Fuzzy Decision Making in Modeling and Control
Fuzzy Decision Making in Modeling and Control

Author: Joao M. C. Sousa

Publisher: World Scientific

Published: 2002

Total Pages: 356

ISBN-13: 9812777911

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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."

Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making
Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making

Author: Cengiz Kahraman

Publisher: Springer

Published: 2019-07-05

Total Pages: 1386

ISBN-13: 3030237567

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This book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Conference, held in Istanbul, Turkey, on July 23–25, 2019. Big data analytics refers to the strategy of analyzing large volumes of data, or big data, gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. Big data analytics allows data scientists and various other users to evaluate large volumes of transaction data and other data sources that traditional business systems would be unable to tackle. Data-driven and knowledge-driven approaches and techniques have been widely used in intelligent decision-making, and they are increasingly attracting attention due to their importance and effectiveness in addressing uncertainty and incompleteness. INFUS 2019 focused on intelligent and fuzzy systems with applications in big data analytics and decision-making, providing an international forum that brought together those actively involved in areas of interest to data science and knowledge engineering. These proceeding feature about 150 peer-reviewed papers from countries such as China, Iran, Turkey, Malaysia, India, USA, Spain, France, Poland, Mexico, Bulgaria, Algeria, Pakistan, Australia, Lebanon, and Czech Republic.

Fuzzy Techniques for Decision Making
Fuzzy Techniques for Decision Making

Author: José Carlos R. Alcantud

Publisher: MDPI

Published: 2018-05-18

Total Pages: 411

ISBN-13: 3038428876

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This book is a printed edition of the Special Issue "Fuzzy Techniques for Decision Making" that was published in Symmetry

Applied Mathematics and Computational Intelligence
Applied Mathematics and Computational Intelligence

Author: Oscar Castillo

Publisher: Springer Nature

Published: 2023-05-23

Total Pages: 254

ISBN-13: 9811981949

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This book contains select papers presented at the International Conference on Applied Mathematics and Computational Intelligence (ICAMCI-2020), held at the National Institute of Technology Agartala, Tripura, India, from 19–20 March 2020. It discusses the most recent breakthroughs in intelligent techniques such as fuzzy logic, neural networks, optimization algorithms, and their application in the development of intelligent information systems by using applied mathematics. The book also explains how these systems will be used in domains such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction, and complicated problems in optimization. The book publishes new developments and advances in various areas of type-3 fuzzy, intuitionistic fuzzy, computational mathematics, block chain, creak analysis, supply chain, soft computing, fuzzy systems, hybrid intelligent systems, thermos-elasticity, etc. The book is targeted to researchers, scientists, professors, and students of mathematics, computer science, applied science and engineering, interested in the theory and applications of intelligent systems in real-world applications. It provides young researchers and students with new directions for their future study by exchanging fresh thoughts and finding new problems.

Fuzzy Cognitive Maps for Applied Sciences and Engineering
Fuzzy Cognitive Maps for Applied Sciences and Engineering

Author: Elpiniki I. Papageorgiou

Publisher: Springer Science & Business Media

Published: 2013-12-02

Total Pages: 411

ISBN-13: 3642397395

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Fuzzy Cognitive Maps (FCM) constitute cognitive models in the form of fuzzy directed graphs consisting of two basic elements: the nodes, which basically correspond to “concepts” bearing different states of activation depending on the knowledge they represent, and the “edges” denoting the causal effects that each source node exercises on the receiving concept expressed through weights. Weights take values in the interval [-1,1], which denotes the positive, negative or neutral causal relationship between two concepts. An FCM can be typically obtained through linguistic terms, inherent to fuzzy systems, but with a structure similar to the neural networks, which facilitates data processing, and has capabilities for training and adaptation. During the last 10 years, an exponential growth of published papers in FCMs was followed showing great impact potential. Different FCM structures and learning schemes have been developed, while numerous studies report their use in many contexts with highly successful modeling results. The aim of this book is to fill the existing gap in the literature concerning fundamentals, models, extensions and learning algorithms for FCMs in knowledge engineering. It comprehensively covers the state-of-the-art FCM modeling and learning methods, with algorithms, codes and software tools, and provides a set of applications that demonstrate their various usages in applied sciences and engineering.

Applications of Fuzzy Optimization and Fuzzy Decision Making
Applications of Fuzzy Optimization and Fuzzy Decision Making

Author: Vassilis C Gerogiannis

Publisher:

Published: 2021-10-26

Total Pages: 416

ISBN-13: 9783036522654

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The aim of the Special Issue "Applications of Fuzzy Optimization and Fuzzy Decision Making" is to expand the applicability of fuzzy optimization and decision making for solving various types of problems in the areas of economics, business, engineering, management, operations research, etc. Any experimental research or empirical study of theoretical developments in fuzzy optimization and decision making is highly welcome. Additionally, research papers presenting solution methods and/or studying their computational complexity, and proposing new algorithms to solve fuzzy optimization and decision making problems, in an effective and efficient manner, are also welcome. We are looking forward to receive innovative approaches that apply, in practical settings, state-of-the art mathematical/algorithmic techniques from fuzzy technology, computational intelligence and soft-computing methodologies, with the aim to offer robust solutions for complex optimization and decision making problems characterized by non-probabilistic uncertainty, vagueness, ambiguity, and hesitation. Such type of papers will address the suitability, validity, and advantages of using fuzzy technologies and the enhancement of them using intelligent methods to treat real-life problems from various disciplines.

Fuzzy Sets, Decision Making, and Expert Systems
Fuzzy Sets, Decision Making, and Expert Systems

Author: Hans-Jürgen Zimmermann

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 342

ISBN-13: 9400932499

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In the two decades since its inception by L. Zadeh, the theory of fuzzy sets has matured into a wide-ranging collection of concepts, models, and tech niques for dealing with complex phenomena which do not lend themselves to analysis by classical methods based on probability theory and bivalent logic. Nevertheless, a question which is frequently raised by the skeptics is: Are there, in fact, any significant problem areas in which the use of the theory of fuzzy sets leads to results which could not be obtained by classical methods? The approximately 5000 publications in this area, which are scattered over many areas such as artificial intelligence, computer science, control engineering, decision making, logic, operations research, pattern recognition, robotics and others, provide an affirmative answer to this question. In spite of the large number of publications, good and comprehensive textbooks which could facilitate the access of newcomers to this area and support teaching were missing until recently. To help to close this gap and to provide a textbook for courses in fuzzy set theory which can also be used as an introduction to this field, the first volume ofthis book was published in 1985 [Zimmermann 1985 b]. This volume tried to cover fuzzy set theory and its applications as extensively as possible. Applications could, therefore, only be described to a limited extent and not very detailed.

Predicting Human Decision-Making
Predicting Human Decision-Making

Author: Ariel Rosenfeld

Publisher: Morgan & Claypool Publishers

Published: 2018-01-22

Total Pages: 152

ISBN-13: 1681732750

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Human decision-making often transcends our formal models of "rationality." Designing intelligent agents that interact proficiently with people necessitates the modeling of human behavior and the prediction of their decisions. In this book, we explore the task of automatically predicting human decision-making and its use in designing intelligent human-aware automated computer systems of varying natures—from purely conflicting interaction settings (e.g., security and games) to fully cooperative interaction settings (e.g., autonomous driving and personal robotic assistants). We explore the techniques, algorithms, and empirical methodologies for meeting the challenges that arise from the above tasks and illustrate major benefits from the use of these computational solutions in real-world application domains such as security, negotiations, argumentative interactions, voting systems, autonomous driving, and games. The book presents both the traditional and classical methods as well as the most recent and cutting edge advances, providing the reader with a panorama of the challenges and solutions in predicting human decision-making.

Linguistic Methods Under Fuzzy Information in System Safety and Reliability Analysis
Linguistic Methods Under Fuzzy Information in System Safety and Reliability Analysis

Author: Mohammad Yazdi

Publisher: Springer Nature

Published: 2022-03-10

Total Pages: 210

ISBN-13: 3030933520

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This book reviews and presents a number of approaches to Fuzzy-based system safety and reliability assessment. For each proposed approach, it provides case studies demonstrating their applicability, which will enable readers to implement them into their own risk analysis process. The book begins by giving a review of using linguistic terms in system safety and reliability analysis methods and their extension by fuzzy sets. It then progresses in a logical fashion, dedicating a chapter to each approach, including the 2-tuple fuzzy-based linguistic term set approach, fuzzy bow-tie analysis, optimizing the allocation of risk control measures using fuzzy MCDM approach, fuzzy sets theory and human reliability, and emergency decision making fuzzy-expert aided disaster management system. This book will be of interest to professionals and researchers working in the field of system safety and reliability, as well as postgraduate and undergraduate students studying applications of fuzzy systems.