Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications

by Oscar Castillo (Editor), Patricia Melin (Editor), Janusz Kacprzyk (Editor)

Overview

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.

Product Details

ISBN-13:	9783030354442
Publisher:	Springer International Publishing
Publication date:	02/28/2020
Series:	Studies in Computational Intelligence , #862
Edition description:	1st ed. 2020
Pages:	792
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

Part I: Type-1 and Type-2 Fuzzy Logic.- Parameter adaptation in the imperialist competitive algorithm using generalized type-2 fuzzy logic.- A Mamdani fuzzy inference prool aimed to identify heterogeneity of the allometric response in arithmetical space.- Fireworks Algorithm (FWA) with adaptation of parameters using Interval Type-2 Fuzzy Logic System.- Omnidirectional Four Wheel Mobile Robot Control with a Type-2 Fuzzy Logic Behavior-based Strategy.