Editors:
- Describes recent advances in fuzzy logic, neural networks, and optimization algorithms, as well as their hybrid combinations
- Presents applications in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction, and optimization of complex problems
- Written by experts in the field
Part of the book series: Studies in Computational Intelligence (SCI, volume 862)
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Table of contents (53 chapters)
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Front Matter
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Type-1 and Type-2 Fuzzy Logic
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Front Matter
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Intuitionistic Fuzzy Logic
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Front Matter
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Metaheuristics: Theory and Applications
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Front Matter
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About this book
Editors and Affiliations
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Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Mexico
Oscar Castillo, Patricia Melin
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Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland
Janusz Kacprzyk
Bibliographic Information
Book Title: Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications
Editors: Oscar Castillo, Patricia Melin, Janusz Kacprzyk
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-030-35445-9
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-35444-2Published: 28 February 2020
Softcover ISBN: 978-3-030-35447-3Published: 28 February 2021
eBook ISBN: 978-3-030-35445-9Published: 27 February 2020
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XIV, 792
Number of Illustrations: 123 b/w illustrations, 240 illustrations in colour