Uncertain Rule Based Fuzzy Systems
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Uncertain Rule Based Fuzzy Systems
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Author : Jerry M. Mendel
language : en
Publisher: Springer
Release Date : 2017-05-17
Uncertain Rule Based Fuzzy Systems written by Jerry M. Mendel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-17 with Technology & Engineering categories.
The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that can model uncertainty — i.e., “type-2” fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications from time-series forecasting to knowledge mining to control. In this new edition, a bottom-up approach is presented that begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty. The author covers fuzzy rule-based systems – from type-1 to interval type-2 to general type-2 – in one volume. For hands-on experience, the book provides information on accessing MatLab and Java software to complement the content. The book features a full suite of classroom material.
Explainable Uncertain Rule Based Fuzzy Systems
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Author : Jerry M. Mendel
language : en
Publisher: Springer
Release Date : 2025-02-15
Explainable Uncertain Rule Based Fuzzy Systems written by Jerry M. Mendel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-15 with Computers categories.
The third edition of this textbook presents a further updated approach to fuzzy sets and systems that can model uncertainty -- i.e., "type-2" fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications, from time-series forecasting to knowledge mining to classification to control and to explainable AI (XAI). This latest edition again begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty, leading to type-2 fuzzy sets and systems. New material is included about how to obtain fuzzy set word models that are needed for XAI, similarity of fuzzy sets, a quantitative methodology that lets one explain in a simple way why the different kinds of fuzzy systems have the potential for performance improvements over each other, and new parameterizations of membership functions that have the potential for achieving even greater performance for all kinds of fuzzy systems. For hands-on experience, the book provides information on accessing MATLAB, Java, and Python software to complement the content. The book features a full suite of classroom material.
Uncertain Rule Based Fuzzy Logic Systems
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Author : Jerry M. Mendel
language : en
Publisher: Prentice Hall
Release Date : 2001
Uncertain Rule Based Fuzzy Logic Systems written by Jerry M. Mendel and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.
Jerry Mendel explains the complete development of fuzzy logic systems and explores a new methodology to build better and more intelligent systems. Two case studies are carried throughout the book to illustrate and expand on the theories introduced.
Genetic Fuzzy Systems Evolutionary Tuning And Learning Of Fuzzy Knowledge Bases
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Author : Oscar Cordon
language : en
Publisher: World Scientific
Release Date : 2001-07-13
Genetic Fuzzy Systems Evolutionary Tuning And Learning Of Fuzzy Knowledge Bases written by Oscar Cordon and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-07-13 with Computers categories.
In recent years, a great number of publications have explored the use of genetic algorithms as a tool for designing fuzzy systems. Genetic Fuzzy Systems explores and discusses this symbiosis of evolutionary computation and fuzzy logic. The book summarizes and analyzes the novel field of genetic fuzzy systems, paying special attention to genetic algorithms that adapt and learn the knowledge base of a fuzzy-rule-based system. It introduces the general concepts, foundations and design principles of genetic fuzzy systems and covers the topic of genetic tuning of fuzzy systems. It also introduces the three fundamental approaches to genetic learning processes in fuzzy systems: the Michigan, Pittsburgh and Iterative-learning methods. Finally, it explores hybrid genetic fuzzy systems such as genetic fuzzy clustering or genetic neuro-fuzzy systems and describes a number of applications from different areas.Genetic Fuzzy System represents a comprehensive treatise on the design of the fuzzy-rule-based systems using genetic algorithms, both from a theoretical and a practical perspective. It is a valuable compendium for scientists and engineers concerned with research and applications in the domain of fuzzy systems and genetic algorithms.
Soft Computing For Hybrid Intelligent Systems
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Author : Oscar Castillo
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-08-25
Soft Computing For Hybrid Intelligent Systems written by Oscar Castillo and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-08-25 with Computers categories.
We describe in this book, new methods and applications of hybrid intelligent systems using soft computing techniques. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary al- rithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of intelligent control, which are basically papers that use hybrid systems to solve particular problems of control. The second part contains papers with the main theme of pattern recognition, which are basically papers using soft computing techniques for achieving pattern recognition in different applications. The third part contains papers with the themes of intelligent agents and social systems, which are papers that apply the ideas of agents and social behavior to solve real-world problems. The fourth part contains papers that deal with the hardware implementation of intelligent systems for solving particular problems. The fifth part contains papers that deal with modeling, simulation and optimization for real-world applications.
Fuzzy Rule Based Modeling With Applications To Geophysical Biological And Engineering Systems
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Author : Andras - Bardossy
language : es
Publisher: CRC Press
Release Date : 1995-04-28
Fuzzy Rule Based Modeling With Applications To Geophysical Biological And Engineering Systems written by Andras - Bardossy and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-04-28 with Technology & Engineering categories.
This book presents in a systematic and comprehensive manner the modeling of uncertainty, vagueness, or imprecision, alias "fuzziness," in just about any field of science and engineering. It delivers a usable methodology for modeling in the absence of real-time feedback. The book includes a short introduction to fuzzy logic containing basic definitions of fuzzy set theory and fuzzy rule systems. It describes methods for the assessment of rule systems, systems with discrete response sets, for modeling time series, for exact physical systems, examines verification and redundancy issues, and investigates rule response functions. Definitions and propositions, some of which have not been published elsewhere, are provided; numerous examples as well as references to more elaborate case studies are also given. Fuzzy rule-based modeling has the potential to revolutionize fields such as hydrology because it can handle uncertainty in modeling problems too complex to be approached by a stochastic analysis. There is also excellent potential for handling large-scale systems such as regionalization or highly non-linear problems such as unsaturated groundwater pollution.
Integrated Uncertainty In Knowledge Modelling And Decision Making
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Author : Yongchuan Tang
language : en
Publisher: Springer
Release Date : 2011-10-13
Integrated Uncertainty In Knowledge Modelling And Decision Making written by Yongchuan Tang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-13 with Computers categories.
This book constitutes the refereed proceedings of the International Symposium on Integrated Uncertainty in Knowledge Modeling and Decision Making, IUKM 2011, held in Hangzhou, China, in October 2011. The 21 revised full papers presented together with 1 keynote lecture and 5 invited talks were carefully reviewed and selected from 55 submissions. The papers provide a wealth of new ideas and report both theoretical and applied research on integrated uncertainty modeling and management.
Computational Intelligence Volume I
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Author : Hisao Ishibuchi
language : en
Publisher: EOLSS Publications
Release Date : 2015-12-30
Computational Intelligence Volume I written by Hisao Ishibuchi and has been published by EOLSS Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-30 with categories.
Computational intelligence is a component of Encyclopedia of Technology, Information, and Systems Management Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. Computational intelligence is a rapidly growing research field including a wide variety of problem-solving techniques inspired by nature. Traditionally computational intelligence consists of three major research areas: Neural Networks, Fuzzy Systems, and Evolutionary Computation. Neural networks are mathematical models inspired by brains. Neural networks have massively parallel network structures with many neurons and weighted connections. Whereas each neuron has a simple input-output relation, a neural network with many neurons can realize a highly non-linear complicated mapping. Connection weights between neurons can be adjusted in an automated manner by a learning algorithm to realize a non-linear mapping required in a particular application task. Fuzzy systems are mathematical models proposed to handle inherent fuzziness in natural language. For example, it is very difficult to mathematically define the meaning of “cold” in everyday conversations such as “It is cold today” and “Can I have cold water”. The meaning of “cold” may be different in a different situation. Even in the same situation, a different person may have a different meaning. Fuzzy systems offer a mathematical mechanism to handle inherent fuzziness in natural language. As a result, fuzzy systems have been successfully applied to real-world problems by extracting linguistic knowledge from human experts in the form of fuzzy IF-THEN rules. Evolutionary computation includes various population-based search algorithms inspired by evolution in nature. Those algorithms usually have the following three mechanisms: fitness evaluation to measure the quality of each solution, selection to choose good solutions from the current population, and variation operators to generate offspring from parents. Evolutionary computation has high applicability to a wide range of optimization problems with different characteristics since it does not need any explicit mathematical formulations of objective functions. For example, simulation-based fitness evaluation is often used in evolutionary design. Subjective fitness evaluation by a human user is also often used in evolutionary art and music. These volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers.
Fuzzy Systems Concepts Methodologies Tools And Applications
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2017-02-22
Fuzzy Systems Concepts Methodologies Tools And Applications written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-22 with Mathematics categories.
There are a myriad of mathematical problems that cannot be solved using traditional methods. The development of fuzzy expert systems has provided new opportunities for problem-solving amidst uncertainties. Fuzzy Systems: Concepts, Methodologies, Tools, and Applications is a comprehensive reference source on the latest scholarly research and developments in fuzzy rule-based methods and examines both theoretical foundations and real-world utilization of these logic sets. Featuring a range of extensive coverage across innovative topics, such as fuzzy logic, rule-based systems, and fuzzy analysis, this is an essential publication for scientists, doctors, engineers, physicians, and researchers interested in emerging perspectives and uses of fuzzy systems in various sectors.
Analysis And Design Of Intelligent Systems Using Soft Computing Techniques
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Author : Patricia Melin
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-06-05
Analysis And Design Of Intelligent Systems Using Soft Computing Techniques written by Patricia Melin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-05 with Computers categories.
This book comprises a selection of papers on new methods for analysis and design of hybrid intelligent systems using soft computing techniques from the IFSA 2007 World Congress, held in Cancun, Mexico, June 2007.