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Cover image for Computational intelligence : theory and applications
Title:
Computational intelligence : theory and applications
Author:
Kumar, T. Ananth (Tamilarasan Ananth), editor.
ISBN:
9781394214259

9781394214242

9781394214235
Physical Description:
1 online resource
Contents:
Cover -- Series Page -- Title Page -- Copyright Page -- Contents -- Introduction -- Chapter 1 Computational Intelligence Theory: An Orientation Technique -- 1.1 Computational Intelligence -- 1.2 Application Fields for Computational Intelligence -- 1.2.1 Neural Networks -- 1.2.1.1 Classification -- 1.2.1.2 Clustering or Compression -- 1.2.1.3 Generation of Sequences or Patterns -- 1.2.1.4 Control Systems -- 1.2.1.5 Evolutionary Computation -- 1.2.2 Fuzzy Logic -- 1.2.2.1 Fuzzy Control Systems -- 1.2.2.2 Fuzzy Systems -- 1.2.2.3 Behavioral Motivations for Fuzzy Logic -- 1.3 Computational Intelligence Paradigms -- 1.3.1 Artificial Neural Networks -- 1.3.2 Evolutionary Computation (EC) -- 1.3.3 Optimization Method -- 1.3.3.1 Optimization -- 1.4 Architecture Assortment -- 1.4.1 Swarm Intelligence -- 1.4.2 Artificial Immune Systems -- 1.5 Myths About Computational Intelligence -- 1.6 Supervised Learning in Computational Intelligence -- 1.6.1 Performance Measures
Abstract:
This book provides a comprehensive exploration of computational intelligence techniques and their applications, offering valuable insights into advanced information processing, machine learning concepts, and their impact on agile manufacturing systems. Computational Intelligence presents a new concept for advanced information processing. Computational Intelligence (CI) is the principle, architecture, implementation, and growth of machine learning concepts that are physiologically and semantically inspired. Computational Intelligence methods aim to develop an approach to evaluating and creating flexible processing of human information, such as sensing, understanding, learning, recognizing, and thinking. The Artificial Neural Network simulates the human nervous system's physiological characteristics and has been implemented numerically for non-linear mapping. Fuzzy Logic Systems simulate the human brain's psychological characteristics and have been used for linguistic translation through membership functions and bioinformatics. The Genetic Algorithm simulates computer evolution and has been applied to solve problems with optimization algorithms for improvements in diagnostic and treatment technologies for various diseases. To expand the agility and learning capacity of manufacturing systems, these methods play essential roles. This book will express the computer vision techniques that make manufacturing systems more flexible, efficient, robust, adaptive, and productive by examining many applications and research into computational intelligence techniques concerning the main problems in design, making plans, and manufacturing goods in agile manufacturing systems.
Local Note:
John Wiley and Sons
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E-Book 599480-1001 Q342 .C66 2024
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