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Table of contents (17 chapters)
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Front Matter
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Modelling with Fuzzy Sets
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Front Matter
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Relational Models
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Front Matter
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Fuzzy Neural Networks
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Front Matter
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Keywords
About this book
The objective of this book is to provide researchers and practitioners involved in the development of models for complex systems with an understanding of fuzzy modelling, and an appreciation of what makes these models unique. The chapters are organized into three major parts covering relational models, fuzzy neural networks and rule-based models. The material on relational models includes theory along with a large number of implemented case studies, including some on speech recognition, prediction, and ecological systems. The part on fuzzy neural networks covers some fundamentals, such as neurocomputing, fuzzy neurocomputing, etc., identifies the nature of the relationship that exists between fuzzy systems and neural networks, and includes extensive coverage of their architectures. The last part addresses the main design principles governing the development of rule-based models.
Fuzzy Modelling: Paradigms and Practice provides a wealth of specific fuzzy modelling paradigms, algorithms and tools used in systems modelling. Also included is a panoply of case studies from various computer, engineering and science disciplines. This should be a primary reference work for researchers and practitioners developing models of complex systems.
Editors and Affiliations
Bibliographic Information
Book Title: Fuzzy Modelling
Book Subtitle: Paradigms and Practice
Editors: Witold Pedrycz
Series Title: International Series in Intelligent Technologies
DOI: https://doi.org/10.1007/978-1-4613-1365-6
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Kluwer Academic Publishers 1996
Hardcover ISBN: 978-0-7923-9703-8Published: 31 March 1996
Softcover ISBN: 978-1-4612-8589-2Published: 26 September 2011
eBook ISBN: 978-1-4613-1365-6Published: 06 December 2012
Series ISSN: 1382-3434
Edition Number: 1
Number of Pages: XX, 394
Topics: Mathematical Logic and Foundations, Systems Theory, Control, Electrical Engineering