Nature-Inspired Design of Hybrid Intelligent Systems

Overview

This book highlights recent advances in the design of hybrid intelligent systems based on nature-inspired optimization and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction, and optimization of complex problems.

Part 1

The book is divided into seven main parts, the first of which addresses theoretical aspects of and new concepts and algorithms based on type-2 and intuitionistic fuzzy logic systems.

Part 2

The second part focuses on neural network theory, and explores the applications of neural networks in diverse areas, such as time series prediction and pattern recognition.

Part 3

The book’s third part presents enhancements to meta-heuristics based on fuzzy logic techniques and describes new nature-inspired optimization algorithms that employ fuzzy dynamic adaptation of parameters.

Part 4

While the fourth part presents diverse applications of nature-inspired optimization algorithms.

Part 5

In turn, the fifth part investigates applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition.

Part 6

The sixth part examines new optimization algorithms and their applications.

Part 7

Lastly, the seventh part is dedicated to the design and application of different hybrid intelligent systems.