools place a...

From information processing to decisions: Formalizing and comparing psychologically plausible choice models.

Science.gov (United States)

Heck, Daniel W; Hilbig, Benjamin E; Moshagen, Morten

2017-08-01

Decision strategies explain how people integrate multiple sources of information to make probabilistic inferences. In the past decade, increasingly sophisticated methods have been developed to determine which strategy explains decision behavior best. We extend these efforts to test psychologically more plausible models (i.e., strategies), including a new, probabilistic version of the take-the-best (TTB) heuristic that implements a rank order of error probabilities based on sequential processing. Within a coherent statistical framework, deterministic and probabilistic versions of TTB and other strategies can directly be compared using model selection by minimum description length or the Bayes factor. In an experiment with inferences from given information, only three of 104 participants were best described by the psychologically plausible, probabilistic version of TTB. Similar as in previous studies, most participants were classified as users of weighted-additive, a strategy that integrates all available information and approximates rational decisions. Copyright © 2017 Elsevier Inc. All rights reserved.

Consequence Based Design. An approach for integrating computational collaborative models (Integrated Dynamic Models) in the building design phase

DEFF Research Database (Denmark)

Negendahl, Kristoffer

relies on various advancements in the area of integrated dynamic models. It also relies on the application and test of the approach in practice to evaluate the Consequence based design and the use of integrated dynamic models. As a result, the Consequence based design approach has been applied in five...... and define new ways to implement integrated dynamic models for the following project. In parallel, seven different developments of new methods, tools and algorithms have been performed to support the application of the approach. The developments concern: Decision diagrams – to clarify goals and the ability...... affect the design process and collaboration between building designers and simulationists. Within the limits of applying the approach of Consequence based design to five case studies, followed by documentation based on interviews, surveys and project related documentations derived from internal reports...

Development of an integrated decision support system to aid cognitive activities of operators

International Nuclear Information System (INIS)

Lee, Seung Jun; Seong, Poong Hyun

2007-01-01

As digital and computer technologies have grown, Human-Machine Interfaces (HMIs) have evolved. In safety-critical systems, especially in Nuclear Power Plants (NPPs), HMIs are important for reducing operational costs, the number of necessary operators, and the probability of accident occurrence. Efforts have been made to improve Main Control Room (MCR) interface design and to develop automated or decision support systems to ensure convenient operation and maintenance. In this paper, an integrated decision support system to aid operator cognitive processes is proposed for advanced MCRs of future NPPs. This work suggests the design concept of a decision support system which accounts for an operator's cognitive processes. The proposed system supports not only a particular task, but also the entire operation process based on a human cognitive process model. In this paper, the operator's operation processes are analyzed according to a human cognitive process model and appropriate support systems that support each cognitive process activity are suggested

Integrated analysis for population estimation, management impact evaluation, and decision-making for a declining species

Science.gov (United States)

Crawford, Brian A.; Moore, Clinton; Norton, Terry M.; Maerz, John C.

2018-01-01

A challenge for making conservation decisions is predicting how wildlife populations respond to multiple, concurrent threats and potential management strategies, usually under substantial uncertainty. Integrated modeling approaches can improve estimation of demographic rates necessary for making predictions, even for rare or cryptic species with sparse data, but their use in management applications is limited. We developed integrated models for a population of diamondback terrapins (Malaclemys terrapin) impacted by road-associated threats to (i) jointly estimate demographic rates from two mark-recapture datasets, while directly estimating road mortality and the impact of management actions deployed during the study; and (ii) project the population using population viability analysis under simulated management strategies to inform decision-making. Without management, population extirpation was nearly certain due to demographic impacts of road mortality, predators, and vegetation. Installation of novel flashing signage increased survival of terrapins that crossed roads by 30%. Signage, along with small roadside barriers installed during the study, increased population persistence probability, but the population was still predicted to decline. Management strategies that included actions targeting multiple threats and demographic rates resulted in the highest persistence probability, and roadside barriers, which increased adult survival, were predicted to increase persistence more than other actions. Our results support earlier findings showing mitigation of multiple threats is likely required to increase the viability of declining populations. Our approach illustrates how integrated models may be adapted to use limited data efficiently, represent system complexity, evaluate impacts of threats and management actions, and provide decision-relevant information for conservation of at-risk populations.

Integrated Environmental Modelling: Human decisions, human challenges

Science.gov (United States)

Glynn, Pierre D.

2015-01-01

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

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

African Journals Online (AJOL)

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

Coping with Complex Environmental and Societal Flood Risk Management Decisions: An Integrated Multi-criteria Framework

Directory of Open Access Journals (Sweden)

Love Ekenberg

2011-08-01

Full Text Available During recent years, a great deal of attention has been focused on the financial risk management of natural disasters. One reason behind is that the economic losses from floods, windstorms, earthquakes and other disasters in both the developing and developed countries are escalating dramatically. It has become apparent that an integrated water resource management approach would be beneficial in order to take both the best interests of society and of the environment into consideration. One improvement consists of models capable of handling multiple criteria (conflicting objectives as well as multiple stakeholders (conflicting interests. A systems approach is applied for coping with complex environmental and societal risk management decisions with respect to flood catastrophe policy formation, wherein the emphasis is on computer-based modeling and simulation techniques combined with methods for evaluating strategies where numerous stakeholders are incorporated in the process. The resulting framework consists of a simulation model, a decision analytical tool, and a set of suggested policy strategies for policy formulation. The framework will aid decision makers with high risk complex environmental decisions subject to significant uncertainties.

Integrating Water Quality and River Rehabilitation Management - A Decision-Analytical Perspective

Science.gov (United States)

Reichert, P.; Langhans, S.; Lienert, J.; Schuwirth, N.

2009-04-01

Integrative river management involves difficult decisions about alternative measures to improve their ecological state. For this reason, it seems useful to apply knowledge from the decision sciences to support river management. We discuss how decision-analytical elements can be employed for designing an integrated river management procedure. An important aspect of this procedure is to clearly separate scientific predictions of the consequences of alternatives from objectives to be achieved by river management. The key elements of the suggested procedure are (i) the quantitative elicitation of the objectives from different stakeholder groups, (ii) the compilation of the current scientific knowledge about the consequences of the effects resulting from suggested measures in the form of a probabilistic mathematical model, and (iii) the use of these predictions and valuations to prioritize alternatives, to uncover conflicting objectives, to support the design of better alternatives, and to improve the transparency of communication about the chosen management strategy. The development of this procedure led to insights regarding necessary steps to be taken for rational decision-making in river management, to guidelines about the use of decision-analytical techniques for performing these steps, but also to new insights about the application of decision-analytical techniques in general. In particular, the consideration of the spatial distribution of the effects of measures and the potential added value of connected rehabilitated river reaches leads to favoring measures that have a positive effect beyond a single river reach. As these effects only propagate within the river network, this results in a river basin oriented management concept as a consequence of a rational decision support procedure, rather than as an a priori management paradigm. There are also limitations to the support that can be expected from the decision-analytical perspective. It will not provide the

Integrated assessment models of global climate change

International Nuclear Information System (INIS)

Parson, E.A.; Fisher-Vanden, K.

1997-01-01

The authors review recent work in the integrated assessment modeling of global climate change. This field has grown rapidly since 1990. Integrated assessment models seek to combine knowledge from multiple disciplines in formal integrated representations; inform policy-making, structure knowledge, and prioritize key uncertainties; and advance knowledge of broad system linkages and feedbacks, particularly between socio-economic and bio-physical processes. They may combine simplified representations of the socio-economic determinants of greenhouse gas emissions, the atmosphere and oceans, impacts on human activities and ecosystems, and potential policies and responses. The authors summarize current projects, grouping them according to whether they emphasize the dynamics of emissions control and optimal policy-making, uncertainty, or spatial detail. They review the few significant insights that have been claimed from work to date and identify important challenges for integrated assessment modeling in its relationships to disciplinary knowledge and to broader assessment seeking to inform policy- and decision-making. 192 refs., 2 figs

The Importance Of Integrating Narrative Into Health Care Decision Making.

Science.gov (United States)

Dohan, Daniel; Garrett, Sarah B; Rendle, Katharine A; Halley, Meghan; Abramson, Corey

2016-04-01

When making health care decisions, patients and consumers use data but also gather stories from family and friends. When advising patients, clinicians consult the medical evidence but also use professional judgment. These stories and judgments, as well as other forms of narrative, shape decision making but remain poorly understood. Furthermore, qualitative research methods to examine narrative are rarely included in health science research. We illustrate how narratives shape decision making and explain why it is difficult but necessary to integrate qualitative research on narrative into the health sciences. We draw on social-scientific insights on rigorous qualitative research and our ongoing studies of decision making by patients with cancer, and we describe new tools and approaches that link qualitative research findings with the predominantly quantitative health science scholarship. Finally, we highlight the benefits of more fully integrating qualitative research and narrative analysis into the medical evidence base and into evidence-based medical practice. Project HOPE—The People-to-People Health Foundation, Inc.

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 ...

An Integrated Model of Decision-Making in Health Contexts: The Role of Science Education in Health Education

Science.gov (United States)

Arnold, Julia C.

2018-01-01

Health education is to foster health literacy, informed decision-making and to promote health behaviour. To date, there are several models that seek to explain health behaviour (e.g. the Theory of Planned Behaviour or the Health Belief Model). These models include motivational factors (expectancies and values) that play a role in decision-making…

Toward an operational model of decision making, emotional regulation, and mental health impact.

Science.gov (United States)

Collura, Thomas Francis; Zalaquett, Ronald P; Bonnstetter, Carlos Joyce; Chatters, Seria J

2014-01-01

Current brain research increasingly reveals the underlying mechanisms and processes of human behavior, cognition, and emotion. In addition to being of interest to a wide range of scientists, educators, and professionals, as well as laypeople, brain-based models are of particular value in a clinical setting. Psychiatrists, psychologists, counselors, and other mental health professionals are in need of operational models that integrate recent findings in the physical, cognitive, and emotional domains, and offer a common language for interdisciplinary understanding and communication. Based on individual traits, predispositions, and responses to stimuli, we can begin to identify emotional and behavioral pathways and mental processing patterns. The purpose of this article is to present a brain-path activation model to understand individual differences in decision making and psychopathology. The first section discusses the role of frontal lobe electroencephalography (EEG) asymmetry, summarizes state- and trait-based models of decision making, and provides a more complex analysis that supplements the traditional simple left-right brain model. Key components of the new model are the introduction of right hemisphere parallel and left hemisphere serial scanning in rendering decisions, and the proposition of pathways that incorporate both past experiences as well as future implications into the decision process. Main attributes of each decision-making mechanism are provided. The second section applies the model within the realm of clinical mental health as a tool to understand specific human behavior and pathology. Applications include general and chronic anxiety, depression, paranoia, risk taking, and the pathways employed when well-functioning operational integration is observed. Finally, specific applications such as meditation and mindfulness are offered to facilitate positive functioning.

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).

Dual Criteria Decisions

DEFF Research Database (Denmark)

Andersen, Steffen; Harrison, Glenn W.; Lau, Morten Igel

2014-01-01

The most popular models of decision making use a single criterion to evaluate projects or lotteries. However, decision makers may actually consider multiple criteria when evaluating projects. We consider a dual criteria model from psychology. This model integrates the familiar tradeoffs between...... to the clear role that income thresholds play in such decision making, but does not rule out a role for tradeoffs between risk and utility or probability weighting....

Crisis Decision Making Through a Shared Integrative Negotiation Mental Model

NARCIS (Netherlands)

Van Santen, W.; Jonker, C.M.; Wijngaards, N.

2009-01-01

Decision making during crises takes place in (multi-agency) teams, in a bureaucratic political context. As a result, the common notion that during crises decision making should be done in line with a Command & Control structure is invalid. This paper shows that the best way for crisis decision

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.

Decision-Making Theories and Models: A Discussion of Rational and Psychological Decision-Making Theories and Models: The Search for a Cultural-Ethical Decision-Making Model

OpenAIRE

Oliveira, Arnaldo

2007-01-01

This paper examines rational and psychological decision-making models. Descriptive and normative methodologies such as attribution theory, schema theory, prospect theory, ambiguity model, game theory, and expected utility theory are discussed. The definition of culture is reviewed, and the relationship between culture and decision making is also highlighted as many organizations use a cultural-ethical decision-making model.

A model for optimization of process integration investments under uncertainty

International Nuclear Information System (INIS)

Svensson, Elin; Stroemberg, Ann-Brith; Patriksson, Michael

2011-01-01

The long-term economic outcome of energy-related industrial investment projects is difficult to evaluate because of uncertain energy market conditions. In this article, a general, multistage, stochastic programming model for the optimization of investments in process integration and industrial energy technologies is proposed. The problem is formulated as a mixed-binary linear programming model where uncertainties are modelled using a scenario-based approach. The objective is to maximize the expected net present value of the investments which enables heat savings and decreased energy imports or increased energy exports at an industrial plant. The proposed modelling approach enables a long-term planning of industrial, energy-related investments through the simultaneous optimization of immediate and later decisions. The stochastic programming approach is also suitable for modelling what is possibly complex process integration constraints. The general model formulation presented here is a suitable basis for more specialized case studies dealing with optimization of investments in energy efficiency. -- Highlights: → Stochastic programming approach to long-term planning of process integration investments. → Extensive mathematical model formulation. → Multi-stage investment decisions and scenario-based modelling of uncertain energy prices. → Results illustrate how investments made now affect later investment and operation opportunities. → Approach for evaluation of robustness with respect to variations in probability distribution.

A decision support model for investment on P2P lending platform.

Science.gov (United States)

Zeng, Xiangxiang; Liu, Li; Leung, Stephen; Du, Jiangze; Wang, Xun; Li, Tao

2017-01-01

Peer-to-peer (P2P) lending, as a novel economic lending model, has triggered new challenges on making effective investment decisions. In a P2P lending platform, one lender can invest N loans and a loan may be accepted by M investors, thus forming a bipartite graph. Basing on the bipartite graph model, we built an iteration computation model to evaluate the unknown loans. To validate the proposed model, we perform extensive experiments on real-world data from the largest American P2P lending marketplace-Prosper. By comparing our experimental results with those obtained by Bayes and Logistic Regression, we show that our computation model can help borrowers select good loans and help lenders make good investment decisions. Experimental results also show that the Logistic classification model is a good complement to our iterative computation model, which motivates us to integrate the two classification models. The experimental results of the hybrid classification model demonstrate that the logistic classification model and our iteration computation model are complementary to each other. We conclude that the hybrid model (i.e., the integration of iterative computation model and Logistic classification model) is more efficient and stable than the individual model alone.

A decision support model for investment on P2P lending platform.

Directory of Open Access Journals (Sweden)

Xiangxiang Zeng

Full Text Available Peer-to-peer (P2P lending, as a novel economic lending model, has triggered new challenges on making effective investment decisions. In a P2P lending platform, one lender can invest N loans and a loan may be accepted by M investors, thus forming a bipartite graph. Basing on the bipartite graph model, we built an iteration computation model to evaluate the unknown loans. To validate the proposed model, we perform extensive experiments on real-world data from the largest American P2P lending marketplace-Prosper. By comparing our experimental results with those obtained by Bayes and Logistic Regression, we show that our computation model can help borrowers select good loans and help lenders make good investment decisions. Experimental results also show that the Logistic classification model is a good complement to our iterative computation model, which motivates us to integrate the two classification models. The experimental results of the hybrid classification model demonstrate that the logistic classification model and our iteration computation model are complementary to each other. We conclude that the hybrid model (i.e., the integration of iterative computation model and Logistic classification model is more efficient and stable than the individual model alone.

Uncertainty management in integrated modelling, the IMAGE case

International Nuclear Information System (INIS)

Van der Sluijs, J.P.

1995-01-01

Integrated assessment models of global environmental problems play an increasingly important role in decision making. This use demands a good insight regarding the reliability of these models. In this paper we analyze uncertainty management in the IMAGE-project (Integrated Model to Assess the Greenhouse Effect). We use a classification scheme comprising type and source of uncertainty. Our analysis shows reliability analysis as main area for improvement. We briefly review a recently developed methodology, NUSAP (Numerical, Unit, Spread, Assessment and Pedigree), that systematically addresses the strength of data in terms of spread, reliability and scientific status (pedigree) of information. This approach is being tested through interviews with model builders. 3 tabs., 20 refs

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.

Sampling and assessment accuracy in mate choice: a random-walk model of information processing in mating decision.

Science.gov (United States)

Castellano, Sergio; Cermelli, Paolo

2011-04-07

Mate choice depends on mating preferences and on the manner in which mate-quality information is acquired and used to make decisions. We present a model that describes how these two components of mating decision interact with each other during a comparative evaluation of prospective mates. The model, with its well-explored precedents in psychology and neurophysiology, assumes that decisions are made by the integration over time of noisy information until a stopping-rule criterion is reached. Due to this informational approach, the model builds a coherent theoretical framework for developing an integrated view of functions and mechanisms of mating decisions. From a functional point of view, the model allows us to investigate speed-accuracy tradeoffs in mating decision at both population and individual levels. It shows that, under strong time constraints, decision makers are expected to make fast and frugal decisions and to optimally trade off population-sampling accuracy (i.e. the number of sampled males) against individual-assessment accuracy (i.e. the time spent for evaluating each mate). From the proximate-mechanism point of view, the model makes testable predictions on the interactions of mating preferences and choosiness in different contexts and it might be of compelling empirical utility for a context-independent description of mating preference strength. Copyright © 2011 Elsevier Ltd. All rights reserved.

Chaotic Feedback Loops within Decision Making Groups: Towards an Integration of Chaos Theory and Cybernetics.

Science.gov (United States)

Keaten, James A.

This paper offers a model that integrates chaos theory and cybernetics, which can be used to describe the structure of decision making within small groups. The paper begins with an overview of cybernetics and chaos. Definitional characteristics of cybernetics are reviewed along with salient constructs, such as goal-seeking, feedback, feedback…

A novel personal health system with integrated decision support and guidance for the management of chronic liver disease.

Science.gov (United States)

Kiefer, Stephan; Schäfer, Michael; Bransch, Marco; Brimmers, Peter; Bartolomé, Diego; Baños, Janie; Orr, James; Jones, Dave; Jara, Maximilian; Stockmann, Martin

2014-01-01

A personal health system platform for the management of patients with chronic liver disease that incorporates a novel approach to integrate decision support and guidance through care pathways for patients and their doctors is presented in this paper. The personal health system incorporates an integrated decision support engine that guides patients and doctors through the management of the disease by issuing tasks and providing recommendations to both the care team and the patient and by controlling the execution of a Care Flow Plan based on the results of tasks and the monitored health status of the patient. This Care Flow Plan represents a formal, business process based model of disease management designed off-line by domain experts on the basis of clinical guidelines, knowledge of care pathways and an organisational model for integrated, patient-centred care. In this way, remote monitoring and treatment are dynamically adapted to the patient's actual condition and clinical symptoms and allow flexible delivery of care with close integration of specialists, therapists and care-givers.

System dynamics models as decision-making tools in agritourism

Directory of Open Access Journals (Sweden)

Jere Jakulin Tadeja

2016-12-01

Full Text Available Agritourism as a type of niche tourism is a complex and softly defined phaenomenon. The demands for fast and integrated decision regarding agritourism and its interconnections with environment, economy (investments, traffic and social factors (tourists is urgent. Many different methodologies and methods master softly structured questions and dilemmas with global and local properties. Here we present methods of systems thinking and system dynamics, which were first brought into force in the educational and training area in the form of different computer simulations and later as tools for decision-making and organisational re-engineering. We develop system dynamics models in order to present accuracy of methodology. These models are essentially simple and can serve only as describers of the activity of basic mutual influences among variables. We will pay the attention to the methodology for parameter model values determination and the so-called mental model. This one is the basis of causal connections among model variables. At the end, we restore a connection between qualitative and quantitative models in frame of system dynamics.

The systems integration modeling system

International Nuclear Information System (INIS)

Danker, W.J.; Williams, J.R.

1990-01-01

This paper discusses the systems integration modeling system (SIMS), an analysis tool for the detailed evaluation of the structure and related performance of the Federal Waste Management System (FWMS) and its interface with waste generators. It's use for evaluations in support of system-level decisions as to FWMS configurations, the allocation, sizing, balancing and integration of functions among elements, and the establishment of system-preferred waste selection and sequencing methods and other operating strategies is presented. SIMS includes major analysis submodels which quantify the detailed characteristics of individual waste items, loaded casks and waste packages, simulate the detailed logistics of handling and processing discrete waste items and packages, and perform detailed cost evaluations

Integrating information for better environmental decisions.

Energy Technology Data Exchange (ETDEWEB)

MacDonell, M.; Morgan, K.; Newland, L.; Environmental Assessment; Texas Christian Univ.

2002-01-01

As more is learned about the complex nature and extent of environmental impacts from progressive human disturbance, scientists, policy analysts, decision makers, educators, and communicators are increasingly joining forces to develop strategies for preserving and protecting the environment. The Eco-Informa Foundation is an educational scientific organization dedicated to promoting the collaborative development and sharing of scientific information. The Foundation participated in a recent international conference on environmental informatics through a special symposium on integrating information for better environmental decisions. Presentations focused on four general themes: (1) remote sensing and data interpretation, including through new knowledge management tools; (2) risk assessment and communication, including for radioactively contaminated facilities, introduced biological hazards, and food safety; (3) community involvement in cleanup projects; and (4) environmental education. The general context for related issues, methods and applications, and results and recommendations from those discussions are highlighted here.

Decision-making and environmental impacts

OpenAIRE

Elmquist, Helena; Lindgren, Urban; Mäkilä, Kalle

2004-01-01

This report describes an interdisciplinary study combining social sciences and natural sciences in an integrated simulation model. The integrated dynamic simulation model consists of the interplay between the decision-making farmer, the physical flows at the farm and the structural conditions that influence the business. The central question studied here concerned the energy use, environmental impacts and business economics of various decision models in comparison to different levels of envir...

Integrative modelling of the influence of MAPK network on cancer cell fate decision.

Directory of Open Access Journals (Sweden)

Luca Grieco

2013-10-01

Full Text Available The Mitogen-Activated Protein Kinase (MAPK network consists of tightly interconnected signalling pathways involved in diverse cellular processes, such as cell cycle, survival, apoptosis and differentiation. Although several studies reported the involvement of these signalling cascades in cancer deregulations, the precise mechanisms underlying their influence on the balance between cell proliferation and cell death (cell fate decision in pathological circumstances remain elusive. Based on an extensive analysis of published data, we have built a comprehensive and generic reaction map for the MAPK signalling network, using CellDesigner software. In order to explore the MAPK responses to different stimuli and better understand their contributions to cell fate decision, we have considered the most crucial components and interactions and encoded them into a logical model, using the software GINsim. Our logical model analysis particularly focuses on urinary bladder cancer, where MAPK network deregulations have often been associated with specific phenotypes. To cope with the combinatorial explosion of the number of states, we have applied novel algorithms for model reduction and for the compression of state transition graphs, both implemented into the software GINsim. The results of systematic simulations for different signal combinations and network perturbations were found globally coherent with published data. In silico experiments further enabled us to delineate the roles of specific components, cross-talks and regulatory feedbacks in cell fate decision. Finally, tentative proliferative or anti-proliferative mechanisms can be connected with established bladder cancer deregulations, namely Epidermal Growth Factor Receptor (EGFR over-expression and Fibroblast Growth Factor Receptor 3 (FGFR3 activating mutations.

An integrated Markov decision process and nested logit consumer response model of air ticket pricing

NARCIS (Netherlands)

Lu, J.; Feng, T.; Timmermans, H.P.J.; Yang, Z.

2017-01-01

The paper attempts to propose an optimal air ticket pricing model during the booking horizon by taking into account passengers' purchasing behavior of air tickets. A Markov decision process incorporating a nested logit consumer response model is established to modeling the dynamic pricing process.

Greenhouse gas emissions control in integrated municipal solid waste management through mixed integer bilevel decision-making

Energy Technology Data Exchange (ETDEWEB)

He, Li, E-mail: li.he@iseis.org [MOE Key Laboratory of Regional Energy Systems Optimization, S and C Academy of Energy and Environmental Research, North China Electric Power University, Beijing 102206 (China); Huang, G.H.; Lu, Hongwei [MOE Key Laboratory of Regional Energy Systems Optimization, S and C Academy of Energy and Environmental Research, North China Electric Power University, Beijing 102206 (China)

2011-10-15

Highlights: {yields} We used bilevel analysis to treat two objectives at different levels. {yields} The model can identify allocation schemes for waste flows. {yields} The model can support waste timing, sizing, and siting for facility expansions. {yields} The model can estimate minimized total management cost and GHG emissions. - Abstract: Recent studies indicated that municipal solid waste (MSW) is a major contributor to global warming due to extensive emissions of greenhouse gases (GHGs). However, most of them focused on investigating impacts of MSW on GHG emission amounts. This study presents two mixed integer bilevel decision-making models for integrated municipal solid waste management and GHG emissions control: MGU-MCL and MCU-MGL. The MGU-MCL model represents a top-down decision process, with the environmental sectors at the national level dominating the upper-level objective and the waste management sectors at the municipal level providing the lower-level objective. The MCU-MGL model implies a bottom-up decision process where municipality plays a leading role. Results from the models indicate that: the top-down decisions would reduce metric tonne carbon emissions (MTCEs) by about 59% yet increase about 8% of the total management cost; the bottom-up decisions would reduce MTCE emissions by about 13% but increase the total management cost very slightly; on-site monitoring and downscaled laboratory experiments are still required for reducing uncertainty in GHG emission rate from the landfill facility.

A preference aggregation model and application in AHP-group decision making

Science.gov (United States)

Yang, Taiyi; Yang, De; Chao, Xiangrui

2018-04-01

Group decision making process integrate individual preferences to obtain the group preference by applying aggregation rules and preference relations. The two most useful approaches, the aggregation of individual judgements and the aggregation of individual priorities, traditionally are employed in the Analytic Hierarchy Process to deal with group decision making problems. In both cases, it is assumed that the group preference is approximate weighted mathematical expectation of individual judgements and individual priorities. We propose new preference aggregation methods using optimization models in order to obtain group preference which is close to all individual priorities. Some illustrative examples are finally examined to demonstrate proposed models for application.

Elite Decision Makers’ Strategic Use of European Integration and Globalisation Discourses

DEFF Research Database (Denmark)

Lynggaard, Kennet

2013-01-01

This article investigates decision makers’ strategic use of European integration and globalisation discourses to justify and coordinate national sector reforms. This is done using the example of banking sector reforms in two small European Union (EU) member states, Ireland and Denmark. Two key...... in line with European integration measures, even in the absence of national commitment to the latter. Discourses of globalisation have thus become ‘the last resort’ for Danish decision makers in justifying and coordinating reforms that are in line with EU regulations and recommendations....

Creating a process for incorporating epidemiological modelling into outbreak management decisions.

Science.gov (United States)

Akselrod, Hana; Mercon, Monica; Kirkeby Risoe, Petter; Schlegelmilch, Jeffrey; McGovern, Joanne; Bogucki, Sandy

2012-01-01

Modern computational models of infectious diseases greatly enhance our ability to understand new infectious threats and assess the effects of different interventions. The recently-released CDC Framework for Preventing Infectious Diseases calls for increased use of predictive modelling of epidemic emergence for public health preparedness. Currently, the utility of these technologies in preparedness and response to outbreaks is limited by gaps between modelling output and information requirements for incident management. The authors propose an operational structure that will facilitate integration of modelling capabilities into action planning for outbreak management, using the Incident Command System (ICS) and Synchronization Matrix framework. It is designed to be adaptable and scalable for use by state and local planners under the National Response Framework (NRF) and Emergency Support Function #8 (ESF-8). Specific epidemiological modelling requirements are described, and integrated with the core processes for public health emergency decision support. These methods can be used in checklist format to align prospective or real-time modelling output with anticipated decision points, and guide strategic situational assessments at the community level. It is anticipated that formalising these processes will facilitate translation of the CDC's policy guidance from theory to practice during public health emergencies involving infectious outbreaks.

Modeling integrated water user decisions in intermittent supply systems

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

2007-07-01

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

Interval-Valued Intuitionistic Fuzzy Multicriteria Group Decision Making Based on VIKOR and Choquet Integral

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Chunqiao Tan

2013-01-01

Full Text Available An effective decision making approach based on VIKOR and Choquet integral is developed to solve multicriteria group decision making problem with conflicting criteria and interdependent subjective preference of decision makers in a fuzzy environment where preferences of decision makers with respect to criteria are represented by interval-valued intuitionistic fuzzy sets. First, an interval-valued intuitionistic fuzzy Choquet integral operator is given. Some of its properties are investigated in detail. The extended VIKOR decision procedure based on the proposed operator is developed for solving the multicriteria group decision making problem where the interactive criteria weight is measured by Shapley value. An illustrative example is given for demonstrating the applicability of the proposed decision procedure for solving the multi-criteria group decision making problem in interval-valued intuitionistic fuzzy environment.

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

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Christian Klaes

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

Categorization = Decision Making + Generalization

Science.gov (United States)

Seger, Carol A; Peterson, Erik J.

2013-01-01

We rarely, if ever, repeatedly encounter exactly the same situation. This makes generalization crucial for real world decision making. We argue that categorization, the study of generalizable representations, is a type of decision making, and that categorization learning research would benefit from approaches developed to study the neuroscience of decision making. Similarly, methods developed to examine generalization and learning within the field of categorization may enhance decision making research. We first discuss perceptual information processing and integration, with an emphasis on accumulator models. We then examine learning the value of different decision making choices via experience, emphasizing reinforcement learning modeling approaches. Next we discuss how value is combined with other factors in decision making, emphasizing the effects of uncertainty. Finally, we describe how a final decision is selected via thresholding processes implemented by the basal ganglia and related regions. We also consider how memory related functions in the hippocampus may be integrated with decision making mechanisms and contribute to categorization. PMID:23548891

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.

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

Science.gov (United States)

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

2012-12-01

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

SCOPE – An Integrated Framework for Multi-Attribute Decision Making

DEFF Research Database (Denmark)

Leleur, Steen

2004-01-01

that are supported by a methodology of both a systemic and a systematic type. Specific use is made of operational research methods such as critical systems heuristics, scenario technique, stakeholder analysis and multi‐attribute decision making (MADM). To deal with issues of complexity and ambiguity, planning......This article presents an integrated framework for multi‐attribute decision making named SCOPE (System for Combined Planning and Evaluation) that was developed to assess infrastructure policy initiatives—in complex decision environments. The framework comprises scanning as well as assessment issues...

Gossip Management at Universities Using Big Data Warehouse Model Integrated with a Decision Support System

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Pelin Vardarlier

2016-01-01

Full Text Available Big Data has recently been used for many purposes like medicine, marketing and sports. It has helped improve management decisions. However, for almost each case a unique data warehouse should be built to benefit from the merits of data mining and Big Data. Hence, each time we start from scratch to form and build a Big Data Warehouse. In this study, we propose a Big Data Warehouse and a model for universities to be used for information management, to be more specific gossip management. The overall model is a decision support system that may help university administraitons when they are making decisions and also provide them with information or gossips being circulated among students and staff. In the model, unsupervised machine learning algorithms have been employed. A prototype of the proposed system has also been presented in the study. User generated data has been collected from students in order to learn gossips and students’ problems related to school, classes, staff and instructors. The findings and results of the pilot study suggest that social media messages among students may give important clues for the happenings at school and this information may be used for management purposes.The model may be developed and implemented by not only universities but also some other organisations.

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...

A decision model for E and P petroleum projects using real options and preference theory

Energy Technology Data Exchange (ETDEWEB)

Lima, Gabriel A.C. [Universidade Estadual de Campinas, SP (Brazil). Inst. de Geociencias. Lab. de Analise Geoconomica (LAGE); Suslick, Saul B. [Universidade Estadual de Campinas, SP (Brazil). Inst. de Geociencias. Centro de Estudo do Petroleo; Nepomuceno Filho, Francisco [PETROBRAS, Rio de Janeiro, RJ (Brazil)

2004-07-01

The results from Discounted Cash Flow (DCF) are limited as a tool for decision-making in the petroleum industry because they do not properly take into account three important features of the modern investments: uncertainty, irreversibility, timing and corporation's risk-aversion. Recent developments in real options and preference theories have allowed decision-makers to employ these two approaches separately in the process of valuation and decision-making of risky projects. This paper presents a model for valuation and decision-making integrating discounted cash flow, real options and reference theory. This model seems to be suitable to answer to the following questions: what is the current value of an oil project? what is the optimal working interest in this project venture?; what is criteria to select projects considering investment irreversibility, uncertainty and timing to implement decisions? This model is applied to valuation and decision-making of a project to produce oil from a deep-water reservoir and its results are compared to those of the traditional approach. NPV model suggest that, as the project value is above its investment cost, the corporation should invest immediately and take 100% working interest in the project. Contrarily, the integrated model suggest the corporation should invest as long as project current value is as large as 1.85 times investment cost and should take only 44.38% working interest, whereas partners fund and acquire the remaining 55,62% of the project. In general, results indicate that NPV tend to pay more attention on return and does not account properly for risk. Then, as the uncertainty or volatile of strategic variables increases, the two models give more divergent results. (author)

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

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Thomas eJahans-Price

2014-03-01

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

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.

Multi-criteria decision analysis integrated with GIS for radio ...

African Journals Online (AJOL)

Multi-criteria decision analysis integrated with GIS for radio astronomical observatory site selection in peninsular of Malaysia. R Umar, Z.Z. Abidin, Z.A. Ibrahim, M.K.A. Kamarudin, S.N. Hazmin, A Endut, H Juahir ...

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

The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Space Flight Medical Systems

Science.gov (United States)

Kerstman, Eric; Minard, Charles; Saile, Lynn; deCarvalho, Mary Freire; Myers, Jerry; Walton, Marlei; Butler, Douglas; Iyengar, Sriram; Johnson-Throop, Kathy; Baumann, David

2009-01-01

The Integrated Medical Model (IMM) is a decision support tool that is useful to mission planners and medical system designers in assessing risks and designing medical systems for space flight missions. The IMM provides an evidence based approach for optimizing medical resources and minimizing risks within space flight operational constraints. The mathematical relationships among mission and crew profiles, medical condition incidence data, in-flight medical resources, potential crew functional impairments, and clinical end-states are established to determine probable mission outcomes. Stochastic computational methods are used to forecast probability distributions of crew health and medical resource utilization, as well as estimates of medical evacuation and loss of crew life. The IMM has been used in support of the International Space Station (ISS) medical kit redesign, the medical component of the ISS Probabilistic Risk Assessment, and the development of the Constellation Medical Conditions List. The IMM also will be used to refine medical requirements for the Constellation program. The IMM outputs for ISS and Constellation design reference missions will be presented to demonstrate the potential of the IMM in assessing risks, planning missions, and designing medical systems. The implementation of the IMM verification and validation plan will be reviewed. Additional planned capabilities of the IMM, including optimization techniques and the inclusion of a mission timeline, will be discussed. Given the space flight constraints of mass, volume, and crew medical training, the IMM is a valuable risk assessment and decision support tool for medical system design and mission planning.

The neural substrate and functional integration of uncertainty in decision making: an information theory approach.

Science.gov (United States)

Goñi, Joaquín; Aznárez-Sanado, Maite; Arrondo, Gonzalo; Fernández-Seara, María; Loayza, Francis R; Heukamp, Franz H; Pastor, María A

2011-03-09

Decision making can be regarded as the outcome of cognitive processes leading to the selection of a course of action among several alternatives. Borrowing a central measurement from information theory, Shannon entropy, we quantified the uncertainties produced by decisions of participants within an economic decision task under different configurations of reward probability and time. These descriptors were used to obtain blood oxygen level-dependent (BOLD) signal correlates of uncertainty and two clusters codifying the Shannon entropy of task configurations were identified: a large cluster including parts of the right middle cingulate cortex (MCC) and left and right pre-supplementary motor areas (pre-SMA) and a small cluster at the left anterior thalamus. Subsequent functional connectivity analyses using the psycho-physiological interactions model identified areas involved in the functional integration of uncertainty. Results indicate that clusters mostly located at frontal and temporal cortices experienced an increased connectivity with the right MCC and left and right pre-SMA as the uncertainty was higher. Furthermore, pre-SMA was also functionally connected to a rich set of areas, most of them associative areas located at occipital and parietal lobes. This study provides a map of the human brain segregation and integration (i.e., neural substrate and functional connectivity respectively) of the uncertainty associated to an economic decision making paradigm.

Development of a descriptive model of an integrated information system to support complex, dynamic, distributed decision making for emergency management in large organisations

International Nuclear Information System (INIS)

Andersen, V.; Andersen, H.B.; Axel, E.; Petersen, T.

1990-01-01

A short introduction will be given to the European (ESPRIT II) project, ''IT Support for Emergency Management - ISEM''. The project is aimed at the development of an integrated information system capable of supporting the complex, dynamic, distributed decision making in the management of emergencies. The basic models developed to describe and construct emergency management organisations and their preparedness have been illustrated, and it has been stated that similarities may be found even in emergency situations that originally are of quite different nature. (author)

Integrating climate forecasts and natural gas supply information into a natural gas purchasing decision

Science.gov (United States)

Changnon, David; Ritsche, Michael; Elyea, Karen; Shelton, Steve; Schramm, Kevin

2000-09-01

This paper illustrates a key lesson related to most uses of long-range climate forecast information, namely that effective weather-related decision-making requires understanding and integration of weather information with other, often complex factors. Northern Illinois University's heating plant manager and staff meteorologist, along with a group of meteorology students, worked together to assess different types of available information that could be used in an autumn natural gas purchasing decision. Weather information assessed included the impact of ENSO events on winters in northern Illinois and the Climate Prediction Center's (CPC) long-range climate outlooks. Non-weather factors, such as the cost and available supplies of natural gas prior to the heating season, contribute to the complexity of the natural gas purchase decision. A decision tree was developed and it incorporated three parts: (a) natural gas supply levels, (b) the CPC long-lead climate outlooks for the region, and (c) an ENSO model developed for DeKalb. The results were used to decide in autumn whether to lock in a price or ride the market each winter. The decision tree was tested for the period 1995-99, and returned a cost-effective decision in three of the four winters.

Democracy and Environmental Integration in Decision-Making

DEFF Research Database (Denmark)

Figueroa, Maria

This dissertation presents an evaluation of the democratic qualities of decision-making processes for large transport infrastructure projects in two Scandinavian countries: Denmark and Sweden. The study uncovers criteria from aggregative and deliberative theories of democracy to create a qualitat......This dissertation presents an evaluation of the democratic qualities of decision-making processes for large transport infrastructure projects in two Scandinavian countries: Denmark and Sweden. The study uncovers criteria from aggregative and deliberative theories of democracy to create...... exemplify points of democratic strength and fragility in the decision processes. A robust system of participatory procedures exists, in both countries, as part of the planning tradition or as part of the legally mandatory environmental assessment procedures. This robust system shows fragility for government...... discourses to the state. While the role of civil society in deliberation is crucial, the study accepts that not all that goes on in civil society is conducive either to more democracy or greater environmental integration. The relevant discussion is then how to deal with differences that may have...

Review of Multi-Criteria Decision Aid for Integrated Sustainability Assessment of Urban Water Systems - MCEARD

Science.gov (United States)

Integrated sustainability assessment is part of a new paradigm for urban water decision making. Multi-criteria decision aid (MCDA) is an integrative framework used in urban water sustainability assessment, which has a particular focus on utilising stakeholder participation. Here ...

Integrated Traffic Flow Management Decision Making

Science.gov (United States)

Grabbe, Shon R.; Sridhar, Banavar; Mukherjee, Avijit

2009-01-01

A generalized approach is proposed to support integrated traffic flow management decision making studies at both the U.S. national and regional levels. It can consider tradeoffs between alternative optimization and heuristic based models, strategic versus tactical flight controls, and system versus fleet preferences. Preliminary testing was accomplished by implementing thirteen unique traffic flow management models, which included all of the key components of the system and conducting 85, six-hour fast-time simulation experiments. These experiments considered variations in the strategic planning look-ahead times, the replanning intervals, and the types of traffic flow management control strategies. Initial testing indicates that longer strategic planning look-ahead times and re-planning intervals result in steadily decreasing levels of sector congestion for a fixed delay level. This applies when accurate estimates of the air traffic demand, airport capacities and airspace capacities are available. In general, the distribution of the delays amongst the users was found to be most equitable when scheduling flights using a heuristic scheduling algorithm, such as ration-by-distance. On the other hand, equity was the worst when using scheduling algorithms that took into account the number of seats aboard each flight. Though the scheduling algorithms were effective at alleviating sector congestion, the tactical rerouting algorithm was the primary control for avoiding en route weather hazards. Finally, the modeled levels of sector congestion, the number of weather incursions, and the total system delays, were found to be in fair agreement with the values that were operationally observed on both good and bad weather days.

A New Group Decision Model Based on Grey-Intuitionistic Fuzzy-ELECTRE and VIKOR for Contractor Assessment Problem

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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.

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...

Comparative Analysis of Investment Decision Models

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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.

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

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

Science.gov (United States)

Sohl, Terry L.; Claggett, Peter

2013-01-01

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

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.

Decision making from economic and signal detection perspectives: development of an integrated framework

Science.gov (United States)

Lynn, Spencer K.; Wormwood, Jolie B.; Barrett, Lisa F.; Quigley, Karen S.

2015-01-01

Behavior is comprised of decisions made from moment to moment (i.e., to respond one way or another). Often, the decision maker cannot be certain of the value to be accrued from the decision (i.e., the outcome value). Decisions made under outcome value uncertainty form the basis of the economic framework of decision making. Behavior is also based on perception—perception of the external physical world and of the internal bodily milieu, which both provide cues that guide decision making. These perceptual signals are also often uncertain: another person's scowling facial expression may indicate threat or intense concentration, alternatives that require different responses from the perceiver. Decisions made under perceptual uncertainty form the basis of the signals framework of decision making. Traditional behavioral economic approaches to decision making focus on the uncertainty that comes from variability in possible outcome values, and typically ignore the influence of perceptual uncertainty. Conversely, traditional signal detection approaches to decision making focus on the uncertainty that arises from variability in perceptual signals and typically ignore the influence of outcome value uncertainty. Here, we compare and contrast the economic and signals frameworks that guide research in decision making, with the aim of promoting their integration. We show that an integrated framework can expand our ability to understand a wider variety of decision-making behaviors, in particular the complexly determined real-world decisions we all make every day. PMID:26217275

Moral and Ethical Decision Making

Science.gov (United States)

2007-07-01

rational ones (i.e. Kohlberg’s influential model of decision making ). However, non- rational elements, such as affect, risk perception, risk preference...dread or anxiety) play a strong role in many types of decisions , and that the addition of decision makers’ emotions to models of choice may make ...White, 1994) agree that emotions are an integral part of ethical decision making as well. Emotions arise in the context of interpersonal

Probabilistic inference under time pressure leads to a cortical-to-subcortical shift in decision evidence integration.

Science.gov (United States)

Oh-Descher, Hanna; Beck, Jeffrey M; Ferrari, Silvia; Sommer, Marc A; Egner, Tobias

2017-11-15

Real-life decision-making often involves combining multiple probabilistic sources of information under finite time and cognitive resources. To mitigate these pressures, people "satisfice", foregoing a full evaluation of all available evidence to focus on a subset of cues that allow for fast and "good-enough" decisions. Although this form of decision-making likely mediates many of our everyday choices, very little is known about the way in which the neural encoding of cue information changes when we satisfice under time pressure. Here, we combined human functional magnetic resonance imaging (fMRI) with a probabilistic classification task to characterize neural substrates of multi-cue decision-making under low (1500 ms) and high (500 ms) time pressure. Using variational Bayesian inference, we analyzed participants' choices to track and quantify cue usage under each experimental condition, which was then applied to model the fMRI data. Under low time pressure, participants performed near-optimally, appropriately integrating all available cues to guide choices. Both cortical (prefrontal and parietal cortex) and subcortical (hippocampal and striatal) regions encoded individual cue weights, and activity linearly tracked trial-by-trial variations in the amount of evidence and decision uncertainty. Under increased time pressure, participants adaptively shifted to using a satisficing strategy by discounting the least informative cue in their decision process. This strategic change in decision-making was associated with an increased involvement of the dopaminergic midbrain, striatum, thalamus, and cerebellum in representing and integrating cue values. We conclude that satisficing the probabilistic inference process under time pressure leads to a cortical-to-subcortical shift in the neural drivers of decisions. Copyright © 2017 Elsevier Inc. All rights reserved.

Modeling and Simulation of Handover Scheme in Integrated EPON-WiMAX Networks

DEFF Research Database (Denmark)

Yan, Ying; Dittmann, Lars

2011-01-01

In this paper, we tackle the seamless handover problem in integrated optical wireless networks. Our model applies for the convergence network of EPON and WiMAX and a mobilityaware signaling protocol is proposed. The proposed handover scheme, Integrated Mobility Management Scheme (IMMS), is assisted...... by enhancing the traditional MPCP signaling protocol, which cooperatively collects mobility information from the front-end wireless network and makes centralized bandwidth allocation decisions in the backhaul optical network. The integrated network architecture and the joint handover scheme are simulated using...... OPNET modeler. Results show validation of the protocol, i.e., integrated handover scheme gains better network performances....

Enabling Real-time Water Decision Support Services Using Model as a Service

Science.gov (United States)

Zhao, T.; Minsker, B. S.; Lee, J. S.; Salas, F. R.; Maidment, D. R.; David, C. H.

2014-12-01

Through application of computational methods and an integrated information system, data and river modeling services can help researchers and decision makers more rapidly understand river conditions under alternative scenarios. To enable this capability, workflows (i.e., analysis and model steps) are created and published as Web services delivered through an internet browser, including model inputs, a published workflow service, and visualized outputs. The RAPID model, which is a river routing model developed at University of Texas Austin for parallel computation of river discharge, has been implemented as a workflow and published as a Web application. This allows non-technical users to remotely execute the model and visualize results as a service through a simple Web interface. The model service and Web application has been prototyped in the San Antonio and Guadalupe River Basin in Texas, with input from university and agency partners. In the future, optimization model workflows will be developed to link with the RAPID model workflow to provide real-time water allocation decision support services.

Evaluation of End-Products in Architecture Design Process: A Fuzzy Decision-Making Model

Directory of Open Access Journals (Sweden)

Serkan PALABIYIK

2012-06-01

Full Text Available This paper presents a study on the development of a fuzzy multi-criteria decision-making model for the evaluation of end products of the architectural design process. Potentials of the developed model were investigated within the scope of architectural design education, specifically an international design studio titled “Design for Disassembly and Reuse: Design & Building Multipurpose Transformable Pavilions.” The studio work followed a design process that integrated systematic and heuristic thinking. The design objectives and assessment criteria were clearly set out at the beginning of the process by the studio coordinator with the aim of narrowing the design space and increasing awareness of the consequences of design decisions. At the end of the design process, designs produced in the studio were evaluated using the developed model to support decision making. The model facilitated the identification of positive and negative aspects of the designs and selection of the design alternative that best met the studio objectives set at the beginning.

The neural substrate and functional integration of uncertainty in decision making: an information theory approach.

Directory of Open Access Journals (Sweden)

Joaquín Goñi

Full Text Available Decision making can be regarded as the outcome of cognitive processes leading to the selection of a course of action among several alternatives. Borrowing a central measurement from information theory, Shannon entropy, we quantified the uncertainties produced by decisions of participants within an economic decision task under different configurations of reward probability and time. These descriptors were used to obtain blood oxygen level-dependent (BOLD signal correlates of uncertainty and two clusters codifying the Shannon entropy of task configurations were identified: a large cluster including parts of the right middle cingulate cortex (MCC and left and right pre-supplementary motor areas (pre-SMA and a small cluster at the left anterior thalamus. Subsequent functional connectivity analyses using the psycho-physiological interactions model identified areas involved in the functional integration of uncertainty. Results indicate that clusters mostly located at frontal and temporal cortices experienced an increased connectivity with the right MCC and left and right pre-SMA as the uncertainty was higher. Furthermore, pre-SMA was also functionally connected to a rich set of areas, most of them associative areas located at occipital and parietal lobes. This study provides a map of the human brain segregation and integration (i.e., neural substrate and functional connectivity respectively of the uncertainty associated to an economic decision making paradigm.

System and method for integrating hazard-based decision making tools and processes

Science.gov (United States)

Hodgin, C Reed [Westminster, CO

2012-03-20

A system and method for inputting, analyzing, and disseminating information necessary for identified decision-makers to respond to emergency situations. This system and method provides consistency and integration among multiple groups, and may be used for both initial consequence-based decisions and follow-on consequence-based decisions. The system and method in a preferred embodiment also provides tools for accessing and manipulating information that are appropriate for each decision-maker, in order to achieve more reasoned and timely consequence-based decisions. The invention includes processes for designing and implementing a system or method for responding to emergency situations.

An Integrated Web-based Decision Support System in Disaster Risk Management

Science.gov (United States)

Aye, Z. C.; Jaboyedoff, M.; Derron, M. H.

2012-04-01

Nowadays, web based decision support systems (DSS) play an essential role in disaster risk management because of their supporting abilities which help the decision makers to improve their performances and make better decisions without needing to solve complex problems while reducing human resources and time. Since the decision making process is one of the main factors which highly influence the damages and losses of society, it is extremely important to make right decisions at right time by combining available risk information with advanced web technology of Geographic Information System (GIS) and Decision Support System (DSS). This paper presents an integrated web-based decision support system (DSS) of how to use risk information in risk management efficiently and effectively while highlighting the importance of a decision support system in the field of risk reduction. Beyond the conventional systems, it provides the users to define their own strategies starting from risk identification to the risk reduction, which leads to an integrated approach in risk management. In addition, it also considers the complexity of changing environment from different perspectives and sectors with diverse stakeholders' involvement in the development process. The aim of this platform is to contribute a part towards the natural hazards and geosciences society by developing an open-source web platform where the users can analyze risk profiles and make decisions by performing cost benefit analysis, Environmental Impact Assessment (EIA) and Strategic Environmental Assessment (SEA) with the support of others tools and resources provided. There are different access rights to the system depending on the user profiles and their responsibilities. The system is still under development and the current version provides maps viewing, basic GIS functionality, assessment of important infrastructures (e.g. bridge, hospital, etc.) affected by landslides and visualization of the impact

PROCESSING THE INFORMATION CONTENT ON THE BASIS OF FUZZY NEURAL MODEL OF DECISION MAKING

Directory of Open Access Journals (Sweden)

Nina V. Komleva

2013-01-01

Full Text Available The article is devoted to the issues of mathematical modeling of the decision-making process of information content processing based on the fuzzy neural network TSK. Integral rating assessment of the content, which is necessary for taking a decision about its further usage, is made depended on varying characteristics. Mechanism for building individual trajectory and forming individual competence is provided to make the intellectual content search.

Integrating fMRI with psychophysiological measurements in the study of decision-making

OpenAIRE

Wong, Savio W.H.; Xue, Gui; Bechara, Antoine

2011-01-01

Neuroimaging techniques have recently been used to examine the neural mechanism of decision-making. Nevertheless, most of the neuroimaging studies overlook the importance of emotion and autonomic response in modulating the process of decision-making. In this paper, we discussed how to integrating fMRI with psychophysiological measurements in studying decision-making. We suggested that psychophysiological data would complement with fMRI findings in providing a more comprehensive understanding ...

Integrated Medical Model Overview

Science.gov (United States)

Myers, J.; Boley, L.; Foy, M.; Goodenow, D.; Griffin, D.; Keenan, A.; Kerstman, E.; Melton, S.; McGuire, K.; Saile, L.;

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...

An integrated multi attribute decision model for energy efficiency processes in petrochemical industry applying fuzzy set theory

International Nuclear Information System (INIS)

Taylan, Osman; Kaya, Durmus; Demirbas, Ayhan

2016-01-01

Graphical abstract: Evaluation of compressors by comparing the different cost parameters. - Highlights: • Fuzzy sets and systems are used for decision making in MCDM problems. • An integrated Fuzzy AHP and fuzzy TOPSIS approaches are employed for compressor selection. • Compressor selection is a highly complex and non-linear process. • This approach increases the efficiency, reliability of alternative scenarios, and reduces the pay-back period. - Abstract: Energy efficient technologies offered by the market increases productivity. However, decision making for these technologies is usually obstructed in the firms and comes up with organizational barriers. Compressor selection in petrochemical industry requires assessment of several criteria such as ‘reliability, energy consumption, initial investment, capacity, pressure, and maintenance cost.’ Therefore, air compressor selection is a multi-attribute decision making (MADM) problem. The aim of this study is to select the most eligible compressor(s) so as to avoid the high energy consumption due to the capacity and maintenance costs. It is also aimed to avoid failures due to the reliability problems and high pressure. MADM usually takes place in a vague and imprecise environment. Soft computing techniques such as fuzzy sets and system can be used for decision making where vague and imprecise knowledge is available. In this study, an integrated fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) methodologies are employed for the compressor selection. Fuzzy AHP was used to determine the weights of criteria and fuzzy TOPSIS was employed to order the scenarios according to their superiority. The total effect of all criteria was determined for all alternative scenarios to make an optimal decision. Moreover, the types of compressor, carbon emission, waste heat recovery and their capacities were analyzed and compared by statistical

Decision Support for Flood Event Prediction and Monitoring

DEFF Research Database (Denmark)

Mioc, Darka; Anton, François; Liang, Gengsheng

2007-01-01

In this paper the development of Web GIS based decision support system for flood events is presented. To improve flood prediction we developed the decision support system for flood prediction and monitoring that integrates hydrological modelling and CARIS GIS. We present the methodology for data...... integration, floodplain delineation, and online map interfaces. Our Web-based GIS model can dynamically display observed and predicted flood extents for decision makers and the general public. The users can access Web-based GIS that models current flood events and displays satellite imagery and digital...... elevation model integrated with flood plain area. The system can show how the flooding prediction based on the output from hydrological modeling for the next 48 hours along the lower Saint John River Valley....

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.

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.

Hierarchical Modelling of Flood Risk for Engineering Decision Analysis

DEFF Research Database (Denmark)

Custer, Rocco

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

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

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

Integrating climate change adaptation in energy planning and decision-making - Key challenges and opportunities

DEFF Research Database (Denmark)

Olhoff, Anne; Olsen, Karen Holm

2011-01-01

management framework is used as the basis for identifying key challenges and opportunities to enhance the integration of climate change adaptation in energy planning and decision-making. Given its importance for raising awareness and for stimulating action by planners and decision-makers, emphasis is placed......Energy systems are significantly vulnerable to current climate variability and extreme events. As climate change becomes more pronounced, the risks and vulnerabilities will be exacerbated. To date, energy sector adaptation issues have received very limited attention. In this paper, a climate risk...... barriers to integration of climate risks and adaptive responses in energy planning and decision making. Both detailed assessments of the costs and benefits of integrating adaptation measures and rougher ‘order of magnitude’ estimates would enhance awareness raising and momentum for action....

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.

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.

Integrated Decision Support for Global Environmental Change Adaptation

Science.gov (United States)

Kumar, S.; Cantrell, S.; Higgins, G. J.; Marshall, J.; VanWijngaarden, F.

2011-12-01

Environmental changes are happening now that has caused concern in many parts of the world; particularly vulnerable are the countries and communities with limited resources and with natural environments that are more susceptible to climate change impacts. Global leaders are concerned about the observed phenomena and events such as Amazon deforestation, shifting monsoon patterns affecting agriculture in the mountain slopes of Peru, floods in Pakistan, water shortages in Middle East, droughts impacting water supplies and wildlife migration in Africa, and sea level rise impacts on low lying coastal communities in Bangladesh. These environmental changes are likely to get exacerbated as the temperatures rise, the weather and climate patterns change, and sea level rise continues. Large populations and billions of dollars of infrastructure could be affected. At Northrop Grumman, we have developed an integrated decision support framework for providing necessary information to stakeholders and planners to adapt to the impacts of climate variability and change at the regional and local levels. This integrated approach takes into account assimilation and exploitation of large and disparate weather and climate data sets, regional downscaling (dynamic and statistical), uncertainty quantification and reduction, and a synthesis of scientific data with demographic and economic data to generate actionable information for the stakeholders and decision makers. Utilizing a flexible service oriented architecture and state-of-the-art visualization techniques, this information can be delivered via tailored GIS portals to meet diverse set of user needs and expectations. This integrated approach can be applied to regional and local risk assessments, predictions and decadal projections, and proactive adaptation planning for vulnerable communities. In this paper we will describe this comprehensive decision support approach with selected applications and case studies to illustrate how this

Testing multi-alternative decision models with non-stationary evidence.

Science.gov (United States)

Tsetsos, Konstantinos; Usher, Marius; McClelland, James L

2011-01-01

Recent research has investigated the process of integrating perceptual evidence toward a decision, converging on a number of sequential sampling choice models, such as variants of race and diffusion models and the non-linear leaky competing accumulator (LCA) model. Here we study extensions of these models to multi-alternative choice, considering how well they can account for data from a psychophysical experiment in which the evidence supporting each of the alternatives changes dynamically during the trial, in a way that creates temporal correlations. We find that participants exhibit a tendency to choose an alternative whose evidence profile is temporally anti-correlated with (or dissimilar from) that of other alternatives. This advantage of the anti-correlated alternative is well accounted for in the LCA, and provides constraints that challenge several other models of multi-alternative choice.

A model of real estate and psychological factors in decision-making to buy real estate

Directory of Open Access Journals (Sweden)

Bojan Grum

2015-06-01

Full Text Available This article explores the psychological characteristics of potential real estate buyers connected with their decision to buy. Through a review of research, it reveals that most studies of psychological factors in the decision to buy real estate have a partial and dispersed orientation, and examine individual factors independently. It appears that the research area is lacking clearly defined models of psychological factors in the decision to buy real estate that would integrally and relationally explain the role of psychological characteristics of real estate buyers and their expectations in relation to a decision to buy. The article identifies two sets of psychological factors, motivational and emotional, determines their interaction with potential buyers’ expectations when deciding to purchase real estate and offers starting points for forming a model.

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.

Integrative structure modeling with the Integrative Modeling Platform.

Science.gov (United States)

Webb, Benjamin; Viswanath, Shruthi; Bonomi, Massimiliano; Pellarin, Riccardo; Greenberg, Charles H; Saltzberg, Daniel; Sali, Andrej

2018-01-01

Building models of a biological system that are consistent with the myriad data available is one of the key challenges in biology. Modeling the structure and dynamics of macromolecular assemblies, for example, can give insights into how biological systems work, evolved, might be controlled, and even designed. Integrative structure modeling casts the building of structural models as a computational optimization problem, for which information about the assembly is encoded into a scoring function that evaluates candidate models. Here, we describe our open source software suite for integrative structure modeling, Integrative Modeling Platform (https://integrativemodeling.org), and demonstrate its use. © 2017 The Protein Society.

Accounting for methodological, structural, and parameter uncertainty in decision-analytic models: a practical guide.

Science.gov (United States)

Bilcke, Joke; Beutels, Philippe; Brisson, Marc; Jit, Mark

2011-01-01

Accounting for uncertainty is now a standard part of decision-analytic modeling and is recommended by many health technology agencies and published guidelines. However, the scope of such analyses is often limited, even though techniques have been developed for presenting the effects of methodological, structural, and parameter uncertainty on model results. To help bring these techniques into mainstream use, the authors present a step-by-step guide that offers an integrated approach to account for different kinds of uncertainty in the same model, along with a checklist for assessing the way in which uncertainty has been incorporated. The guide also addresses special situations such as when a source of uncertainty is difficult to parameterize, resources are limited for an ideal exploration of uncertainty, or evidence to inform the model is not available or not reliable. for identifying the sources of uncertainty that influence results most are also described. Besides guiding analysts, the guide and checklist may be useful to decision makers who need to assess how well uncertainty has been accounted for in a decision-analytic model before using the results to make a decision.

Cost-Based Vertical Handover Decision Algorithm for WWAN/WLAN Integrated Networks

Directory of Open Access Journals (Sweden)

Kim LaeYoung

2009-01-01

Full Text Available Abstract Next generation wireless communications are expected to rely on integrated networks consisting of multiple wireless technologies. Heterogeneous networks based on Wireless Local Area Networks (WLANs and Wireless Wide Area Networks (WWANs can combine their respective advantages on coverage and data rates, offering a high Quality of Service (QoS to mobile users. In such environment, multi-interface terminals should seamlessly switch from one network to another in order to obtain improved performance or at least to maintain a continuous wireless connection. Therefore, network selection algorithm is important in providing better performance to the multi-interface terminals in the integrated networks. In this paper, we propose a cost-based vertical handover decision algorithm that triggers the Vertical Handover (VHO based on a cost function for WWAN/WLAN integrated networks. For the cost function, we focus on developing an analytical model of the expected cost of WLAN for the mobile users that enter the double-coverage area while having a connection in the WWAN. Our simulation results show that the proposed scheme achieves better performance in terms of power consumption and throughput than typical approach where WLANs are always preferred whenever the WLAN access is available.

A fuzzy multi-criteria decision-making model for CCHP systems driven by different energy sources

International Nuclear Information System (INIS)

Jing Youyin; Bai He; Wang Jiangjiang

2012-01-01

Because of its energy-saving and pollutant emission reduction potentials, combined cooling, heating and power (CCHP) system has been widely used in different kinds of buildings to solve building-related energetic problems and environmental issues. As various kinds of clean energy and renewable energy have been focused and applied to CCHP systems, it is urgent to find a practical decision making methodology for CCHP systems driven by different energy sources. In this paper, an evaluation model which integrates fuzzy theory with multi-criteria decision making process is proposed to assess the comprehensive benefits of CCHP systems from technology, economic, society and environment criterions. Grey relation analysis and combination weighting method are also employed to compare the integrated performances of CCHP systems driven by natural gas, fuel cell, biomass energy and combined gas-steam cycle respectively with a separation production system. Finally, a baseline residential building in Beijing, China is selected as a case to obtain the optimal CCHP system alternative. The results indicate that gas–steam combined cycle CCHP system is the optimum scheme among the five options. - Graphical abstract: A fuzzy multi-criteria decision-making model combined with combination weighting method and grey system theory is presented in this paper, which can be used to evaluate CCHP systems driven by different energy sources from technology, economic, environment and society criteria. Highlights: ► The integrated benefits of CCHP systems driven by different energy sources are evaluated. ► A fuzzy multi-criteria model combined with combination weighting method is proposed. ► Environment evaluation criteria play an important role in the decision-making process. ► CCHP system driven by gas–steam combined cycle is the optimal alternative.

Large-scale hydrological modelling and decision-making for sustainable water and land management along the Tarim River

OpenAIRE

Yu, Yang

2017-01-01

The debate over the effectiveness of Integrated Water Resources Management (IWRM) in practice has lasted for years. As the complexity and scope of IWRM increases in practice, it is difficult for hydrological models to directly simulate the interactions among water, ecosystem and humans. This study presents the large-scale hydrological modeling (MIKE HYDRO) approach and a Decision Support System (DSS) for decision-making with stakeholders on the sustainable water and land management along the ...

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.

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...

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

Integrating Dynamic Pricing and Replenishment Decisions Under Supply Capacity Uncertainty

OpenAIRE

Qi Feng

2010-01-01

This paper examines an integrated decision-making process regarding pricing for uncertain demand and sourcing from uncertain supply, which are often studied separately in the literature. Our analysis of the integrated system suggests that the base stock list price policy fails to achieve optimality even under deterministic demand. Instead, the optimal policy is characterized by two critical values: a reorder point and a target safety stock. Under this policy, a positive order is issued if and...

What is on your mind? Using the perceptual cycle model and critical decision method to understand the decision-making process in the cockpit.

Science.gov (United States)

Plant, Katherine L; Stanton, Neville A

2013-01-01

Aeronautical decision-making is complex as there is not always a clear coupling between the decision made and decision outcome. As such, there is a call for process-orientated decision research in order to understand why a decision made sense at the time it was made. Schema theory explains how we interact with the world using stored mental representations and forms an integral part of the perceptual cycle model (PCM); proposed here as a way to understand the decision-making process. This paper qualitatively analyses data from the critical decision method (CDM) based on the principles of the PCM. It is demonstrated that the approach can be used to understand a decision-making process and highlights how influential schemata can be at informing decision-making. The reliability of this approach is established, the general applicability is discussed and directions for future work are considered. This paper introduces the PCM, and the associated schema theory, as a framework to structure and explain data collected from the CDM. The reliability of both the method and coding scheme is addressed.

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.

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

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

Safety Lead Optimization and Candidate Identification: Integrating New Technologies into Decision-Making.

Science.gov (United States)

Dambach, Donna M; Misner, Dinah; Brock, Mathew; Fullerton, Aaron; Proctor, William; Maher, Jonathan; Lee, Dong; Ford, Kevin; Diaz, Dolores

2016-04-18

Discovery toxicology focuses on the identification of the most promising drug candidates through the development and implementation of lead optimization strategies and hypothesis-driven investigation of issues that enable rational and informed decision-making. The major goals are to [a] identify and progress the drug candidate with the best overall drug safety profile for a therapeutic area, [b] remove the most toxic drugs from the portfolio prior to entry into humans to reduce clinical attrition due to toxicity, and [c] establish a well-characterized hazard and translational risk profile to enable clinical trial designs. This is accomplished through a framework that balances the multiple considerations to identify a drug candidate with the overall best drug characteristics and provides a cogent understanding of mechanisms of toxicity. The framework components include establishing a target candidate profile for each program that defines the qualities of a successful candidate based on the intended therapeutic area, including the risk tolerance for liabilities; evaluating potential liabilities that may result from engaging the therapeutic target (pharmacology-mediated or on-target) and that are chemical structure-mediated (off-target); and characterizing identified liabilities. Lead optimization and investigation relies upon the integrated use of a variety of technologies and models (in silico, in vitro, and in vivo) that have achieved a sufficient level of qualification or validation to provide confidence in their use. We describe the strategic applications of various nonclinical models (established and new) for a holistic and integrated risk assessment that is used for rational decision-making. While this review focuses on strategies for small molecules, the overall concepts, approaches, and technologies are generally applicable to biotherapeutics.

Automating an integrated spatial data-mining model for landfill site selection

Science.gov (United States)

Abujayyab, Sohaib K. M.; Ahamad, Mohd Sanusi S.; Yahya, Ahmad Shukri; Ahmad, Siti Zubaidah; Aziz, Hamidi Abdul

2017-10-01

An integrated programming environment represents a robust approach to building a valid model for landfill site selection. One of the main challenges in the integrated model is the complicated processing and modelling due to the programming stages and several limitations. An automation process helps avoid the limitations and improve the interoperability between integrated programming environments. This work targets the automation of a spatial data-mining model for landfill site selection by integrating between spatial programming environment (Python-ArcGIS) and non-spatial environment (MATLAB). The model was constructed using neural networks and is divided into nine stages distributed between Matlab and Python-ArcGIS. A case study was taken from the north part of Peninsular Malaysia. 22 criteria were selected to utilise as input data and to build the training and testing datasets. The outcomes show a high-performance accuracy percentage of 98.2% in the testing dataset using 10-fold cross validation. The automated spatial data mining model provides a solid platform for decision makers to performing landfill site selection and planning operations on a regional scale.

Developing an Integrated Model Framework for the Assessment of Sustainable Agricultural Residue Removal Limits for Bioenergy Systems

Energy Technology Data Exchange (ETDEWEB)

David Muth, Jr.; Jared Abodeely; Richard Nelson; Douglas McCorkle; Joshua Koch; Kenneth Bryden

2011-08-01

Agricultural residues have significant potential as a feedstock for bioenergy production, but removing these residues can have negative impacts on soil health. Models and datasets that can support decisions about sustainable agricultural residue removal are available; however, no tools currently exist capable of simultaneously addressing all environmental factors that can limit availability of residue. The VE-Suite model integration framework has been used to couple a set of environmental process models to support agricultural residue removal decisions. The RUSLE2, WEPS, and Soil Conditioning Index models have been integrated. A disparate set of databases providing the soils, climate, and management practice data required to run these models have also been integrated. The integrated system has been demonstrated for two example cases. First, an assessment using high spatial fidelity crop yield data has been run for a single farm. This analysis shows the significant variance in sustainably accessible residue across a single farm and crop year. A second example is an aggregate assessment of agricultural residues available in the state of Iowa. This implementation of the integrated systems model demonstrates the capability to run a vast range of scenarios required to represent a large geographic region.

Towards Integrated Health Technology Assessment for Improving Decision Making in Selected Countries.

Science.gov (United States)

Oortwijn, Wija; Determann, Domino; Schiffers, Krijn; Tan, Siok Swan; van der Tuin, Jeroen

2017-09-01

To assess the level of comprehensiveness of health technology assessment (HTA) practices around the globe and to formulate recommendations for enhancing legitimacy and fairness of related decision-making processes. To identify best practices, we developed an evaluation framework consisting of 13 criteria on the basis of the INTEGRATE-HTA model (integrative perspective on assessing health technologies) and the Accountability for Reasonableness framework (deliberative appraisal process). We examined different HTA systems in middle-income countries (Argentina, Brazil, and Thailand) and high-income countries (Australia, Canada, England, France, Germany, Scotland, and South Korea). For this purpose, desk research and structured interviews with relevant key stakeholders (N = 32) in the selected countries were conducted. HTA systems in Canada, England, and Scotland appear relatively well aligned with our framework, followed by Australia, Germany, and France. Argentina and South Korea are at an early stage, whereas Brazil and Thailand are at an intermediate level. Both desk research and interviews revealed that scoping is often not part of the HTA process. In contrast, providing evidence reports for assessment is well established. Indirect and unintended outcomes are increasingly considered, but there is room for improvement. Monitoring and evaluation of the HTA process is not well established across countries. Finally, adopting transparent and robust processes, including stakeholder consultation, takes time. This study presents a framework for assessing the level of comprehensiveness of the HTA process in a country. On the basis of applying the framework, we formulate recommendations on how the HTA community can move toward a more integrated decision-making process using HTA. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Minimizing Project Cost by Integrating Subcontractor Selection Decisions with Scheduling

Science.gov (United States)

Biruk, Sławomir; Jaśkowski, Piotr; Czarnigowska, Agata

2017-10-01

Subcontracting has been a worldwide practice in the construction industry. It enables the construction enterprises to focus on their core competences and, at the same time, it makes complex project possible to be delivered. Since general contractors bear full responsibility for the works carried out by their subcontractors, it is their task and their risk to select a right subcontractor for a particular work. Although subcontractor management has been admitted to significantly affect the construction project’s performance, current practices and past research deal with subcontractor management and scheduling separately. The proposed model aims to support subcontracting decisions by integrating subcontractor selection with scheduling to enable the general contractor to select the optimal combination of subcontractors and own crews for all work packages of the project. The model allows for the interactions between the subcontractors and their impacts on the overall project performance in terms of cost and, indirectly, time and quality. The model is intended to be used at the general contractor’s bid preparation stage. The authors claim that the subcontracting decisions should be taken in a two-stage process. The first stage is a prequalification - provision of a short list of capable and reliable subcontractors; this stage is not the focus of the paper. The resulting pool of available resources is divided into two subsets: subcontractors, and general contractor’s in-house crews. Once it has been defined, the next stage is to assign them to the work packages that, bound by fixed precedence constraints, form the project’s network diagram. Each package is possible to be delivered by the general contractor’s crew or some of the potential subcontractors, at a specific time and cost. Particular crews and subcontractors can be contracted more than one package, but not at the same time. Other constraints include the predefined project completion date (the project is

Multiscale Modelling and Analysis of Collective Decision Making in Swarm Robotics

Science.gov (United States)

Vigelius, Matthias; Meyer, Bernd; Pascoe, Geoffrey

2014-01-01

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

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

Science.gov (United States)

Vigelius, Matthias; Meyer, Bernd; Pascoe, Geoffrey

2014-01-01

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

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.

The Moderating Effects of Decision-making Preference on M&A Integration Speed and Performance

DEFF Research Database (Denmark)

Uzelac, Boris; Bauer, Florian; Matzler, Kurt

2016-01-01

This paper illustrates the effects of post-merger integration speed on M&A performance and the moderating role of decision-making preferences. For a better understanding of the effects of integration speed, we separate the role of human and task integration speed. The results, obtained from...

A modeling framework for optimal long-term care insurance purchase decisions in retirement planning.

Science.gov (United States)

Gupta, Aparna; Li, Lepeng

2004-05-01

The level of need and costs of obtaining long-term care (LTC) during retired life require that planning for it is an integral part of retirement planning. In this paper, we divide retirement planning into two phases, pre-retirement and post-retirement. On the basis of four interrelated models for health evolution, wealth evolution, LTC insurance premium and coverage, and LTC cost structure, a framework for optimal LTC insurance purchase decisions in the pre-retirement phase is developed. Optimal decisions are obtained by developing a trade-off between post-retirement LTC costs and LTC insurance premiums and coverage. Two-way branching models are used to model stochastic health events and asset returns. The resulting optimization problem is formulated as a dynamic programming problem. We compare the optimal decision under two insurance purchase scenarios: one assumes that insurance is purchased for good and other assumes it may be purchased, relinquished and re-purchased. Sensitivity analysis is performed for the retirement age.

Integrating ecosystem-service tradeoffs into land-use decisions

OpenAIRE

Goldstein, Joshua H.; Caldarone, Giorgio; Duarte, Thomas Kaeo; Ennaanay, Driss; Hannahs, Neil; Mendoza, Guillermo; Polasky, Stephen; Wolny, Stacie; Daily, Gretchen C.

2012-01-01

Recent high-profile efforts have called for integrating ecosystem-service values into important societal decisions, but there are few demonstrations of this approach in practice. We quantified ecosystem-service values to help the largest private landowner in Hawaii, Kamehameha Schools, design a land-use development plan that balances multiple private and public values on its North Shore land holdings (Island of O’ahu) of ∼10,600 ha. We used the InVEST software tool to evaluate the environment...

Integrated Modelling in CRUCIAL Science Education

Science.gov (United States)

Mahura, Alexander; Nuterman, Roman; Mukhamedzhanova, Elena; Nerobelov, Georgiy; Sedeeva, Margarita; Suhodskiy, Alexander; Mostamandy, Suleiman; Smyshlyaev, Sergey

2017-04-01

The NordForsk CRUCIAL project (2016-2017) "Critical steps in understanding land surface - atmosphere interactions: from improved knowledge to socioeconomic solutions" as a part of the Pan-Eurasian EXperiment (PEEX; https://www.atm.helsinki.fi/peex) programme activities, is looking for a deeper collaboration between Nordic-Russian science communities. In particular, following collaboration between Danish and Russian partners, several topics were selected for joint research and are focused on evaluation of: (1) urbanization processes impact on changes in urban weather and climate on urban-subregional-regional scales and at contribution to assessment studies for population and environment; (2) effects of various feedback mechanisms on aerosol and cloud formation and radiative forcing on urban-regional scales for better predicting extreme weather events and at contribution to early warning systems, (3) environmental contamination from continues emissions and industrial accidents for better assessment and decision making for sustainable social and economic development, and (4) climatology of atmospheric boundary layer in northern latitudes to improve understanding of processes, revising parameterizations, and better weather forecasting. These research topics are realized employing the online integrated Enviro-HIRLAM (Environment - High Resolution Limited Area Model) model within students' research projects: (1) "Online integrated high-resolution modelling of Saint-Petersburg metropolitan area influence on weather and air pollution forecasting"; (2) "Modeling of aerosol impact on regional-urban scales: case study of Saint-Petersburg metropolitan area"; (3) "Regional modeling and GIS evaluation of environmental pollution from Kola Peninsula sources"; and (4) "Climatology of the High-Latitude Planetary Boundary Layer". The students' projects achieved results and planned young scientists research training on online integrated modelling (Jun 2017) will be presented and

[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.

Towards representing human behavior and decision making in Earth system models - an overview of techniques and approaches

Science.gov (United States)

Müller-Hansen, Finn; Schlüter, Maja; Mäs, Michael; Donges, Jonathan F.; Kolb, Jakob J.; Thonicke, Kirsten; Heitzig, Jobst

2017-11-01

Today, humans have a critical impact on the Earth system and vice versa, which can generate complex feedback processes between social and ecological dynamics. Integrating human behavior into formal Earth system models (ESMs), however, requires crucial modeling assumptions about actors and their goals, behavioral options, and decision rules, as well as modeling decisions regarding human social interactions and the aggregation of individuals' behavior. Here, we review existing modeling approaches and techniques from various disciplines and schools of thought dealing with human behavior at different levels of decision making. We demonstrate modelers' often vast degrees of freedom but also seek to make modelers aware of the often crucial consequences of seemingly innocent modeling assumptions. After discussing which socioeconomic units are potentially important for ESMs, we compare models of individual decision making that correspond to alternative behavioral theories and that make diverse modeling assumptions about individuals' preferences, beliefs, decision rules, and foresight. We review approaches to model social interaction, covering game theoretic frameworks, models of social influence, and network models. Finally, we discuss approaches to studying how the behavior of individuals, groups, and organizations can aggregate to complex collective phenomena, discussing agent-based, statistical, and representative-agent modeling and economic macro-dynamics. We illustrate the main ingredients of modeling techniques with examples from land-use dynamics as one of the main drivers of environmental change bridging local to global scales.

Expert intuitions: how to model the decision strategies of airport customs officers?

Science.gov (United States)

Pachur, Thorsten; Marinello, Gianmarco

2013-09-01

How does expertise impact the selection of decision strategies? We asked airport customs officers and a novice control group to decide which passengers (described on several cue dimensions) they would submit to a search. Additionally, participants estimated the validities of the different cues. Then we modeled the decisions using compensatory strategies, which integrate many cues, and a noncompensatory heuristic, which relies on one-reason decision making. The majority of the customs officers were best described by the noncompensatory heuristic, whereas the majority of the novices were best described by a compensatory strategy. We also found that the experts' subjective cue validity estimates showed a higher dispersion across the cues and that differences in cue dispersion partially mediated differences in strategy use between experts and novices. Our results suggest that experts often rely on one-reason decision making and that expert-novice differences in strategy selection may reflect a response to the internal representation of the environment. Copyright © 2013 Elsevier B.V. All rights reserved.

Development of a fuzzy optimization model, supporting global warming decision-making

International Nuclear Information System (INIS)

Leimbach, M.

1996-01-01

An increasing number of models have been developed to support global warming response policies. The model constructors are facing a lot of uncertainties which limit the evidence of these models. The support of climate policy decision-making is only possible in a semi-quantitative way, as presented by a Fuzzy model. The model design is based on an optimization approach, integrated in a bounded risk decision-making framework. Given some regional emission-related and impact-related restrictions, optimal emission paths can be calculated. The focus is not only on carbon dioxide but on other greenhouse gases too. In the paper, the components of the model will be described. Cost coefficients, emission boundaries and impact boundaries are represented as Fuzzy parameters. The Fuzzy model will be transformed into a computational one by using an approach of Rommelfanger. In the second part, some problems of applying the model to computations will be discussed. This includes discussions on the data situation and the presentation, as well as interpretation of results of sensitivity analyses. The advantage of the Fuzzy approach is that the requirements regarding data precision are not so strong. Hence, the effort for data acquisition can be reduced and computations can be started earlier. 9 figs., 3 tabs., 17 refs., 1 appendix

Effective use of integrated hydrological models in basin-scale water resources management: surrogate modeling approaches

Science.gov (United States)

Zheng, Y.; Wu, B.; Wu, X.

2015-12-01

Integrated hydrological models (IHMs) consider surface water and subsurface water as a unified system, and have been widely adopted in basin-scale water resources studies. However, due to IHMs' mathematical complexity and high computational cost, it is difficult to implement them in an iterative model evaluation process (e.g., Monte Carlo Simulation, simulation-optimization analysis, etc.), which diminishes their applicability for supporting decision-making in real-world situations. Our studies investigated how to effectively use complex IHMs to address real-world water issues via surrogate modeling. Three surrogate modeling approaches were considered, including 1) DYCORS (DYnamic COordinate search using Response Surface models), a well-established response surface-based optimization algorithm; 2) SOIM (Surrogate-based Optimization for Integrated surface water-groundwater Modeling), a response surface-based optimization algorithm that we developed specifically for IHMs; and 3) Probabilistic Collocation Method (PCM), a stochastic response surface approach. Our investigation was based on a modeling case study in the Heihe River Basin (HRB), China's second largest endorheic river basin. The GSFLOW (Coupled Ground-Water and Surface-Water Flow Model) model was employed. Two decision problems were discussed. One is to optimize, both in time and in space, the conjunctive use of surface water and groundwater for agricultural irrigation in the middle HRB region; and the other is to cost-effectively collect hydrological data based on a data-worth evaluation. Overall, our study results highlight the value of incorporating an IHM in making decisions of water resources management and hydrological data collection. An IHM like GSFLOW can provide great flexibility to formulating proper objective functions and constraints for various optimization problems. On the other hand, it has been demonstrated that surrogate modeling approaches can pave the path for such incorporation in real

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.

FEMA's Earthquake Incident Journal: A Web-Based Data Integration and Decision Support Tool for Emergency Management

Science.gov (United States)

Jones, M.; Pitts, R.

2017-12-01

For emergency managers, government officials, and others who must respond to rapidly changing natural disasters, timely access to detailed information related to affected terrain, population and infrastructure is critical for planning, response and recovery operations. Accessing, analyzing and disseminating such disparate information in near real-time are critical decision support components. However, finding a way to handle a variety of informative yet complex datasets poses a challenge when preparing for and responding to disasters. Here, we discuss the implementation of a web-based data integration and decision support tool for earthquakes developed by the Federal Emergency Management Agency (FEMA) as a solution to some of these challenges. While earthquakes are among the most well- monitored and measured of natural hazards, the spatially broad impacts of shaking, ground deformation, landslides, liquefaction, and even tsunamis, are extremely difficult to quantify without accelerated access to data, modeling, and analytics. This web-based application, deemed the "Earthquake Incident Journal", provides real-time access to authoritative and event-specific data from external (e.g. US Geological Survey, NASA, state and local governments, etc.) and internal (FEMA) data sources. The journal includes a GIS-based model for exposure analytics, allowing FEMA to assess the severity of an event, estimate impacts to structures and population in near real-time, and then apply planning factors to exposure estimates to answer questions such as: What geographic areas are impacted? Will federal support be needed? What resources are needed to support survivors? And which infrastructure elements or essential facilities are threatened? This presentation reviews the development of the Earthquake Incident Journal, detailing the data integration solutions, the methodology behind the GIS-based automated exposure model, and the planning factors as well as other analytical advances that

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

Integrating geophysics and hydrology for reducing the uncertainty of groundwater model predictions and improved prediction performance

DEFF Research Database (Denmark)

Christensen, Nikolaj Kruse; Christensen, Steen; Ferre, Ty

the integration of geophysical data in the construction of a groundwater model increases the prediction performance. We suggest that modelers should perform a hydrogeophysical “test-bench” analysis of the likely value of geophysics data for improving groundwater model prediction performance before actually...... and the resulting predictions can be compared with predictions from the ‘true’ model. By performing this analysis we expect to give the modeler insight into how the uncertainty of model-based prediction can be reduced.......A major purpose of groundwater modeling is to help decision-makers in efforts to manage the natural environment. Increasingly, it is recognized that both the predictions of interest and their associated uncertainties should be quantified to support robust decision making. In particular, decision...

Comparing multi-criteria decision analysis and integrated assessment to support long-term water supply planning.

Directory of Open Access Journals (Sweden)

Lisa Scholten

Full Text Available We compare the use of multi-criteria decision analysis (MCDA-or more precisely, models used in multi-attribute value theory (MAVT-to integrated assessment (IA models for supporting long-term water supply planning in a small town case study in Switzerland. They are used to evaluate thirteen system scale water supply alternatives in four future scenarios regarding forty-four objectives, covering technical, social, environmental, and economic aspects. The alternatives encompass both conventional and unconventional solutions and differ regarding technical, spatial and organizational characteristics. This paper focuses on the impact assessment and final evaluation step of the structured MCDA decision support process. We analyze the performance of the alternatives for ten stakeholders. We demonstrate the implications of model assumptions by comparing two IA and three MAVT evaluation model layouts of different complexity. For this comparison, we focus on the validity (ranking stability, desirability (value, and distinguishability (value range of the alternatives given the five model layouts. These layouts exclude or include stakeholder preferences and uncertainties. Even though all five led us to identify the same best alternatives, they did not produce identical rankings. We found that the MAVT-type models provide higher distinguishability and a more robust basis for discussion than the IA-type models. The needed complexity of the model, however, should be determined based on the intended use of the model within the decision support process. The best-performing alternatives had consistently strong performance for all stakeholders and future scenarios, whereas the current water supply system was outperformed in all evaluation layouts. The best-performing alternatives comprise proactive pipe rehabilitation, adapted firefighting provisions, and decentralized water storage and/or treatment. We present recommendations for possible ways of improving water

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.

An integrated multi-criteria decision-making methodology for conveyor system selection

Directory of Open Access Journals (Sweden)

Pairat Jiamruangjarus

2016-12-01

Full Text Available Material handling equipment (MHE is important for every industry because it has an effect on the productivity of manufacturing. Conveyor systems are presently one popular type of MHE. This paper presents an integration of the analytic network process (ANP with the benefits, opportunities, costs and risk (BOCR model in order to select the best conveyor system. The proposed model established a network with four merits, six strategies criteria, and twenty six sub-criteria with four alternatives (present, roller conveyor, chain conveyor, and monorail. The ANP is to determine the relative weights of an evaluative criteria and decision alternatives. Therefore, the final ranking of the alternatives are calculated by synthesizing the score of each alternative under BOCR. The results showed that the best alternative under all five methods is the chain conveyor. These research results can be easily applied, adapted and used to improve performance of selecting the conveyer system in small and medium enterprises through large industries.

Integrative evaluation for sustainable decisions of urban wastewater system management under uncertainty

Science.gov (United States)

Hadjimichael, A.; Corominas, L.; Comas, J.

2017-12-01

With sustainable development as their overarching goal, urban wastewater system (UWS) managers need to take into account multiple social, economic, technical and environmental facets related to their decisions. In this complex decision-making environment, uncertainty can be formidable. It is present both in the ways the system is interpreted stochastically, but also in its natural ever-shifting behavior. This inherent uncertainty suggests that wiser decisions would be made under an adaptive and iterative decision-making regime. No decision-support framework has been presented in the literature to effectively addresses all these needs. The objective of this work is to describe such a conceptual framework to evaluate and compare alternative solutions for various UWS challenges within an adaptive management structure. Socio-economic aspects such as externalities are taken into account, along with other traditional criteria as necessary. Robustness, reliability and resilience analyses test the performance of the system against present and future variability. A valuation uncertainty analysis incorporates uncertain valuation assumptions in the decision-making process. The framework is demonstrated with an application to a case study presenting a typical problem often faced by managers: poor river water quality, increasing population, and more stringent water quality legislation. The application of the framework made use of: i) a cost-benefit analysis including monetized environmental benefits and damages; ii) a robustness analysis of system performance against future conditions; iii) reliability and resilience analyses of the system given contextual variability; and iv) a valuation uncertainty analysis of model parameters. The results suggest that the installation of bigger volumes would give rise to increased benefits despite larger capital costs, as well as increased robustness and resilience. Population numbers appear to affect the estimated benefits most, followed by

An integrated decision support system for wastewater nutrient recovery and recycling to agriculture

Science.gov (United States)

Roy, E. D.; Bomeisl, L.; Cornbrooks, P.; Mo, W.

2017-12-01

Nutrient recovery and recycling has become a key research topic within the wastewater engineering and nutrient management communities. Several technologies now exist that can effectively capture nutrients from wastewater, and innovation in this area continues to be an important research pursuit. However, practical nutrient recycling solutions require more than capable nutrient capture technologies. We also need to understand the role that wastewater nutrient recovery and recycling can play within broader nutrient management schemes at the landscape level, including important interactions at the nexus of food, energy, and water. We are developing an integrated decision support system that combines wastewater treatment data, agricultural data, spatial nutrient balance modeling, life cycle assessment, stakeholder knowledge, and multi-criteria decision making. Our goals are to: (1) help guide design decisions related to the implementation of sustainable nutrient recovery technology, (2) support innovations in watershed nutrient management that operate at the interface of the built environment and agriculture, and (3) aid efforts to protect aquatic ecosystems while supporting human welfare in a circular nutrient economy. These goals will be realized partly through the assessment of plausible alternative scenarios for the future. In this presentation, we will describe the tool and focus on nutrient balance results for the New England region. These results illustrate that both centralized and decentralized wastewater nutrient recovery schemes have potential to transform nutrient flows in many New England watersheds, diverting wastewater N and P away from aquatic ecosystems and toward local or regional agricultural soils where they can offset a substantial percentage of imported fertilizer. We will also highlight feasibility criteria and next steps to integrate stakeholder knowledge, economics, and life cycle assessment into the tool.

Integrated modelling of crop production and nitrate leaching with the Daisy model.

Science.gov (United States)

Manevski, Kiril; Børgesen, Christen D; Li, Xiaoxin; Andersen, Mathias N; Abrahamsen, Per; Hu, Chunsheng; Hansen, Søren

2016-01-01

An integrated modelling strategy was designed and applied to the Soil-Vegetation-Atmosphere Transfer model Daisy for simulation of crop production and nitrate leaching under pedo-climatic and agronomic environment different than that of model original parameterisation. The points of significance and caution in the strategy are: •Model preparation should include field data in detail due to the high complexity of the soil and the crop processes simulated with process-based model, and should reflect the study objectives. Inclusion of interactions between parameters in a sensitivity analysis results in better account for impacts on outputs of measured variables.•Model evaluation on several independent data sets increases robustness, at least on coarser time scales such as month or year. It produces a valuable platform for adaptation of the model to new crops or for the improvement of the existing parameters set. On daily time scale, validation for highly dynamic variables such as soil water transport remains challenging. •Model application is demonstrated with relevance for scientists and regional managers. The integrated modelling strategy is applicable for other process-based models similar to Daisy. It is envisaged that the strategy establishes model capability as a useful research/decision-making, and it increases knowledge transferability, reproducibility and traceability.

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

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

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

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.

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.

LIANA Model Integration System - architecture, user interface design and application in MOIRA DSS

Directory of Open Access Journals (Sweden)

D. Hofman

2005-01-01

Full Text Available The LIANA Model Integration System is the shell application supporting model integration and user interface functionality required for the rapid construction and run-time support of the environmental decision support systems (EDSS. Internally it is constructed as the framework of C++ classes and functions covering most common tasks performed by the EDSS (such as managing of and alternative strategies, running of the chain of the models, supporting visualisation of the data with tables and graphs, keeping ranges and default values for input parameters etc.. EDSS is constructed by integration of LIANA system with the models or other applications such as GIS or MAA software. The basic requirements to the model or other application to be integrated is minimal - it should be a Windows or DOS .exe file and receive input and provide output as text files. For the user the EDSS is represented as the number of data sets describing scenario or giving results of evaluation of scenario via modelling. Internally data sets correspond to the I/O files of the models. During the integration the parameters included in each the data sets as well as specifications necessary to present the data set in GUI and export or import it to/from text file are provided with MIL_LIANA language. Visual C++ version of LIANA has been developed in the frame of MOIRA project and is used as the basis for the MOIRA Software Framework - the shell and user interface component of the MOIRA Decision Support System. At present, the usage of LIANA for the creation of a new EDSS requires changes to be made in its C++ code. The possibility to use LIANA for the new EDSS construction without extending the source code is achieved by substituting MIL_LIANA with the object-oriented LIANA language.

SimBasin: serious gaming for integrated decision-making in the Magdalena-Cauca basin

Science.gov (United States)

Craven, Joanne; Angarita, Hector; Corzo, Gerald

2016-04-01

The Magdalena-Cauca macrobasin covers 24% of the land area of Colombia, and provides more than half of the country's economic potential. The basin is also home a large proportion of Colombia's biodiversity. These conflicting demands have led to problems in the basin, including a dramatic fall in fish populations, additional flooding (such as the severe nationwide floods caused by the La Niña phenomenon in 2011), and habitat loss. It is generally believed that the solution to these conflicts is to manage the basin in a more integrated way, and bridge the gaps between decision-makers in different sectors and scientists. To this end, inter-ministerial agreements are being formulated and a decision support system is being developed by The Nature Conservancy Colombia. To engage stakeholders in this process SimBasin, a "serious game", has been developed. It is intended to act as a catalyst for bringing stakeholders together, an illustration of the uncertainties, relationships and feedbacks in the basin, and an accessible introduction to modelling and decision support for non-experts. During the game, groups of participants are led through a 30 year future development of the basin, during which they take decisions about the development of the basin and see the impacts on four different sectors: agriculture, hydropower, flood risk, and environment. These impacts are displayed through seven indicators, which players should try to maintain above critical thresholds. To communicate the effects of uncertainty and climate variability, players see the actual value of the indicator and also a band of possible values, so they can see if their decisions have actually reduced risk or if they just "got lucky". The game works as a layer on top of a WEAP water resources model of the basin, adapted from a basin-wide model already created, so the fictional game basin is conceptually similar to the Magdalena-Cauca basin. The game is freely available online, and new applications are being

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

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...

Risk-sensitivity in Bayesian sensorimotor integration.

Directory of Open Access Journals (Sweden)

Jordi Grau-Moya

Full Text Available Information processing in the nervous system during sensorimotor tasks with inherent uncertainty has been shown to be consistent with Bayesian integration. Bayes optimal decision-makers are, however, risk-neutral in the sense that they weigh all possibilities based on prior expectation and sensory evidence when they choose the action with highest expected value. In contrast, risk-sensitive decision-makers are sensitive to model uncertainty and bias their decision-making processes when they do inference over unobserved variables. In particular, they allow deviations from their probabilistic model in cases where this model makes imprecise predictions. Here we test for risk-sensitivity in a sensorimotor integration task where subjects exhibit Bayesian information integration when they infer the position of a target from noisy sensory feedback. When introducing a cost associated with subjects' response, we found that subjects exhibited a characteristic bias towards low cost responses when their uncertainty was high. This result is in accordance with risk-sensitive decision-making processes that allow for deviations from Bayes optimal decision-making in the face of uncertainty. Our results suggest that both Bayesian integration and risk-sensitivity are important factors to understand sensorimotor integration in a quantitative fashion.

A Four-Type Decision-Variable MINLP Model for a Supply Chain Network Design

Directory of Open Access Journals (Sweden)

M. M. Monteiro

2010-01-01

Full Text Available We propose a mixed integer nonlinear programming model for the design of a one-period planning horizon supply chain with integrated and flexible decisions on location of plants and of warehouses, on levels of production and of inventory, and on transportation models, considering stochastic demand and the ABC classification for finished goods, which is an NP-hard industrial engineering optimization problem. Furthermore, computational implementation of the proposed model is presented through the direct application of the outer approximation algorithm on some randomly generated supply chain data.

Inhibition of Pre-Supplementary Motor Area by Continuous Theta Burst Stimulation Leads to More Cautious Decision-making and More Efficient Sensory Evidence Integration.

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Tosun, Tuğçe; Berkay, Dilara; Sack, Alexander T; Çakmak, Yusuf Ö; Balcı, Fuat

2017-08-01

Decisions are made based on the integration of available evidence. The noise in evidence accumulation leads to a particular speed-accuracy tradeoff in decision-making, which can be modulated and optimized by adaptive decision threshold setting. Given the effect of pre-SMA activity on striatal excitability, we hypothesized that the inhibition of pre-SMA would lead to higher decision thresholds and an increased accuracy bias. We used offline continuous theta burst stimulation to assess the effect of transient inhibition of the right pre-SMA on the decision processes in a free-response two-alternative forced-choice task within the drift diffusion model framework. Participants became more cautious and set higher decision thresholds following right pre-SMA inhibition compared with inhibition of the control site (vertex). Increased decision thresholds were accompanied by an accuracy bias with no effects on post-error choice behavior. Participants also exhibited higher drift rates as a result of pre-SMA inhibition compared with the vertex inhibition. These results, in line with the striatal theory of speed-accuracy tradeoff, provide evidence for the functional role of pre-SMA activity in decision threshold modulation. Our results also suggest that pre-SMA might be a part of the brain network associated with the sensory evidence integration.

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 ...

Model integration and a theory of models

OpenAIRE

Dolk, Daniel R.; Kottemann, Jeffrey E.

1993-01-01

Model integration extends the scope of model management to include the dimension of manipulation as well. This invariably leads to comparisons with database theory. Model integration is viewed from four perspectives: Organizational, definitional, procedural, and implementational. Strategic modeling is discussed as the organizational motivation for model integration. Schema and process integration are examined as the logical and manipulation counterparts of model integr...

Towards Integrating the Principlist and Casuist Approaches to Ethical Decisions via Multi-Criterial Support

DEFF Research Database (Denmark)

Kaltoft, Mette Kjer; Nielsen, Jesper Bo; Salkeld, Glenn

2016-01-01

of each option, as a contribution to enhanced deliberation. As proof of concept and method an exemplar aid adds veracity and confidentiality to beneficence, non-maleficence, autonomy and justice, as the criteria, with case-based reasoning supplying the necessary inputs for the decision of whether a nurse......An interactive decision support tool based on Multi-Criteria Decision Analysis (MCDA) can help health professionals integrate the principlist (principle-based) and casuist (case-based) approaches to ethical decision making in both their training and practice. MCDA can incorporate generic ethical...

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

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)

The role of emotion in clinical decision making: an integrative literature review

OpenAIRE

Kozlowski, Desirée; Hutchinson, Marie; Hurley, John; Rowley, Joanne; Sutherland, Joanna

2017-01-01

Background Traditionally, clinical decision making has been perceived as a purely rational and cognitive process. Recently, a number of authors have linked emotional intelligence (EI) to clinical decision making (CDM) and calls have been made for an increased focus on EI skills for clinicians. The objective of this integrative literature review was to identify and synthesise the empirical evidence for a role of emotion in CDM. Methods A systematic search of the bibliographic databases PubMed,...

Improving wave forecasting by integrating ensemble modelling and machine learning

Science.gov (United States)

O'Donncha, F.; Zhang, Y.; James, S. C.

2017-12-01

Modern smart-grid networks use technologies to instantly relay information on supply and demand to support effective decision making. Integration of renewable-energy resources with these systems demands accurate forecasting of energy production (and demand) capacities. For wave-energy converters, this requires wave-condition forecasting to enable estimates of energy production. Current operational wave forecasting systems exhibit substantial errors with wave-height RMSEs of 40 to 60 cm being typical, which limits the reliability of energy-generation predictions thereby impeding integration with the distribution grid. In this study, we integrate physics-based models with statistical learning aggregation techniques that combine forecasts from multiple, independent models into a single "best-estimate" prediction of the true state. The Simulating Waves Nearshore physics-based model is used to compute wind- and currents-augmented waves in the Monterey Bay area. Ensembles are developed based on multiple simulations perturbing input data (wave characteristics supplied at the model boundaries and winds) to the model. A learning-aggregation technique uses past observations and past model forecasts to calculate a weight for each model. The aggregated forecasts are compared to observation data to quantify the performance of the model ensemble and aggregation techniques. The appropriately weighted ensemble model outperforms an individual ensemble member with regard to forecasting wave conditions.

Operator models for delivering municipal solid waste management services in developing countries: Part B: Decision support.

Science.gov (United States)

Soós, Reka; Whiteman, Andrew D; Wilson, David C; Briciu, Cosmin; Nürnberger, Sofia; Oelz, Barbara; Gunsilius, Ellen; Schwehn, Ekkehard

2017-08-01

This is the second of two papers reporting the results of a major study considering 'operator models' for municipal solid waste management (MSWM) in emerging and developing countries. Part A documents the evidence base, while Part B presents a four-step decision support system for selecting an appropriate operator model in a particular local situation. Step 1 focuses on understanding local problems and framework conditions; Step 2 on formulating and prioritising local objectives; and Step 3 on assessing capacities and conditions, and thus identifying strengths and weaknesses, which underpin selection of the operator model. Step 4A addresses three generic questions, including public versus private operation, inter-municipal co-operation and integration of services. For steps 1-4A, checklists have been developed as decision support tools. Step 4B helps choose locally appropriate models from an evidence-based set of 42 common operator models ( coms); decision support tools here are a detailed catalogue of the coms, setting out advantages and disadvantages of each, and a decision-making flowchart. The decision-making process is iterative, repeating steps 2-4 as required. The advantages of a more formal process include avoiding pre-selection of a particular com known to and favoured by one decision maker, and also its assistance in identifying the possible weaknesses and aspects to consider in the selection and design of operator models. To make the best of whichever operator models are selected, key issues which need to be addressed include the capacity of the public authority as 'client', management in general and financial management in particular.

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

Bridging the gap between evidence and policy for infectious diseases: How models can aid public health decision-making

Directory of Open Access Journals (Sweden)

Gwenan M. Knight

2016-01-01

Full Text Available The dominant approach to decision-making in public health policy for infectious diseases relies heavily on expert opinion, which often applies empirical evidence to policy questions in a manner that is neither systematic nor transparent. Although systematic reviews are frequently commissioned to inform specific components of policy (such as efficacy, the same process is rarely applied to the full decision-making process. Mathematical models provide a mechanism through which empirical evidence can be methodically and transparently integrated to address such questions. However, such models are often considered difficult to interpret. In addition, models provide estimates that need to be iteratively re-evaluated as new data or considerations arise. Using the case study of a novel diagnostic for tuberculosis, a framework for improved collaboration between public health decision-makers and mathematical modellers that could lead to more transparent and evidence-driven policy decisions for infectious diseases in the future is proposed. The framework proposes that policymakers should establish long-term collaborations with modellers to address key questions, and that modellers should strive to provide clear explanations of the uncertainty of model structure and outputs. Doing so will improve the applicability of models and clarify their limitations when used to inform real-world public health policy decisions.

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

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

A new parameterization for integrated population models to document amphibian reintroductions.

Science.gov (United States)

Duarte, Adam; Pearl, Christopher A; Adams, Michael J; Peterson, James T

2017-09-01

Managers are increasingly implementing reintroduction programs as part of a global effort to alleviate amphibian declines. Given uncertainty in factors affecting populations and a need to make recurring decisions to achieve objectives, adaptive management is a useful component of these efforts. A major impediment to the estimation of demographic rates often used to parameterize and refine decision-support models is that life-stage-specific monitoring data are frequently sparse for amphibians. We developed a new parameterization for integrated population models to match the ecology of amphibians and capitalize on relatively inexpensive monitoring data to document amphibian reintroductions. We evaluate the capability of this model by fitting it to Oregon spotted frog (Rana pretiosa) monitoring data collected from 2007 to 2014 following their reintroduction within the Klamath Basin, Oregon, USA. The number of egg masses encountered and the estimated adult and metamorph abundances generally increased following reintroduction. We found that survival probability from egg to metamorph ranged from 0.01 in 2008 to 0.09 in 2009 and was not related to minimum spring temperatures, metamorph survival probability ranged from 0.13 in 2010-2011 to 0.86 in 2012-2013 and was positively related to mean monthly temperatures (logit-scale slope = 2.37), adult survival probability was lower for founders (0.40) than individuals recruited after reintroduction (0.56), and the mean number of egg masses per adult female was 0.74. Our study is the first to test hypotheses concerning Oregon spotted frog egg-to-metamorph and metamorph-to-adult transition probabilities in the wild and document their response at multiple life stages following reintroduction. Furthermore, we provide an example to illustrate how the structure of our integrated population model serves as a useful foundation for amphibian decision-support models within adaptive management programs. The integration of multiple, but

Iterative integral parameter identification of a respiratory mechanics model.

Science.gov (United States)

Schranz, Christoph; Docherty, Paul D; Chiew, Yeong Shiong; Möller, Knut; Chase, J Geoffrey

2012-07-18

Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual's model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS) patients. The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.

System-level Modeling of Wireless Integrated Sensor Networks

DEFF Research Database (Denmark)

Virk, Kashif M.; Hansen, Knud; Madsen, Jan

2005-01-01

Wireless integrated sensor networks have emerged as a promising infrastructure for a new generation of monitoring and tracking applications. In order to efficiently utilize the extremely limited resources of wireless sensor nodes, accurate modeling of the key aspects of wireless sensor networks...... is necessary so that system-level design decisions can be made about the hardware and the software (applications and real-time operating system) architecture of sensor nodes. In this paper, we present a SystemC-based abstract modeling framework that enables system-level modeling of sensor network behavior...... by modeling the applications, real-time operating system, sensors, processor, and radio transceiver at the sensor node level and environmental phenomena, including radio signal propagation, at the sensor network level. We demonstrate the potential of our modeling framework by simulating and analyzing a small...

Mainstreaming Natural Capital into Decisions: Integrated Valuation of Ecosystem Services

Directory of Open Access Journals (Sweden)

Arnas Palaima

2013-08-01

Full Text Available The purpose of the article is to review current paradigms in ecosystem services valuation, existing gaps and current trends in addressing those gaps. Natural capital, often defined as the stock of natural ecosystems that yields a flow of valuable ecosystem goods or services into the future, is often undervalued or not valued at all by governments, business and society, which leads to environmental degradation and loss of biodiversity. One of the major reasons of such undervaluation is the lack of practical, realistic quantitative methods/models that would establish ecosystem services value and its change due to human development. A promising, recently developed ecosystem services modeling system is InVEST: “Integrated Valuation of Ecosystem Services and Trade-Offs.” InVEST is a set of Geographic Information Systems (GIS models that predict the provision and value of ecosystem services and habitat provision given land use/land cover maps and related biophysical, economic, and institutional data for the study region. InVEST, if further developed and applied in a systematic way, could facilitate mainstreaming the natural capital into decisions at all levels and provide a strong foundation for local natural resources managers to improve and optimize their environmental management strategies.

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.

An Integrative Process Approach on Judgment and Decision Making: The Impact of Arousal, Affect, Motivation, and Cognitive Ability

Science.gov (United States)

Roets, Arne; Van Hiel, Alain

2011-01-01

This article aims to integrate the findings from various research traditions on human judgment and decision making, focusing on four process variables: arousal, affect, motivation, and cognitive capacity/ability. We advocate a broad perspective referred to as the integrative process approach (IPA) of decision making, in which these process…

Use of a knowledge synthesis by decision makers and planners to facilitate system level integration in a large Canadian provincial health authority

Directory of Open Access Journals (Sweden)

Esther Suter

2011-03-01

Full Text Available Purpose: The study is an examination of how a knowledge synthesis, conducted to fill an information gap identified by decision makers and planners responsible for integrating health systems in a western Canadian health authority, is being used within that organisation. Methods: Purposive sampling and snowball technique were used to identify 13 participants who were interviewed about how they are using the knowledge synthesis for health services planning and decision-making. Results: The knowledge synthesis is used by those involved in the strategic direction of the provincial healthcare organisation and those tasked with the operationalization of integration at the provincial or local level. Both groups most frequently use the ten key principles for integration, followed by the sections on integration processes, strategies and models. The key principles facilitate discussion on priority areas to be considered and provide a reference point for a desired future state. Perceived information gaps relate to a lack of detail on "how to" strategies, tools and processes that would lead to successful integration. Discussion and conclusion: The current project demonstrates that decision makers and planners will effectively use a knowledge synthesis if it is timely, relevant and accessible. The information can be applied at strategic and operations levels. Attention needs to be paid to include more information on implementation strategies and processes. Including knowledge users in identifying research questions will increase information uptake.

Use of a knowledge synthesis by decision makers and planners to facilitate system level integration in a large Canadian provincial health authority

Directory of Open Access Journals (Sweden)

Esther Suter

2011-03-01

Full Text Available Purpose: The study is an examination of how a knowledge synthesis, conducted to fill an information gap identified by decision makers and planners responsible for integrating health systems in a western Canadian health authority, is being used within that organisation.Methods: Purposive sampling and snowball technique were used to identify 13 participants who were interviewed about how they are using the knowledge synthesis for health services planning and decision-making.Results: The knowledge synthesis is used by those involved in the strategic direction of the provincial healthcare organisation and those tasked with the operationalization of integration at the provincial or local level. Both groups most frequently use the ten key principles for integration, followed by the sections on integration processes, strategies and models. The key principles facilitate discussion on priority areas to be considered and provide a reference point for a desired future state. Perceived information gaps relate to a lack of detail on "how to" strategies, tools and processes that would lead to successful integration.Discussion and conclusion: The current project demonstrates that decision makers and planners will effectively use a knowledge synthesis if it is timely, relevant and accessible. The information can be applied at strategic and operations levels. Attention needs to be paid to include more information on implementation strategies and processes. Including knowledge users in identifying research questions will increase information uptake.

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...

Waste Management: An integrated modeling approach for analyzing change in NWC production processes

International Nuclear Information System (INIS)

Christensen, D.C.; Sohn, C.L.; Helm, T.M.; Farish, T.J.; Reid, R.A.

1991-01-01

A problem-driven, integrated modeling, decision-support framework has been conceptualized to aid a team of experts determine the set of evolving technologies that should receive additional developmental support. This conceptual framework utilizes a variety of decision aiding models including Flowsheeting, Analytical Hierarchy Process, Linear and Goal Programming, and Object-Oriented Discrete Event Simulation. A number of the technologies under consideration are strong candidates to overcome current plutonium processing problems so that effective technology will be available for implementation in Complex 21. Complex 21 is a participatory, inter-installation planning effort sponsored by US DOE to consolidate and revitalize the nuclear weapons complex facilities by the 21st century. A computer-based dynamic simulation model has been constructed that will allow testing of alternative combinations of developing technologies. The modeling of new configurations of technologies under a number of different operating conditions and material flow assumptions provides information needed for effective decision making for Complex 21. 4 figs

Integrated environmental modeling: a vision and roadmap for the future

Science.gov (United States)

Laniak, Gerard F.; Olchin, Gabriel; Goodall, Jonathan; Voinov, Alexey; Hill, Mary; Glynn, Pierre; Whelan, Gene; Geller, Gary; Quinn, Nigel; Blind, Michiel; Peckham, Scott; Reaney, Sim; Gaber, Noha; Kennedy, Philip R.; Hughes, Andrew

2013-01-01

Integrated environmental modeling (IEM) is inspired by modern environmental problems, decisions, and policies and enabled by transdisciplinary science and computer capabilities that allow the environment to be considered in a holistic way. The problems are characterized by the extent of the environmental system involved, dynamic and interdependent nature of stressors and their impacts, diversity of stakeholders, and integration of social, economic, and environmental considerations. IEM provides a science-based structure to develop and organize relevant knowledge and information and apply it to explain, explore, and predict the behavior of environmental systems in response to human and natural sources of stress. During the past several years a number of workshops were held that brought IEM practitioners together to share experiences and discuss future needs and directions. In this paper we organize and present the results of these discussions. IEM is presented as a landscape containing four interdependent elements: applications, science, technology, and community. The elements are described from the perspective of their role in the landscape, current practices, and challenges that must be addressed. Workshop participants envision a global scale IEM community that leverages modern technologies to streamline the movement of science-based knowledge from its sources in research, through its organization into databases and models, to its integration and application for problem solving purposes. Achieving this vision will require that the global community of IEM stakeholders transcend social, and organizational boundaries and pursue greater levels of collaboration. Among the highest priorities for community action are the development of standards for publishing IEM data and models in forms suitable for automated discovery, access, and integration; education of the next generation of environmental stakeholders, with a focus on transdisciplinary research, development, and

An integrated probabilistic risk analysis decision support methodology for systems with multiple state variables

International Nuclear Information System (INIS)

Sen, P.; Tan, John K.G.; Spencer, David

1999-01-01

Probabilistic risk analysis (PRA) methods have been proven to be valuable in risk and reliability analysis. However, a weak link seems to exist between methods for analysing risks and those for making rational decisions. The integrated decision support system (IDSS) methodology presented in this paper attempts to address this issue in a practical manner. In consists of three phases: a PRA phase, a risk sensitivity analysis (SA) phase and an optimisation phase, which are implemented through an integrated computer software system. In the risk analysis phase the problem is analysed by the Boolean representation method (BRM), a PRA method that can deal with systems with multiple state variables and feedback loops. In the second phase the results obtained from the BRM are utilised directly to perform importance and risk SA. In the third phase, the problem is formulated as a multiple objective decision making problem in the form of multiple objective reliability optimisation. An industrial example is included. The resultant solutions of a five objective reliability optimisation are presented, on the basis of which rational decision making can be explored

Advancing Integrated Systems Modelling Framework for Life Cycle Sustainability Assessment

Directory of Open Access Journals (Sweden)

Anthony Halog

2011-02-01

Full Text Available The need for integrated methodological framework for sustainability assessment has been widely discussed and is urgent due to increasingly complex environmental system problems. These problems have impacts on ecosystems and human well-being which represent a threat to economic performance of countries and corporations. Integrated assessment crosses issues; spans spatial and temporal scales; looks forward and backward; and incorporates multi-stakeholder inputs. This study aims to develop an integrated methodology by capitalizing the complementary strengths of different methods used by industrial ecologists and biophysical economists. The computational methodology proposed here is systems perspective, integrative, and holistic approach for sustainability assessment which attempts to link basic science and technology to policy formulation. The framework adopts life cycle thinking methods—LCA, LCC, and SLCA; stakeholders analysis supported by multi-criteria decision analysis (MCDA; and dynamic system modelling. Following Pareto principle, the critical sustainability criteria, indicators and metrics (i.e., hotspots can be identified and further modelled using system dynamics or agent based modelling and improved by data envelopment analysis (DEA and sustainability network theory (SNT. The framework is being applied to development of biofuel supply chain networks. The framework can provide new ways of integrating knowledge across the divides between social and natural sciences as well as between critical and problem-solving research.

Motivated information processing and group decision-making : Effects of process accountability on information processing and decision quality

NARCIS (Netherlands)

Scholten, Lotte; van Knippenberg, Daan; Nijstad, Bernard A.; De Dreu, Carsten K. W.

Integrating dual-process models [Chaiken, S., & Trope, Y. (Eds.). (1999). Dual-process theories in social psychology. NewYork: Guilford Press] with work on information sharing and group decision-making [Stasser, G., & Titus, W. (1985). Pooling of unshared information in group decision making: biased

CEO Appointments and the Loss of Firm-specific Knowledge - Putting Integrity Back into Hiring Decisions

DEFF Research Database (Denmark)

Rost, Katja; Salomo, Søren

2008-01-01

the last thirty years. Assuming that general managerial skills are becoming more important relative to firm-specific skills, the authors conclude that competition in the managerial labor market establishes optimal contracts. In our model and our empirical analysis we question this explanation by assuming...... that over the past decades the dishonesty of the predecessor has become relatively more important for the appointment decisions of firms. We conclude that outside hires are a suboptimal trend because external candidates even step up the regression of integrity in firms: As nobody has an incentive to invest...

CEO Appointments and the Loss of Firm-Specific Knowledge - Putting Integrity Back into Hiring Decisions

DEFF Research Database (Denmark)

Rost, Katja; Salomo, Søren; Osterloh, Margit

2008-01-01

the last thirty years. Assuming that general managerial skills are becoming more important relative to firm-specific skills, the authors conclude that competition in the managerial labor market establishes optimal contracts. In our model and our empirical analysis we question this explanation by assuming...... that over the past decades the dishonesty of the predecessor has become relatively more important for the appointment decisions of firms. We conclude that outside hires are a suboptimal trend because external candidates even step up the regression of integrity in firms: As nobody has an incentive to invest...

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

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.

Decision Support For Digester Algae Integration For Improved Environmental And Economic Sustainability

Energy Technology Data Exchange (ETDEWEB)

2017-06-28

The Idaho National Laboratory (INL) has teamed with University of Idaho and Boise State University to make the use of ADs more attractive by implementing a two-stage AD and coupling additional processes to the system. The addition of a polyhydroxyalkanoate (PHA) reactor, algae cultivation system, and a biomass treatment system such as fast-pyrolysis or hydrothermal liquefaction (HTL) would further sequester carbon and nutrients, as well as add valuable products that can be sold or used on-site to mitigate costs. The Decision-support for Digester-Algae IntegRation for Improved Environmental and Economic Sustainability (DAIRIEES) technoeconomic model will play a key role in evaluating the effectiveness and viability of this system to achieve economic and environmental sustainability by the dairy industry.

A model of interval timing by neural integration.

Science.gov (United States)

Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip

2011-06-22

We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.

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 ...

How the brain integrates costs and benefits during decision making

NARCIS (Netherlands)

Basten, U.; Biele, G.; Heekeren, H.R.; Fiebach, C.J.

2010-01-01

When we make decisions, the benefits of an option often need to be weighed against accompanying costs. Little is known, however, about the neural systems underlying such cost-benefit computations. Using functional magnetic resonance imaging and choice modeling, we show that decision making based on

An integrated environmental decision support system for water pollution control based on TMDL--A case study in the Beiyun River watershed.

Science.gov (United States)

Zhang, Shanghong; Li, Yueqiang; Zhang, Tianxiang; Peng, Yang

2015-06-01

This paper details the development and application of an integrated environmental decision support system (EDSS) for water pollution control based on total maximum daily load (TMDL). The system includes an infrastructure, simulation, and application platforms. Using the water pollution control of Beiyun River in China as a case study, the key development processes and technologies of the EDSS are discussed including relations and links between various environmental simulation models, and model integration, visualization and real-time simulation methods. A loose coupling method is used to connect the environmental models, and an XML file is used to complete data exchange between different models. Project configuration and scheme configuration are used for simulation data organization. The integration approach is easy to implement and enables different development languages and reuse of existing models. The EDSS has been applied to water environment management of Beiyun River, and can be applied to other geographic regions. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Decision making by relatives about brain death organ donation: an integrative review.

Science.gov (United States)

de Groot, Jack; Vernooij-Dassen, Myrra; Hoedemaekers, Cornelia; Hoitsma, Andries; Smeets, Wim; van Leeuwen, Evert

2012-06-27

Deciding about the organ donation of one's brain-dead beloved often occurs in an unexpected and delicate situation. We explored the decision making of the relatives of potential brain-dead donors, its evaluation, and the factors influencing decision making. We used the integrative review method. Our search included 10 databases. Inclusion criteria were presence of the donation request or the subsequent decision process. Three authors independently assessed the eligibility of identified articles. Content analysis of 70 included articles led to three themes: decision, evaluation, and support. We extracted results and recommendations concerning these three themes. The timing of the request and understandable information influence the decision. The relatives evaluate their decision differently: in case of refusal, approximately one third regret their decision, and in case of consent, approximately one tenth mention regret. The relatives are often ambivalent about their values (protection, altruism, and respect) and the deceased's wishes, not wanting additional suffering either for their beloved or for themselves. Support is mainly focused on increasing consent rates and less on satisfaction with the decision. Evaluation of decision making by the relatives of potential brain-dead donors reveals possibilities for improving the decision process. Special skills of the requester, attention to the circumstances, and unconditional support for the relatives might prevent the relatives' regret about refusal and unnecessary loss of organs. We hypothesize that support in exploring the relatives' values and the deceased's wishes can lead to stable decisions. This hypothesis deserves further investigation.

An Integrated Model for Identifying Linkages Between the Management of Fuel Treatments, Fire and Ecosystem Services

Science.gov (United States)

Bart, R. R.; Anderson, S.; Moritz, M.; Plantinga, A.; Tague, C.

2015-12-01

Vegetation fuel treatments (e.g. thinning, prescribed burning) are a frequent tool for managing fire-prone landscapes. However, predicting how fuel treatments may affect future wildfire risk and associated ecosystem services, such as forest water availability and streamflow, remains a challenge. This challenge is in part due to the large range of conditions under which fuel treatments may be implemented, as response is likely to vary with species type, rates of vegetation regrowth, meteorological conditions and physiographic properties of the treated site. It is also due to insufficient understanding of how social factors such as political pressure, public demands and economic constraints affect fuel management decisions. To examine the feedbacks between ecological and social dimensions of fuel treatments, we present an integrated model that links a biophysical model that simulates vegetation and hydrology (RHESSys), a fire spread model (WMFire) and an empirical fuel treatment model that accounts for agency decision-making. We use this model to investigate how management decisions affect landscape fuel loads, which in turn affect fire severity and ecosystem services, which feedback to management decisions on fuel treatments. We hypothesize that this latter effect will be driven by salience theory, which predicts that fuel treatments are more likely to occur following major wildfire events. The integrated model provides a flexible framework for answering novel questions about fuel treatments that span social and ecological domains, areas that have previously been treated separately.

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...

The Climate-Agriculture-Modeling and Decision Tool (CAMDT) for Climate Risk Management in Agriculture

Science.gov (United States)

Ines, A. V. M.; Han, E.; Baethgen, W.

2017-12-01

Advances in seasonal climate forecasts (SCFs) during the past decades have brought great potential to improve agricultural climate risk managements associated with inter-annual climate variability. In spite of popular uses of crop simulation models in addressing climate risk problems, the models cannot readily take seasonal climate predictions issued in the format of tercile probabilities of most likely rainfall categories (i.e, below-, near- and above-normal). When a skillful SCF is linked with the crop simulation models, the informative climate information can be further translated into actionable agronomic terms and thus better support strategic and tactical decisions. In other words, crop modeling connected with a given SCF allows to simulate "what-if" scenarios with different crop choices or management practices and better inform the decision makers. In this paper, we present a decision support tool, called CAMDT (Climate Agriculture Modeling and Decision Tool), which seamlessly integrates probabilistic SCFs to DSSAT-CSM-Rice model to guide decision-makers in adopting appropriate crop and agricultural water management practices for given climatic conditions. The CAMDT has a functionality to disaggregate a probabilistic SCF into daily weather realizations (either a parametric or non-parametric disaggregation method) and to run DSSAT-CSM-Rice with the disaggregated weather realizations. The convenient graphical user-interface allows easy implementation of several "what-if" scenarios for non-technical users and visualize the results of the scenario runs. In addition, the CAMDT also translates crop model outputs to economic terms once the user provides expected crop price and cost. The CAMDT is a practical tool for real-world applications, specifically for agricultural climate risk management in the Bicol region, Philippines, having a great flexibility for being adapted to other crops or regions in the world. CAMDT GitHub: https://github.com/Agro-Climate/CAMDT

Modeling of shallot supply decisions: the case of Indonesia

Science.gov (United States)

Prabawati, N. F.; Pujawan, I. N.; Widodo, E.

2018-04-01

To optimize supply chain role, the players of supply chain need to integrate its function. One of the general problems in supply chain was the unbalanced quantity of sales and quantity of supply. This paper focused on modelling a simple method to manage the gap between the demand and the supply. The gap might cause an overstock or a loss. This paper propose a buffer quantity in order to handle the gap by using import decision. The case study was about shallot supply - demand in Indonesia. In this study we model the supply decisions of shallot in Indonesia. While the demand was quite stable over time, the supply was heavily affected by the yield from the farms. The shortage could result in the government importing shallot from other countries. Hence, the government also needed to have a proper buffering mechanism in order to ensure the supply was sufficient and the price was quite stable. The initial model of this research was built by stochastic parameters and the extended model to gain pricing mechanism was built by Shapley value principal with modification. The primary variables were supply quantity, demand quantity, buffer and purchased quantity (stock needed), actual consumption, and price for three players. The validation proved that the result of price at each player presented a significant difference. Therefore, the model could be applied to decide the stock quantity needed and to keep the price stable at each player especially at the end player which would influence the market price.

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.

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.

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.

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.

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.  

Tools for collaborative decision-making

CERN Document Server

Zaraté, Pascale

2013-01-01

Decision-making has evolved recently thanks to the introduction of information and communication technologies in many organizations, which has led to new kinds of decision-making processes, called "collaborative decision-making", at the organizational and cognitive levels. This book looks at the development of the decision-making process in organizations. Decision-aiding and its paradigm of problem solving are defined, showing how decision-makers now need to work in a cooperative way. Definitions of cooperation and associated concepts such as collaboration and coordination are given and a framework of cooperative decision support systems is presented, including intelligent DSS, cooperative knowledge-based systems, workflow, group support systems, collaborative engineering, integrating with a collaborative decision-making model in part or being part of global projects. Several models and experimental studies are also included showing that these new processes have to be supported by new types of tools, several ...

The decision of out-of-home placement in residential care after parental neglect: Empirically testing a psychosocial model.

Science.gov (United States)

Rodrigues, Leonor; Calheiros, Manuela; Pereira, Cícero

2015-11-01

Out-of-home placement decisions in residential care are complex, ambiguous and full of uncertainty, especially in cases of parental neglect. Literature on this topic is so far unable to understand and demonstrate the source of errors involved in those decisions and still fails to focus on professional's decision making process. Therefore, this work intends to test a socio-psychological model of decision-making that is a more integrated, dualistic and ecological version of the Theory of Planned Behavior's model. It describes the process through which the decision maker takes into account personal, contextual and social factors of the Decision-Making Ecology in the definition of his/her decision threshold. One hundred and ninety-five professionals from different Children and Youth Protection Units, throughout the Portuguese territory, participated in this online study. After reading a vignette of a (psychological and physical) neglect case toward a one-year-old child, participants were presented with a group of questions that measured worker's assessment of risk, intention, attitude, subjective norm, behavior control and beliefs toward residential care placement decision, as well as worker's behavior experience, emotions and family/child-related-values involved in that decision. A set of structural equation modeling analyses have proven the good fit of the proposed model. The intention to propose a residential care placement decision was determined by cognitive, social, affective, value-laden and experience variables and the perceived risk. Altogether our model explained 61% of professional's decision toward a parental neglect case. The theoretical and practical implications of these results are discussed, namely the importance of raising awareness about the existence of these biased psychosocial determinants. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING AND RISK ASSESSMENT (SLIDE PRESENTATION)

Science.gov (United States)

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

Stakeholder views of management and decision support tools to integrate climate change into Great Lakes Lake Whitefish management

Science.gov (United States)

Lynch, Abigail J.; Taylor, William W.; McCright, Aaron M.

2016-01-01

Decision support tools can aid decision making by systematically incorporating information, accounting for uncertainties, and facilitating evaluation between alternatives. Without user buy-in, however, decision support tools can fail to influence decision-making processes. We surveyed fishery researchers, managers, and fishers affiliated with the Lake Whitefish Coregonus clupeaformis fishery in the 1836 Treaty Waters of Lakes Huron, Michigan, and Superior to assess opinions of current and future management needs to identify barriers to, and opportunities for, developing a decision support tool based on Lake Whitefish recruitment projections with climate change. Approximately 64% of 39 respondents were satisfied with current management, and nearly 85% agreed that science was well integrated into management programs. Though decision support tools can facilitate science integration into management, respondents suggest that they face significant implementation barriers, including lack of political will to change management and perceived uncertainty in decision support outputs. Recommendations from this survey can inform development of decision support tools for fishery management in the Great Lakes and other regions.

Decision model incorporating utility theory and measurement of social values applied to nuclear waste management

International Nuclear Information System (INIS)

Litchfield, J.W.; Hansen, J.V.; Beck, L.C.

1975-07-01

A generalized computer-based decision analysis model was developed and tested. Several alternative concepts for ultimate disposal have already been developed; however, significant research is still required before any of these can be implemented. To make a choice based on technical estimates of the costs, short-term safety, long-term safety, and accident detection and recovery requires estimating the relative importance of each of these factors or attributes. These relative importance estimates primarily involve social values and therefore vary from one individual to the next. The approach used was to sample various public groups to determine the relative importance of each of the factors to the public. These estimates of importance weights were combined in a decision analysis model with estimates, furnished by technical experts, of the degree to which each alternative concept achieves each of the criteria. This model then integrates the two separate and unique sources of information and provides the decision maker with information as to the preferences and concerns of the public as well as the technical areas within each concept which need further research. The model can rank the alternatives using sampled public opinion and techno-economic data. This model provides a decision maker with a structured approach to subdividing complex alternatives into a set of more easily considered attributes, measuring the technical performance of each alternative relative to each attribute, estimating relevant social values, and assimilating quantitative information in a rational manner to estimate total value for each alternative. Because of the explicit nature of this decision analysis, the decision maker can select a specific alternative supported by clear documentation and justification for his assumptions and estimates. (U.S.)

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...

A Model of Human Decision Making in Complex Systems and its Use for Design of System Control Strategies

DEFF Research Database (Denmark)

Rasmussen, Jens; Lind, Morten

The paper describes a model of operators' decision making in complex system control, based on studies of event reports and performance in control rooms. This study shows how operators base their decisions on knowledge of system properties at different levels of abstraction depending on their perc...... representation of system properties in a multilevel flow model is described to provide a basis for an integrated control system design.......The paper describes a model of operators' decision making in complex system control, based on studies of event reports and performance in control rooms. This study shows how operators base their decisions on knowledge of system properties at different levels of abstraction depending...... on their perception of the system's immediate control requirements. These levels correspond to the abstraction hierarchy including system purpose, functions, and physical details, which is generally used to describe a formal design process. In emergency situations the task of the operator is to design a suitable...

NED-2: a decision support system for integrated forest ecosystem management

Science.gov (United States)

Mark J. Twery; Peter D. Knopp; Scott A. Thomasma; H. Michael Rauscher; Donald E. Nute; Walter D. Potter; Frederick Maier; Jin Wang; Mayukh Dass; Hajime Uchiyama; Astrid Glende; Robin E. Hoffman

2005-01-01

NED-2 is a Windows-based system designed to improve project-level planning and decision making by providing useful and scientifically sound information to natural resource managers. Resources currently addressed include visual quality, ecology, forest health, timber, water, and wildlife. NED-2 expands on previous versions of NED applications by integrating treatment...

Integrating conflict analysis and consensus reaching in a decision support system for water resource management.

Science.gov (United States)

Giordano, R; Passarella, G; Uricchio, V F; Vurro, M

2007-07-01

The importance of shared decision processes in water management derives from the awareness of the inadequacy of traditional--i.e. engineering--approaches in dealing with complex and ill-structured problems. It is becoming increasingly obvious that traditional problem solving and decision support techniques, based on optimisation and factual knowledge, have to be combined with stakeholder based policy design and implementation. The aim of our research is the definition of an integrated decision support system for consensus achievement (IDSS-C) able to support a participative decision-making process in all its phases: problem definition and structuring, identification of the possible alternatives, formulation of participants' judgments, and consensus achievement. Furthermore, the IDSS-C aims at structuring, i.e. systematising the knowledge which has emerged during the participative process in order to make it comprehensible for the decision-makers and functional for the decision process. Problem structuring methods (PSM) and multi-group evaluation methods (MEM) have been integrated in the IDSS-C. PSM are used to support the stakeholders in providing their perspective of the problem and to elicit their interests and preferences, while MEM are used to define not only the degree of consensus for each alternative, highlighting those where the agreement is high, but also the consensus label for each alternative and the behaviour of individuals during the participative decision-making. The IDSS-C is applied experimentally to a decision process regarding the use of treated wastewater for agricultural irrigation in the Apulia Region (southern Italy).

Integrating observations and models to help understanding how flooding impacts upon catchments as a basis for decision making.

Science.gov (United States)

Owen, Gareth; Quinn, Paul; O'Donnell, Greg

2014-05-01

This paper explains how flood management projects might be better informed in the future by using more observations and a novel impact modelling tool in a simple transparent framework. The understanding of how local scale impacts propagate downstream to impact on the downstream hydrograph is difficult to determine using traditional rainfall runoff and hydraulic routing methods. The traditional approach to modelling essentially comprises selecting a fixed model structure and then calibrating to an observational hydrograph, which make those model predictions highly uncertain. Here, a novel approach is used in which the structure of the runoff generation is not specified a priori and incorporates expert knowledge. Rather than using externally for calibration, the observed outlet hydrographs are used directly within the model. Essentially the approach involves the disaggregation of the outlet hydrograph by making assumptions about the spatial distribution of runoff generated. The channel network is parameterised through a comparison of the timing of observed hydrographs at a number of nested locations within the catchment. The user is then encouraged to use their expert knowledge to define how runoff is generated locally and what the likely impact of any local mitigation is. Therefore the user can specify any hydrological model or flow estimation method that captures their expertise. Equally, the user is encouraged to install as many instruments as they can afford to cover the catchment network. A Decision Support Matrix (DSM) is used to encapsulate knowledge of the runoff dynamics gained from simulation in a simple visual way and hence to convey the likely impacts that arise from a given flood management scenario. This tool has been designed primarily to inform and educate landowners, catchment managers and decision makers. The DSM outlines scenarios that are likely to increase or decrease runoff rates and allows the user to contemplate the implications and

A conceptual and computational model of moral decision making in human and artificial agents.

Science.gov (United States)

Wallach, Wendell; Franklin, Stan; Allen, Colin

2010-07-01

Recently, there has been a resurgence of interest in general, comprehensive models of human cognition. Such models aim to explain higher-order cognitive faculties, such as deliberation and planning. Given a computational representation, the validity of these models can be tested in computer simulations such as software agents or embodied robots. The push to implement computational models of this kind has created the field of artificial general intelligence (AGI). Moral decision making is arguably one of the most challenging tasks for computational approaches to higher-order cognition. The need for increasingly autonomous artificial agents to factor moral considerations into their choices and actions has given rise to another new field of inquiry variously known as Machine Morality, Machine Ethics, Roboethics, or Friendly AI. In this study, we discuss how LIDA, an AGI model of human cognition, can be adapted to model both affective and rational features of moral decision making. Using the LIDA model, we will demonstrate how moral decisions can be made in many domains using the same mechanisms that enable general decision making. Comprehensive models of human cognition typically aim for compatibility with recent research in the cognitive and neural sciences. Global workspace theory, proposed by the neuropsychologist Bernard Baars (1988), is a highly regarded model of human cognition that is currently being computationally instantiated in several software implementations. LIDA (Franklin, Baars, Ramamurthy, & Ventura, 2005) is one such computational implementation. LIDA is both a set of computational tools and an underlying model of human cognition, which provides mechanisms that are capable of explaining how an agent's selection of its next action arises from bottom-up collection of sensory data and top-down processes for making sense of its current situation. We will describe how the LIDA model helps integrate emotions into the human decision-making process, and we

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.

Development of an integrated economic decision-support tool for the remediation of contaminated sites. Overview note

International Nuclear Information System (INIS)

Samson, R.; Bage, G.

2004-05-01

This report concludes the first design phase of an innovative software tool which, when completed, will allow managers of contaminated sites to make optimal decisions with respect to site remediation. The principal objective of the project was to develop the foundations for decision-support software (SITE VII) which will allow a comprehensive and rigorous approach to the comparison of remediation scenarios for sites contaminated with petroleum hydrocarbons. During this first phase of the project, the NSERC Industrial Chair in Site Remediation and Management of the Ecole Polytechnique de Montreal has completed four stages in the design of a decision-support tool that could be applied by any site manager using a simple computer. These four stages are: refinement of a technico-economic evaluation model; development of databases for five soil remediation technologies; design of a structure for integration of the databases with the technico-economic model; and simulation of the remediation of a contaminated site using the technico-economic model and a subset of the databases. In the interim report, the emphasis was placed on the development of the technico-economic model, supported by a very simple, single-technology simulation of remediation. In the present report, the priority is placed on the integration of the different components required for the creation of decision-support software based on the technico-economic model. An entire chapter of this report is devoted to elaborating the decision structure of the software. The treatment of information within the software is shown schematically and explained step-by-step. Five remediation technologies are handled by the software: three in-situ technologies (bio-venting, bio-slurping, bio-sparging) and two ex-situ technologies (thermal desorption, Bio-pile treatment). A technology file has been created for each technology, containing a brief description of the technology, its performance, its criteria of applicability

Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment

International Nuclear Information System (INIS)

Wanderer, Thomas; Herle, Stefan

2015-01-01

By their spatially very distributed nature, profitability and impacts of renewable energy resources are highly correlated with the geographic locations of power plant deployments. A web-based Spatial Decision Support System (SDSS) based on a Multi-Criteria Decision Analysis (MCDA) approach has been implemented for identifying preferable locations for solar power plants based on user preferences. The designated areas found serve for the input scenario development for a subsequent integrated Environmental Impact Assessment. The capabilities of the SDSS service get showcased for Concentrated Solar Power (CSP) plants in the region of Andalusia, Spain. The resulting spatial patterns of possible power plant sites are an important input to the procedural chain of assessing impacts of renewable energies in an integrated effort. The applied methodology and the implemented SDSS are applicable for other renewable technologies as well. - Highlights: • The proposed tool facilitates well-founded CSP plant siting decisions. • Spatial MCDA methods are implemented in a WebGIS environment. • GIS-based SDSS can contribute to a modern integrated impact assessment workflow. • The conducted case study proves the suitability of the methodology

Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment

Energy Technology Data Exchange (ETDEWEB)

Wanderer, Thomas, E-mail: thomas.wanderer@dlr.de; Herle, Stefan, E-mail: stefan.herle@rwth-aachen.de

2015-04-15

By their spatially very distributed nature, profitability and impacts of renewable energy resources are highly correlated with the geographic locations of power plant deployments. A web-based Spatial Decision Support System (SDSS) based on a Multi-Criteria Decision Analysis (MCDA) approach has been implemented for identifying preferable locations for solar power plants based on user preferences. The designated areas found serve for the input scenario development for a subsequent integrated Environmental Impact Assessment. The capabilities of the SDSS service get showcased for Concentrated Solar Power (CSP) plants in the region of Andalusia, Spain. The resulting spatial patterns of possible power plant sites are an important input to the procedural chain of assessing impacts of renewable energies in an integrated effort. The applied methodology and the implemented SDSS are applicable for other renewable technologies as well. - Highlights: • The proposed tool facilitates well-founded CSP plant siting decisions. • Spatial MCDA methods are implemented in a WebGIS environment. • GIS-based SDSS can contribute to a modern integrated impact assessment workflow. • The conducted case study proves the suitability of the methodology.

Integration of Social Aspects in Decision Support, Based on Life Cycle Thinking

Directory of Open Access Journals (Sweden)

Pere Fullana-i-Palmer

2011-03-01

Full Text Available Recently increasing attention has been paid to complementing environmental Life Cycle Assessment (LCA with social aspects. The paper discusses the selection of social impacts and indicators from existing frameworks like Social Life Cycle Assessment (SLCA and Social Impact Assessment (SIA. Two ongoing case studies, addressing sustainability assessment within decision support, were considered: (1 Integrated Water Resources Management (IWRM in Indonesia; and (2 Integrated Packaging Waste Management in Spain and Portugal (FENIX. The focus was put on social impacts occurring due to decisions within these systems, such as choice of technologies, practices or suppliers. Thus, decision makers—here understood as intended users of the studies’ results—are not consumers that buy (or do not buy a product, such as in recent SLCA case-studies, but mainly institutions that decide about the design of the water or packaging waste management system. Therefore, in the FENIX project, a list of social impacts identified from literature was sent to the intended users to be ranked according to their priorities. Finally, the paper discusses to what extent the entire life cycle is reflected in SLCA impact categories and indicators, and explains how both life-cycle and on-site-related social impacts were chosen to be assessed. However, not all indicators in the two projects will assess all stages of the life cycle, because of their varying relevance in the different stages, data availability and practical interest of decision makers.

Development of an integrated model for the Campaspe catchment: a tool to help improve understanding of the interaction between society, policy, farming decision, ecology, hydrology and climate

Science.gov (United States)

Iwanaga, Takuya; Zare, Fateme; Croke, Barry; Fu, Baihua; Merritt, Wendy; Partington, Daniel; Ticehurst, Jenifer; Jakeman, Anthony

2018-06-01

Management of water resources requires understanding of the hydrology and hydrogeology, as well as the policy and human drivers and their impacts. This understanding requires relevant inputs from a wide range of disciplines, which will vary depending on the specific case study. One approach to gain understanding of the impact of climate and society on water resources is through the use of an integrated modelling process that engages stakeholders and experts in specifics of problem framing, co-design of the underpinning conceptual model, and discussion of the ensuing results. In this study, we have developed such an integrated modelling process for the Campaspe basin in northern Victoria, Australia. The numerical model built has a number of components: - Node/link based surface water hydrology module based on the IHACRES rainfall-streamflow model - Distributed groundwater model for the lower catchment (MODFLOW) - Farm decision optimisation module (to determine irrigation requirements) - Policy module (setting conditions on availability of water based on existing rules) - Ecology module (determining the impacts of available streamflow on platypus, fish and river red gum trees) The integrated model is component based and has been developed in Python, with the MODFLOW and surface water hydrology model run in external programs, controlled by the master program (in Python). The integrated model has been calibrated using historical data, with the intention of exploring the impact of various scenarios (future climate scenarios, different policy options, water management options) on the water resources. The scenarios were selected based on workshops with, and a social survey of, stakeholders in the basin regarding what would be socially acceptable and physically plausible options for changes in management. An example of such a change is the introduction of a managed aquifer recharge system to capture dam overflows, and store at least a portion of this in the aquifer

Characteristic times in the English Channel from numerical modelling: supporting decision-making

Energy Technology Data Exchange (ETDEWEB)

Perianez, R [Departamento de Fisica Aplicada 1, Universidad de Sevilla, EUITA, Carretera Utrera km 1, 41013 Sevilla (Spain); Miro, C [Departamento de Fisica Aplicada, Facultad de Veterinaria, Universidad de Extremadura, Avenida de la Universidad s/n, 10071 Caceres (Spain)], E-mail: rperianez@us.es, E-mail: cmiro@unex.es

2009-06-15

A numerical model that simulates the dispersion of radionuclides in the English Channel has been applied to study the dispersion of conservative and non-conservative radionuclides released from the La Hague nuclear fuel reprocessing plant. The model is based upon previous work and now is able to simulate dispersion over long timescales (decades), explicitly including transport by instantaneous tidal currents and variable wind conditions. Wind conditions are obtained from meteorological statistics using a stochastic method. Outputs from the model are treated using time-series analysis techniques. These techniques allow the determination of characteristic times of the system, transport velocities and dispersion factors. This information may be very useful to support the decision-making process after an emergency situation. Thus, we are proposing that time-series analysis can be integrated with numerical modelling for helping decision-making in response to an accident. The model is first validated through its application to actual releases of {sup 99}Tc and {sup 125}Sb, comparing measured and computed concentrations, and characteristic times for three radionuclides are given next: a perfectly conservative one, a very reactive one ({sup 239,240}Pu) and {sup 137}Cs, which has an intermediate behaviour. Characteristic transport velocities and dispersion factors have been calculated as well. Model results are supported by experimental evidence.

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

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...

Iterative integral parameter identification of a respiratory mechanics model

Directory of Open Access Journals (Sweden)

Schranz Christoph

2012-07-01

Full Text Available Abstract Background Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual’s model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. Methods An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS patients. Results The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. Conclusion These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.

A decision support system for on-line leakage localization

OpenAIRE

Meseguer, Jordi; Mirats-Tur, Josep M.; Cembrano, Gabriela; Puig, Vicenç; Quevedo, Joseba; Pérez, Ramon; Sanz, Gerard; Ibarra, David

2014-01-01

This paper describes a model-driven decision-support system (software tool) implementing a model-based methodology for on-line leakage detection and localization which is useful for a large class of water distribution networks. Since these methods present a certain degree of complexity which limits their use to experts, the proposed software tool focuses on the integration of a method emphasizing its use by water network managers as a decision support system. The proposed software tool integr...

Integrated model for supplier selection and performance evaluation

Directory of Open Access Journals (Sweden)

Borges de Araújo, Maria Creuza

2015-08-01

Full Text Available This paper puts forward a model for selecting suppliers and evaluating the performance of those already working with a company. A simulation was conducted in a food industry. This sector has high significance in the economy of Brazil. The model enables the phases of selecting and evaluating suppliers to be integrated. This is important so that a company can have partnerships with suppliers who are able to meet their needs. Additionally, a group method is used to enable managers who will be affected by this decision to take part in the selection stage. Finally, the classes resulting from the performance evaluation are shown to support the contractor in choosing the most appropriate relationship with its suppliers.

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

CERN Document Server

Murthy, D N Prabhakar

2014-01-01

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

Sleep Disruption Medical Intervention Forecasting (SDMIF) Module for the Integrated Medical Model

Science.gov (United States)

Lewandowski, Beth; Brooker, John; Mallis, Melissa; Hursh, Steve; Caldwell, Lynn; Myers, Jerry

2011-01-01

The NASA Integrated Medical Model (IMM) assesses the risk, including likelihood and impact of occurrence, of all credible in-flight medical conditions. Fatigue due to sleep disruption is a condition that could lead to operational errors, potentially resulting in loss of mission or crew. Pharmacological consumables are mitigation strategies used to manage the risks associated with sleep deficits. The likelihood of medical intervention due to sleep disruption was estimated with a well validated sleep model and a Monte Carlo computer simulation in an effort to optimize the quantity of consumables. METHODS: The key components of the model are the mission parameter program, the calculation of sleep intensity and the diagnosis and decision module. The mission parameter program was used to create simulated daily sleep/wake schedules for an ISS increment. The hypothetical schedules included critical events such as dockings and extravehicular activities and included actual sleep time and sleep quality. The schedules were used as inputs to the Sleep, Activity, Fatigue and Task Effectiveness (SAFTE) Model (IBR Inc., Baltimore MD), which calculated sleep intensity. Sleep data from an ISS study was used to relate calculated sleep intensity to the probability of sleep medication use, using a generalized linear model for binomial regression. A human yes/no decision process using a binomial random number was also factored into sleep medication use probability. RESULTS: These probability calculations were repeated 5000 times resulting in an estimate of the most likely amount of sleep aids used during an ISS mission and a 95% confidence interval. CONCLUSIONS: These results were transferred to the parent IMM for further weighting and integration with other medical conditions, to help inform operational decisions. This model is a potential planning tool for ensuring adequate sleep during sleep disrupted periods of a mission.

Using Petri nets for modeling enterprise integration patterns

NARCIS (Netherlands)

Fahland, D.; Gierds, C.

2012-01-01

Enterprise Integration Patterns are a collection of widely used patterns for integrating enterprise applications and business processes. These patterns informally represent typical design decisions for connecting enterprise applications. For the set of patterns collected by Hohpe and Woolf in

Optimal Decision-making Model of Integrated Water Resources Management - A Case of Hsinchu Water Resources Management

Science.gov (United States)

Wang, S. Y.; Ho, C. C.; Chang, L. C.

2017-12-01

The public use water in Hsinchu are mainly supplied from Baoshan Reservoir, Second Baoshan Reservoir, Yongheshan Reservoir and Longen Weir. However, the increasing water demand, caused by development of the Hsinchu Science and Industrial Park, results in supply stable water getting more difficult. For stabilize water supply in Hsinchu, the study applies long-term and short-term plans to fulfill the water shortage. Developing an efficient methodology to define a cost-effective action portfolio is an important task. Hence, the study develops a novel decision model, the Stochastic Programming with Recourse Decision Model (SPRDM), to estimate a cost-effective action portfolio. The first-stage of SPRDM determine the long-term action portfolio and the portfolio accompany recourse information (the probability for water shortage event). The second-stage of SPRDM optimize the cost-effective action portfolio in response to the recourse information. In order to consider the uncertainty of reservoir sediment and demand growth, the study set 9 scenarios comprise optimistic, most likely, and pessimistic reservoir sediment and demand growth. The results show the optimal action portfolio consist of FengTain Lake and Panlon Weir, Hsinchu Desalination Plant, Domestic and Industrial Water long-term plans, and Emergency Backup Well, Irrigation Water Transference, Preliminary Water Rationing, Advanced Water Rationing and Water Transport from Other Districts short-term plans. The minimum expected cost of optimal action portfolio is NT$1.1002 billion. The results can be used as a reference for decision making because the results have considered the uncertainty of varied hydrology, reservoir sediment, and water demand growth.

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…

Evaluating community investments in the mining sector using multi-criteria decision analysis to integrate SIA with business planning

International Nuclear Information System (INIS)

Esteves, A.M.

2008-01-01

Gaining senior management's commitment to long-term social development projects, which are characterised by uncertainty and complexity, is made easier if projects are shown to benefit the site's strategic goals. However, even though the business case for community investment may have been accepted at a general level, as a strategy for competitive differentiation, risk mitigation and a desire to deliver - and to be seen to deliver - a 'net benefit' to affected communities, mining operations are still faced with implementation challenges. Case study research on mining companies, including interviews with social investment decision-makers, has assisted in developing the Social Investment Decision Analysis Tool (SIDAT), a decision model for evaluating social projects in order to create value for both the company and the community. Multi-criteria decision analysis techniques integrating business planning processes with social impact assessment have proved useful in assisting mining companies think beyond the traditional drivers (i.e. seeking access to required lands and peaceful relations with neighbours), to broader issues of how they can meet their business goals and contribute to sustainable development in the regions in which they operate

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.

Handling risk attitudes for preference learning and intelligent decision support

DEFF Research Database (Denmark)

Franco de los Ríos, Camilo; Hougaard, Jens Leth; Nielsen, Kurt

2015-01-01

Intelligent decision support should allow integrating human knowledge with efficient algorithms for making interpretable and useful recommendations on real world decision problems. Attitudes and preferences articulate and come together under a decision process that should be explicitly modeled...

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.

Integrated environmental decision support tool based on GIS technology

International Nuclear Information System (INIS)

Doctor, P.G.; O'Neil, T.K.; Sackschewsky, M.R.; Becker, J.M.; Rykiel, E.J.; Walters, T.B.; Brandt, C.A.; Hall, J.A.

1995-01-01

Environmental restoration and management decisions facing the US Department of Energy require balancing trade-offs between diverse land uses and impacts over multiple spatial and temporal scales. Many types of environmental data have been collected for the Hanford Site and the Columbia River in Washington State over the past fifty years. Pacific Northwest National Laboratory (PNNL) is integrating these data into a Geographic Information System (GIS) based computer decision support tool. This tool provides a comprehensive and concise description of the current environmental landscape that can be used to evaluate the ecological and monetary trade-offs between future land use, restoration and remediation options before action is taken. Ecological impacts evaluated include effects to individual species of concern and habitat loss and fragmentation. Monetary impacts include those associated with habitat mitigation. The tool is organized as both a browsing tool for educational purposes, and as a framework that leads a project manager through the steps needed to be in compliance with environmental requirements

Modeling energy-economy interactions using integrated models

International Nuclear Information System (INIS)

Uyterlinde, M.A.

1994-06-01

Integrated models are defined as economic energy models that consist of several submodels, either coupled by an interface module, or embedded in one large model. These models can be used for energy policy analysis. Using integrated models yields the following benefits. They provide a framework in which energy-economy interactions can be better analyzed than in stand-alone models. Integrated models can represent both energy sector technological details, as well as the behaviour of the market and the role of prices. Furthermore, the combination of modeling methodologies in one model can compensate weaknesses of one approach with strengths of another. These advantages motivated this survey of the class of integrated models. The purpose of this literature survey therefore was to collect and to present information on integrated models. To carry out this task, several goals were identified. The first goal was to give an overview of what is reported on these models in general. The second one was to find and describe examples of such models. Other goals were to find out what kinds of models were used as component models, and to examine the linkage methodology. Solution methods and their convergence properties were also a subject of interest. The report has the following structure. In chapter 2, a 'conceptual framework' is given. In chapter 3 a number of integrated models is described. In a table, a complete overview is presented of all described models. Finally, in chapter 4, the report is summarized, and conclusions are drawn regarding the advantages and drawbacks of integrated models. 8 figs., 29 refs

Integrated Modeling of Solutions in the System of Distributing Logistics of a Fruit and Vegetable Cooperative

Directory of Open Access Journals (Sweden)

Oleksandr Velychko

2014-12-01

Full Text Available A mechanism of preparing rationalistic solutions in the system of distributing logistics of a fruit and vegetable cooperative has been studied considering possible alternatives and existing limitations. Belonging of separate operations of the fruit and vegetable cooperative to technological, logistical or marketing business processes has been identified. Expediency of the integrated use of logistical concept DRP, decision tree method and linear programming in management of the cooperative has been grounded. The model for preparing decisions on organizing sales of vegetables and fruit which is focused on minimization of costs of cooperative services and maximization of profits for members of the cooperation has been developed. The necessity to consider integrated model of differentiation on levels of post gathering processing and logistical service has been revealed. Methodology of representation in the economical-mathematical model of probabilities in the tree of decisions concerning the expected amount of sales and margin for members of the cooperative using different channels has been processed. A formula which enables scientists to describe limitations in linear programming concerning critical duration of providing harvest of vegetables and fruit after gathering towards a customer has been suggested.

NARAC Dispersion Model Product Integration With RadResponder

Energy Technology Data Exchange (ETDEWEB)

Aluzzi, Fernando [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2015-09-30

Work on enhanced cooperation and interoperability of Nuclear Incident Response Teams (NIRT) is a joint effort between DHS/FEMA, DOE/NNSA and EPA. One such effort was the integration between the RadResponder Network, a resource sponsored by FEMA for the management of radiological data during an emergency, and the National Atmospheric Advisory Center (NARAC), a DOE/NNSA modeling resource whose predictions are used to aid radiological emergency preparedness and response. Working together under a FEMA-sponsored project these two radiological response assets developed a capability to read and display plume model prediction results from the NARAC computer system in the RadResponder software tool. As a result of this effort, RadResponder users have been provided with NARAC modeling predictions of contamination areas, radiological dose levels, and protective action areas (e.g., areas warranting worker protection or sheltering/evacuation) to help guide protective action decisions and field monitoring surveys, and gain key situation awareness following a radiological/nuclear accident or incident (e.g., nuclear power plant accident, radiological dispersal device incident, or improvised nuclear detonation incident). This document describes the details of this integration effort.

Non-market forest ecosystem services and decision support in Nordic countries

DEFF Research Database (Denmark)

Filyushkina, Anna; Strange, Niels; Löf, Magnus

2016-01-01

The need to integrate non-market ecosystem services into decision-making is widely acknowledged. Despite the exponentially growing body of literature, trade-offs between services are still poorly understood. We conducted a systematic review of published literature in the Nordic countries (Denmark......, Norway, Sweden and Finland) on the integration of non-market forest ecosystem services into decision-making. The aim of the review was two-fold: (1) to provide an overview of coverage of biophysical and socio-economic assessments of non-market ecosystem services in relation to forest management; (2......) to determine the extent of the integration of biophysical and socio-economic models of these services into decision support models. Our findings reveal the need for wider coverage of non-market ecosystem services and evidence-based modelling of how forest management regimes affect ecosystem services...

Social Influences in Sequential Decision Making.

Directory of Open Access Journals (Sweden)

Markus Schöbel

Full Text Available People often make decisions in a social environment. The present work examines social influence on people's decisions in a sequential decision-making situation. In the first experimental study, we implemented an information cascade paradigm, illustrating that people infer information from decisions of others and use this information to make their own decisions. We followed a cognitive modeling approach to elicit the weight people give to social as compared to private individual information. The proposed social influence model shows that participants overweight their own private information relative to social information, contrary to the normative Bayesian account. In our second study, we embedded the abstract decision problem of Study 1 in a medical decision-making problem. We examined whether in a medical situation people also take others' authority into account in addition to the information that their decisions convey. The social influence model illustrates that people weight social information differentially according to the authority of other decision makers. The influence of authority was strongest when an authority's decision contrasted with private information. Both studies illustrate how the social environment provides sources of information that people integrate differently for their decisions.

Social Influences in Sequential Decision Making

Science.gov (United States)

Schöbel, Markus; Rieskamp, Jörg; Huber, Rafael

2016-01-01

People often make decisions in a social environment. The present work examines social influence on people’s decisions in a sequential decision-making situation. In the first experimental study, we implemented an information cascade paradigm, illustrating that people infer information from decisions of others and use this information to make their own decisions. We followed a cognitive modeling approach to elicit the weight people give to social as compared to private individual information. The proposed social influence model shows that participants overweight their own private information relative to social information, contrary to the normative Bayesian account. In our second study, we embedded the abstract decision problem of Study 1 in a medical decision-making problem. We examined whether in a medical situation people also take others’ authority into account in addition to the information that their decisions convey. The social influence model illustrates that people weight social information differentially according to the authority of other decision makers. The influence of authority was strongest when an authority's decision contrasted with private information. Both studies illustrate how the social environment provides sources of information that people integrate differently for their decisions. PMID:26784448

Social Influences in Sequential Decision Making.

Science.gov (United States)

Schöbel, Markus; Rieskamp, Jörg; Huber, Rafael

2016-01-01

People often make decisions in a social environment. The present work examines social influence on people's decisions in a sequential decision-making situation. In the first experimental study, we implemented an information cascade paradigm, illustrating that people infer information from decisions of others and use this information to make their own decisions. We followed a cognitive modeling approach to elicit the weight people give to social as compared to private individual information. The proposed social influence model shows that participants overweight their own private information relative to social information, contrary to the normative Bayesian account. In our second study, we embedded the abstract decision problem of Study 1 in a medical decision-making problem. We examined whether in a medical situation people also take others' authority into account in addition to the information that their decisions convey. The social influence model illustrates that people weight social information differentially according to the authority of other decision makers. The influence of authority was strongest when an authority's decision contrasted with private information. Both studies illustrate how the social environment provides sources of information that people integrate differently for their decisions.

Medical Device Integrated Vital Signs Monitoring Application with Real-Time Clinical Decision Support.

Science.gov (United States)

Moqeem, Aasia; Baig, Mirza; Gholamhosseini, Hamid; Mirza, Farhaan; Lindén, Maria

2018-01-01

This research involves the design and development of a novel Android smartphone application for real-time vital signs monitoring and decision support. The proposed application integrates market available, wireless and Bluetooth connected medical devices for collecting vital signs. The medical device data collected by the app includes heart rate, oxygen saturation and electrocardiograph (ECG). The collated data is streamed/displayed on the smartphone in real-time. This application was designed by adopting six screens approach (6S) mobile development framework and focused on user-centered approach and considered clinicians-as-a-user. The clinical engagement, consultations, feedback and usability of the application in the everyday practices were considered critical from the initial phase of the design and development. Furthermore, the proposed application is capable to deliver rich clinical decision support in real-time using the integrated medical device data.

A novel sustainable decision making model for municipal solid waste management

International Nuclear Information System (INIS)

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

2007-01-01

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

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 building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building

Farm Household Economic Model of The Integrated Crop Livestock System: Conceptual and Empirical Study

Directory of Open Access Journals (Sweden)

Atien Priyanti

2007-06-01

Full Text Available An integrated approach to enhance rice production in Indonesia is very prospectus throughout the implementation of adapted and liable integrated program. One of the challenges in rice crop sub sector is the stagnation of its production due to the limitation of organic matter availability. This provides an opportunity for livestock development to overcome the problems on land fertility through the use of manure as the source of organic fertilizer. Ministry of Agriculture had implemented a program on Increasing Integrated Rice Productivity with an Integrated Crop Livestock System as one of the potential components since 2002. Integrated crop livestock system program with special reference to rice field and beef cattle is an alternative to enhance the potential development of agriculture sector in Indonesia. The implementation on this integrated program is to enhance rice production and productivity through a system involving beef cattle with its goal on increasing farmers’ income. Household economic model can be used as one of the analysis to evaluate the success of the implemented crop livestock system program. The specificity of the farmers is that rationality behavior of the role as production and consumption decision making. In this case, farmers perform the production to meet home consumption based on the resources that used directly for its production. The economic analysis of farmers household can be described to anticipate policy options through this model. Factors influencing farmers’ decisions and direct interrelations to production and consumption aspects that have complex implications for the farmers’ welfare of the integrated crop livestock system program.

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...

Comparing perceptual and preferential decision making.

Science.gov (United States)

Dutilh, Gilles; Rieskamp, Jörg

2016-06-01

Perceptual and preferential decision making have been studied largely in isolation. Perceptual decisions are considered to be at a non-deliberative cognitive level and have an outside criterion that defines the quality of decisions. Preferential decisions are considered to be at a higher cognitive level and the quality of decisions depend on the decision maker's subjective goals. Besides these crucial differences, both types of decisions also have in common that uncertain information about the choice situation has to be processed before a decision can be made. The present work aims to acknowledge the commonalities of both types of decision making to lay bare the crucial differences. For this aim we examine perceptual and preferential decisions with a novel choice paradigm that uses the identical stimulus material for both types of decisions. This paradigm allows us to model the decisions and response times of both types of decisions with the same sequential sampling model, the drift diffusion model. The results illustrate that the different incentive structure in both types of tasks changes people's behavior so that they process information more efficiently and respond more cautiously in the perceptual as compared to the preferential task. These findings set out a perspective for further integration of perceptual and preferential decision making in a single ramework.

An integrated model of statistical process control and maintenance based on the delayed monitoring

International Nuclear Information System (INIS)

Yin, Hui; Zhang, Guojun; Zhu, Haiping; Deng, Yuhao; He, Fei

2015-01-01

This paper develops an integrated model of statistical process control and maintenance decision. The proposal of delayed monitoring policy postpones the sampling process till a scheduled time and contributes to ten-scenarios of the production process, where equipment failure may occur besides quality shift. The equipment failure and the control chart alert trigger the corrective maintenance and the predictive maintenance, respectively. The occurrence probability, the cycle time and the cycle cost of each scenario are obtained by integral calculation; therefore, a mathematical model is established to minimize the expected cost by using the genetic algorithm. A Monte Carlo simulation experiment is conducted and compared with the integral calculation in order to ensure the analysis of the ten-scenario model. Another ordinary integrated model without delayed monitoring is also established as comparison. The results of a numerical example indicate satisfactory economic performance of the proposed model. Finally, a sensitivity analysis is performed to investigate the effect of model parameters. - Highlights: • We develop an integrated model of statistical process control and maintenance. • We propose delayed monitoring policy and derive an economic model with 10 scenarios. • We consider two deterioration mechanisms, quality shift and equipment failure. • The delayed monitoring policy will help reduce the expected cost

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 ...

FUZZY DECISION ANALYSIS FOR INTEGRATED ENVIRONMENTAL VULNERABILITY ASSESSMENT OF THE MID-ATLANTIC REGION

Science.gov (United States)

A fuzzy decision analysis method for integrating ecological indicators is developed. This is a combination of a fuzzy ranking method and the Analytic Hierarchy Process (AHP). The method is capable ranking ecosystems in terms of environmental conditions and suggesting cumula...

Database modeling to integrate macrobenthos data in Spatial Data Infrastructure

Directory of Open Access Journals (Sweden)

José Alberto Quintanilha

2012-08-01

Full Text Available Coastal zones are complex areas that include marine and terrestrial environments. Besides its huge environmental wealth, they also attracts humans because provides food, recreation, business, and transportation, among others. Some difficulties to manage these areas are related with their complexity, diversity of interests and the absence of standardization to collect and share data to scientific community, public agencies, among others. The idea to organize, standardize and share this information based on Web Atlas is essential to support planning and decision making issues. The construction of a spatial database integrating the environmental business, to be used on Spatial Data Infrastructure (SDI is illustrated by a bioindicator that indicates the quality of the sediments. The models show the phases required to build Macrobenthos spatial database based on Santos Metropolitan Region as a reference. It is concluded that, when working with environmental data the structuring of knowledge in a conceptual model is essential for their subsequent integration into the SDI. During the modeling process it can be noticed that methodological issues related to the collection process may obstruct or prejudice the integration of data from different studies of the same area. The development of a database model, as presented in this study, can be used as a reference for further research with similar goals.

Modeling Feedbacks Between Individual Human Decisions and Hydrology Using Interconnected Physical and Social Models

Science.gov (United States)

Murphy, J.; Lammers, R. B.; Proussevitch, A. A.; Ozik, J.; Altaweel, M.; Collier, N. T.; Alessa, L.; Kliskey, A. D.

2014-12-01

The global hydrological cycle intersects with human decision making at multiple scales, from dams and irrigation works to the taps in individuals' homes. Residential water consumers are commonly encouraged to conserve; these messages are heard against a background of individual values and conceptions about water quality, uses, and availability. The degree to which these values impact the larger-hydrological dynamics, the way that changes in those values have impacts on the hydrological cycle through time, and the feedbacks by which water availability and quality in turn shape those values, are not well explored. To investigate this domain we employ a global-scale water balance model (WBM) coupled with a social-science-grounded agent-based model (ABM). The integration of a hydrological model with an agent-based model allows us to explore driving factors in the dynamics in coupled human-natural systems. From the perspective of the physical hydrologist, the ABM offers a richer means of incorporating the human decisions that drive the hydrological system; from the view of the social scientist, a physically-based hydrological model allows the decisions of the agents to play out against constraints faithful to the real world. We apply the interconnected models to a study of Tucson, Arizona, USA, and its role in the larger Colorado River system. Our core concept is Technology-Induced Environmental Distancing (TIED), which posits that layers of technology can insulate consumers from direct knowledge of a resource. In Tucson, multiple infrastructure and institutional layers have arguably increased the conceptual distance between individuals and their water supply, offering a test case of the TIED framework. Our coupled simulation allows us to show how the larger system transforms a resource with high temporal and spatial variability into a consumer constant, and the effects of this transformation on the regional system. We use this to explore how pricing, messaging, and

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...

Design of an integrated forward and reverse logistics network optimi-zation model for commercial goods management

Directory of Open Access Journals (Sweden)

Eva Ponce-Cueto

2015-01-01

Full Text Available In this study, an optimization model is formulated for designing an integrated forward and reverse logistics network in the consumer goods industry. The resultant model is a mixed-integer linear programming model (MILP. Its purpose is to minimize the total costs of the closed-loop supply chain network. It is important to note that the design of the logistics network may involve a trade-off between the total costs and the optimality in commercial goods management. The model comprises a discrete set as potential locations of unlimited capacity warehouses and fixed locations of customers’ zones. It provides decisions related to the facility location and customers’ requirements satisfaction, all of this related with the inventory and shipment decisions of the supply chain. Finally, an application of this model is illustrated by a real-life case in the food and drinks industry. We can conclude that this model can significantly help companies to make decisions about problems associated with logistics network design.

Modeling Integrated Water-User Decisions with Intermittent Supplies

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Lund, J. R.; Rosenberg, D.

2006-12-01

We present an economic-engineering method to estimate urban water use demands with intermittent water supplies. A two-stage, probabilistic optimization formulation includes a wide variety of water supply enhancement and conservation actions that individual households can adopt to meet multiple water quality uses with uncertain water availability. We embed the optimization in Monte-Carlo simulations to show aggregate effects at a utility (citywide) scale for a population of user conditions and decisions. Parametric analysis provides derivations of supply curves to subsidize conservation, demand responses to alternative pricing, and customer willingness-to-pay to avoid shortages. Results show a good empirical fit for the average and distribution of billed residential water use in Amman, Jordan. Additional outputs give likely market penetration rates for household conservation actions, associated water savings, and subsidies required to entice further adoption. We discuss new insights to size, target, market, and finance conservation programs and interpret a demand curve with block pricing.

Integrated modeling approach for optimal management of water, energy and food security nexus

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Zhang, Xiaodong; Vesselinov, Velimir V.

2017-03-01

Water, energy and food (WEF) are inextricably interrelated. Effective planning and management of limited WEF resources to meet current and future socioeconomic demands for sustainable development is challenging. WEF production/delivery may also produce environmental impacts; as a result, green-house-gas emission control will impact WEF nexus management as well. Nexus management for WEF security necessitates integrated tools for predictive analysis that are capable of identifying the tradeoffs among various sectors, generating cost-effective planning and management strategies and policies. To address these needs, we have developed an integrated model analysis framework and tool called WEFO. WEFO provides a multi-period socioeconomic model for predicting how to satisfy WEF demands based on model inputs representing productions costs, socioeconomic demands, and environmental controls. WEFO is applied to quantitatively analyze the interrelationships and trade-offs among system components including energy supply, electricity generation, water supply-demand, food production as well as mitigation of environmental impacts. WEFO is demonstrated to solve a hypothetical nexus management problem consistent with real-world management scenarios. Model parameters are analyzed using global sensitivity analysis and their effects on total system cost are quantified. The obtained results demonstrate how these types of analyses can be helpful for decision-makers and stakeholders to make cost-effective decisions for optimal WEF management.

Cellular Decision Making by Non-Integrative Processing of TLR Inputs

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Ryan A. Kellogg

2017-04-01

Full Text Available Cells receive a multitude of signals from the environment, but how they process simultaneous signaling inputs is not well understood. Response to infection, for example, involves parallel activation of multiple Toll-like receptors (TLRs that converge on the nuclear factor κB (NF-κB pathway. Although we increasingly understand inflammatory responses for isolated signals, it is not clear how cells process multiple signals that co-occur in physiological settings. We therefore examined a bacterial infection scenario involving co-stimulation of TLR4 and TLR2. Independent stimulation of these receptors induced distinct NF-κB dynamic profiles, although surprisingly, under co-stimulation, single cells continued to show ligand-specific dynamic responses characteristic of TLR2 or TLR4 signaling rather than a mixed response, comprising a cellular decision that we term “non-integrative” processing. Iterating modeling and microfluidic experiments revealed that non-integrative processing occurred through interaction of switch-like NF-κB activation, receptor-specific processing timescales, cell-to-cell variability, and TLR cross-tolerance mediated by multilayer negative feedback.

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

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Berkman, Elliot T

2018-01-01

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

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

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Scherbaum, Stefan; Dshemuchadse, Maja; Goschke, Thomas

2012-01-01

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

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

Directory of Open Access Journals (Sweden)

Stefan eScherbaum

2012-11-01

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

Including model uncertainty in risk-informed decision making

International Nuclear Information System (INIS)

Reinert, Joshua M.; Apostolakis, George E.

2006-01-01

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

A Signal Detection Model of Compound Decision Tasks

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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

Usefulness of alternative integrative assessment methodologies in public decision making

Energy Technology Data Exchange (ETDEWEB)

Erickson, L. E.; Litchfield, J. W.; Currie, J. W.; McDonald, C. L.; Adams, R. C.

1978-07-01

Many diverse social, economic, and environmental effects are associated with each of the available energy development alternatives. The assessment of the costs, risks, and benefits of these energy development options is an important function of the U. S. Department of Energy. This task is more difficult when no single alternative is better than the others in all respects. This paper compares benefit-cost and multi-attribute utility analysis as decision aids for these more difficult and more common assessment cases. PNL has developed expertise in making these assessments through its involvement since the Calvert Cliffs decision in both the preparation of Environmental Impact Statements and the development of methods to make these statements more thorough and responsive to the spirit of the National Environmental Protection Act (NEPA). Since 1973 PNL has had continuing efforts to quantify, value, and compare all of the major factors which influence the overall impacts of energy development options. An important part of this work has been the measurement and incorporation of the relative values which community groups place on these conflicting factors. Such difficult assessment problems could be approached in many ways including the use of benefit-cost or multi-attribute utility analysis. This paper addresses the following questions: (1) Should an integrative assessment methodology be used for the overall assessment of these costs, risks, and benefits. (2) If an integrative assessment methodology is to be used, what alternative methods are available and what should be the basis for selecting a method. (3) Is it possible to use one of the available alternatives for one portion of the assessment and another for another portion of the assessment. The answers to these questions presented in this report are applicable to most public decision problems.

Simple model for multiple-choice collective decision making.

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Lee, Ching Hua; Lucas, Andrew

2014-11-01

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

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