Search results for: policy-decision-modeling-with-fuzzy-logic

Policy Decision Modeling with Fuzzy Logic

Author : Ali Guidara
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This book introduces the concept of policy decision emergence and its dynamics at the sub systemic level of the decision process. This level constitutes the breeding ground of the emergence of policy decisions but remains unexplored due to the absence of adequate tools. It is a nonlinear complex system made of several entities that interact dynamically. The behavior of such a system cannot be understood with linear and deterministic methods. The book presents an innovative multidisciplinary approach that results in the development of a Policy Decision Emergence Simulation Model (PODESIM). This computational model is a multi-level fuzzy inference system that allows the identification of the decision emergence levers. This development represents a major advancement in the field of public policy decision studies. It paves the way for decision emergence modeling and simulation by bridging complex systems theory, multiple streams theory, and fuzzy logic theory.

International Norms and Decision Making

Author : Gary Goertz
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This book presents a punctuated equilibrium framework for understanding the nature of policy decision-making by governments as well as a theory of the creation, functioning, and evolution of international norms and institutions.

Dynamical Aspects in Fuzzy Decision Making

Author : Yuji Yoshida
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The concept of fuzziness, inspired by Zadeh (1965), brings us fruitful results when it is applied to problems in decision making. Recently, problems in fuzzy decision making are getting more complex, and one of the most complex fac tors is dynamics in systems. Dynamical approach to fuzzy decision making has been proposed by Bellman and Zadeh's celebrated paper "Decision-making in a fuzzy environment" (1970). The idea has developed into fuzzy mathemati cal programming and has been applied in many fields including management science, operations research, control theory, engineering, systems analysis, computer science, mathematical finance etc. Dynamic programming, advo cated in Bellmans book "Dynamic programming" (1957), is one of the most powerful tools to deal with dynamics in systems, and Bellman and Zadeh has proposed the optimality principle in fuzzy decision making by (1970) introducing fuzzy dynamic programming. Fuzzy dynamic programming and fuzzy mathematical programming has been making remakable progress after they were given life by Bellman and Zadeh's paper (1970). In this volume, various kinds of dynamics, not only time but also structure of systems, are considered. This volume contains ten reviewed papers, which deal with dynamics in theory and applications and whose topics are poten tially related to dynamics and are expected to develope dynamical study in near future. first, fuzzy dynamic programming is reviewed from a viewpoint of its origin and consider its developement in theory and applications.

Fuzzy Logic and Information Fusion

Author : Tomasa Calvo Sánchez
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This book offers a timely report on key theories and applications of soft-computing. Written in honour of Professor Gaspar Mayor on his 70th birthday, it primarily focuses on areas related to his research, including fuzzy binary operators, aggregation functions, multi-distances, and fuzzy consensus/decision models. It also discusses a number of interesting applications such as the implementation of fuzzy mathematical morphology based on Mayor-Torrens t-norms. Importantly, the different chapters, authored by leading experts, present novel results and offer new perspectives on different aspects of Mayor’s research. The book also includes an overview of evolutionary fuzzy systems, a topic that is not one of Mayor’s main areas of interest, and a final chapter written by the Spanish pioneer in fuzzy logic, Professor E. Trillas. Computer and decision scientists, knowledge engineers and mathematicians alike will find here an authoritative overview of key soft-computing concepts and techniques.

Fuzzy Logic and Soft Computing

Author : Guoqing Chen
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Fuzzy Logic and Soft Computing contains contributions from world-leading experts from both the academic and industrial communities. The first part of the volume consists of invited papers by international authors describing possibilistic logic in decision analysis, fuzzy dynamic programming in optimization, linguistic modifiers for word computation, and theoretical treatments and applications of fuzzy reasoning. The second part is composed of eleven contributions from Chinese authors focusing on some of the key issues in the fields: stable adaptive fuzzy control systems, partial evaluations and fuzzy reasoning, fuzzy wavelet neural networks, analysis and applications of genetic algorithms, partial repeatability, rough set reduction for data enriching, limits of agents in process calculus, medium logic and its evolution, and factor spaces canes. These contributions are not only theoretically sound and well-formulated, but are also coupled with applicability implications and/or implementation treatments. The domains of applications realized or implied are: decision analysis, word computation, databases and knowledge discovery, power systems, control systems, and multi-destinational routing. Furthermore, the articles contain materials that are an outgrowth of recently conducted research, addressing fundamental and important issues of fuzzy logic and soft computing.

Intelligent Decision and Policy Making Support Systems

Author : Da Ruan
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This edited book reports recent research results and provides a state-of-the-art on intelligent decision support systems applications, lessons learned and future research directions. The book covers a balanced mixture of theory and practice, including new methods and developments of intelligent decision support systems applications in Society and Policy Support. Its main objective is to gather a peer-reviewed collection of high quality contributions in the relevant topic areas.

Fuzzy Multiple Objective Decision Making

Author : Young-Jou Lai
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In the last 25 years, the fuzzy set theory has been applied in many disciplines such as operations research, management science, control theory, artificial intelligence/expert system, etc. In this volume, methods and applications of crisp, fuzzy and possibilistic multiple objective decision making are first systematically and thoroughly reviewed and classified. This state-of-the-art survey provides readers with a capsule look into the existing methods, and their characteristics and applicability to analysis of fuzzy and possibilistic programming problems. To realize practical fuzzy modelling, it presents solutions for real-world problems including production/manufacturing, location, logistics, environment management, banking/finance, personnel, marketing, accounting, agriculture economics and data analysis. This book is a guided tour through the literature in the rapidly growing fields of operations research and decision making and includes the most up-to-date bibliographical listing of literature on the topic.

Advancements in Fuzzy Reliability Theory

Author : Kumar, Akshay
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In recent years, substantial efforts are being made in the development of reliability theory including fuzzy reliability theories and their applications to various real-life problems. Fuzzy set theory is widely used in decision making and multi criteria such as management and engineering, as well as other important domains in order to evaluate the uncertainty of real-life systems. Fuzzy reliability has proven to have effective tools and techniques based on real set theory for proposed models within various engineering fields, and current research focuses on these applications. Advancements in Fuzzy Reliability Theory introduces the concept of reliability fuzzy set theory including various methods, techniques, and algorithms. The chapters present the latest findings and research in fuzzy reliability theory applications in engineering areas. While examining the implementation of fuzzy reliability theory among various industries such as mining, construction, automobile, engineering, and more, this book is ideal for engineers, practitioners, researchers, academicians, and students interested in fuzzy reliability theory applications in engineering areas.

Decision Modeling in Policy Management

Author : Giampiero Beroggi
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The last decade has experienced major societal challenges at the intersection of technological systems and policy making. Prevalent examples are the liberalization of energy and telecommunications markets, the public aversion towards nuclear power plants, the development of high-speed trains, the debates about global warming and sustainability, the development of intelligent vehicle systems, and the controversies concerning the location of waste depositories, airports, and energy systems. These challenges, coupled with the call from industry for a systems-engineering oriented approach to policy analysis, motivated Delft University of Technology to launch the first European School of Systems Engineering, Policy Analysis. and Management (SEPA). The purpose was to educate engineering oriented policy analysts in bridging the gap between engineering systems and policy decision making processes, both for the public and private sector. Up to now, more than 500 first-year students and 30 Ph.D. students have enrolled in the program. In 1993, I set up a class called Quantitative Methods for Problem Solving which had to address the most relevant issues in decision making for policy management, such as linear and non-linear optimization, multiattribute utility theory, multicriteria decision making, concepts from game theory, outranking relations, and probabilistic influence diagrams.

Applying Fuzzy Mathematics to Formal Models in Comparative Politics

Author : Terry D. Clark
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This book explores the intersection of fuzzy mathematics and the spatial modeling of preferences in political science. Beginning with a critique of conventional modeling approaches predicated on Cantor set theoretical assumptions, the authors outline the potential benefits of a fuzzy approach to the study of ambiguous or uncertain preference profiles. This is a good text for a graduate seminar in formal modeling. It is also suitable as an introductory text in fuzzy mathematics.