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Author: Ali Guidara
Publisher: Springer Nature
ISBN: 3030626288
Category : Technology & Engineering
Languages : en
Pages : 140
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Book Description
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.
Author: Ali Guidara
Publisher: Springer Nature
ISBN: 3030626288
Category : Technology & Engineering
Languages : en
Pages : 140
Get Book Here
Book Description
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.
Author: Joao M. C. Sousa
Publisher: World Scientific
ISBN: 9812777911
Category : Computers
Languages : en
Pages : 356
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Book Description
Decision making and control are two fields with distinct methods for solving problems, and yet they are closely related. This book bridges the gap between decision making and control in the field of fuzzy decisions and fuzzy control, and discusses various ways in which fuzzy decision making methods can be applied to systems modeling and control.Fuzzy decision making is a powerful paradigm for dealing with human expert knowledge when one is designing fuzzy model-based controllers. The combination of fuzzy decision making and fuzzy control in this book can lead to novel control schemes that improve the existing controllers in various ways. The following applications of fuzzy decision making methods for designing control systems are considered: OCo Fuzzy decision making for enhancing fuzzy modeling. The values of important parameters in fuzzy modeling algorithms are selected by using fuzzy decision making.OCo Fuzzy decision making for designing signal-based fuzzy controllers. The controller mappings and the defuzzification steps can be obtained by decision making methods.OCo Fuzzy design and performance specifications in model-based control. Fuzzy constraints and fuzzy goals are used.OCo Design of model-based controllers combined with fuzzy decision modules. Human operator experience is incorporated for the performance specification in model-based control.The advantages of bringing together fuzzy control and fuzzy decision making are shown with multiple examples from real and simulated control systems."
Author: Rafik Aziz Aliev
Publisher: Springer
ISBN: 3642348955
Category : Technology & Engineering
Languages : en
Pages : 332
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Book Description
Every day decision making and decision making in complex human-centric systems are characterized by imperfect decision-relevant information. Main drawback of the existing decision theories is namely incapability to deal with imperfect information and modeling vague preferences. Actually, a paradigm of non-numerical probabilities in decision making has a long history and arose also in Keynes’s analysis of uncertainty. There is a need for further generalization – a move to decision theories with perception-based imperfect information described in NL. The languages of new decision models for human-centric systems should be not languages based on binary logic but human-centric computational schemes able to operate on NL-described information. Development of new theories is now possible due to an increased computational power of information processing systems which allows for computations with imperfect information, particularly, imprecise and partially true information, which are much more complex than computations over numbers and probabilities. The monograph exposes the foundations of a new decision theory with imperfect decision-relevant information on environment and a decision maker’s behavior. This theory is based on the synthesis of the fuzzy sets theory with perception-based information and the probability theory. The book is self containing and represents in a systematic way the decision theory with imperfect information into the educational systems. The book will be helpful for teachers and students of universities and colleges, for managers and specialists from various fields of business and economics, production and social sphere.
Author: Robert Babuška
Publisher: Springer Science & Business Media
ISBN: 9401148686
Category : Mathematics
Languages : en
Pages : 269
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Book Description
Rule-based fuzzy modeling has been recognised as a powerful technique for the modeling of partly-known nonlinear systems. Fuzzy models can effectively integrate information from different sources, such as physical laws, empirical models, measurements and heuristics. Application areas of fuzzy models include prediction, decision support, system analysis, control design, etc. Fuzzy Modeling for Control addresses fuzzy modeling from the systems and control engineering points of view. It focuses on the selection of appropriate model structures, on the acquisition of dynamic fuzzy models from process measurements (fuzzy identification), and on the design of nonlinear controllers based on fuzzy models. To automatically generate fuzzy models from measurements, a comprehensive methodology is developed which employs fuzzy clustering techniques to partition the available data into subsets characterized by locally linear behaviour. The relationships between the presented identification method and linear regression are exploited, allowing for the combination of fuzzy logic techniques with standard system identification tools. Attention is paid to the trade-off between the accuracy and transparency of the obtained fuzzy models. Control design based on a fuzzy model of a nonlinear dynamic process is addressed, using the concepts of model-based predictive control and internal model control with an inverted fuzzy model. To this end, methods to exactly invert specific types of fuzzy models are presented. In the context of predictive control, branch-and-bound optimization is applied. The main features of the presented techniques are illustrated by means of simple examples. In addition, three real-world applications are described. Finally, software tools for building fuzzy models from measurements are available from the author.
Author: Cengiz Kahraman
Publisher: Springer Science & Business Media
ISBN: 0387768130
Category : Computers
Languages : en
Pages : 591
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Book Description
This work examines all the fuzzy multicriteria methods recently developed, such as fuzzy AHP, fuzzy TOPSIS, interactive fuzzy multiobjective stochastic linear programming, fuzzy multiobjective dynamic programming, grey fuzzy multiobjective optimization, fuzzy multiobjective geometric programming, and more. Each of the 22 chapters includes practical applications along with new developments/results. This book may be used as a textbook in graduate operations research, industrial engineering, and economics courses. It will also be an excellent resource, providing new suggestions and directions for further research, for computer programmers, mathematicians, and scientists in a variety of disciplines where multicriteria decision making is needed.
Author: Klir
Publisher:
ISBN: 9788120306950
Category :
Languages : en
Pages : 368
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Book Description
Author: Aliev Rafig Aziz
Publisher: World Scientific
ISBN: 9814611050
Category : Mathematics
Languages : en
Pages : 468
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Book Description
Every day decision making in complex human-centric systems are characterized by imperfect decision-relevant information. The principal problems with the existing decision theories are that they do not have capability to deal with situations in which probabilities and events are imprecise. In this book, we describe a new theory of decision making with imperfect information. The aim is to shift the foundation of decision analysis and economic behavior from the realm bivalent logic to the realm fuzzy logic and Z-restriction, from external modeling of behavioral decisions to the framework of combined states.This book will be helpful for professionals, academics, managers and graduate students in fuzzy logic, decision sciences, artificial intelligence, mathematical economics, and computational economics.
Author: Andrzej Piegat
Publisher: Physica
ISBN: 3790818240
Category : Computers
Languages : en
Pages : 737
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Book Description
In the last ten years, a true explosion of investigations into fuzzy modeling and its applications in control, diagnostics, decision making, optimization, pattern recognition, robotics, etc. has been observed. The attraction of fuzzy modeling results from its intelligibility and the high effectiveness of the models obtained. Owing to this the modeling can be applied for the solution of problems which could not be solved till now with any known conventional methods. The book provides the reader with an advanced introduction to the problems of fuzzy modeling and to one of its most important applications: fuzzy control. It is based on the latest and most significant knowledge of the subject and can be used not only by control specialists but also by specialists working in any field requiring plant modeling, process modeling, and systems modeling, e.g. economics, business, medicine, agriculture,and meteorology.
Author: Christer Carlsson
Publisher: Springer Science & Business Media
ISBN: 1441989773
Category : Mathematics
Languages : en
Pages : 289
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Book Description
This book shows how the application of fuzzy logic can benefit management, group decision making, strategic planning, supply chain management and other business imperatives. The theoretical analysis is fully supported by real-life case studies. The book develops themes that businesses can use to master effectiveness and quality, work with flexibility, and support continuous learning in the organization and the individual.
Author: H. B. Verbruggen
Publisher: World Scientific
ISBN: 9789810238254
Category : Technology & Engineering
Languages : en
Pages : 344
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Book Description
Fuzzy logic control has become an important methodology in control engineering. This volume deals with applications of fuzzy logic control in various domains. The contributions are divided into three parts. The first part consists of two state-of-the-art tutorials on fuzzy control and fuzzy modeling. Surveys of advanced methodologies are included in the second part. These surveys address fuzzy decision making and control, fault detection, isolation and diagnosis, complexity reduction in fuzzy systems and neuro-fuzzy methods. The third part contains application-oriented contributions from various fields, such as process industry, cement and ceramics, vehicle control and traffic management, electromechanical and production systems, avionics, biotechnology and medical applications. The book is intended for researchers both from the academic world and from industry.
