Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications (Hardcover, 1st ed. 2020)

This book describes the latest advances in fuzzy logic, neural networks, and optimization algorithms, as well as their hybrid intelligent combinations, and their applications in the areas such as intelligent control, robotics, pattern recognition, medical diagnosis, time series prediction, and optimization. The topic is highly relevant as most current intelligent systems and devices use some form of intelligent feature to enhance their performance. The book also presents new and advanced models and algorithms of type-2 fuzzy logic and intuitionistic fuzzy systems, which are of great interest to researchers in these areas. Further, it proposes novel, nature-inspired optimization algorithms and innovative neural models. Featuring contributions on theoretical aspects as well as applications, the book appeals to a wide audience.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Studies in Computational Intelligence, 862
Release date:	March 2020
First published:	2020
Editors:	Oscar Castillo • Patricia Melin • Janusz Kacprzyk
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	792
Edition:	1st ed. 2020
ISBN-13:	978-3-03-035444-2
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > Neural networks
LSN:	3-03-035444-X
Barcode:	9783030354442

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