Computational Intelligence Paradigms: Theory & Applications using MATLAB

S. Sumathi, Surekha Paneerselvam

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商品描述

Offering a wide range of programming examples implemented in MATLAB®, Computational Intelligence Paradigms: Theory and Applications Using MATLAB® presents theoretical concepts and a general framework for computational intelligence (CI) approaches, including artificial neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous intelligent computing methodologies and algorithms used in CI research.

 

The book first focuses on neural networks, including common artificial neural networks; neural networks based on data classification, data association, and data conceptualization; and real-world applications of neural networks. It then discusses fuzzy sets, fuzzy rules, applications of fuzzy systems, and different types of fused neuro-fuzzy systems, before providing MATLAB illustrations of ANFIS, classification and regression trees, fuzzy c-means clustering algorithms, fuzzy ART map, and Takagi–Sugeno inference systems. The authors also describe the history, advantages, and disadvantages of evolutionary computation and include solved MATLAB programs to illustrate the implementation of evolutionary computation in various problems. After exploring the operators and parameters of genetic algorithms, they cover the steps and MATLAB routines of genetic programming. The final chapter introduces swarm intelligence and its applications, particle swarm optimization, and ant colony optimization.

 

Full of worked examples and end-of-chapter questions, this comprehensive book explains how to use MATLAB to implement CI techniques for the solution of biological problems. It will help readers with their work on evolution dynamics, self-organization, natural and artificial morphogenesis, emergent collective behaviors, swarm intelligence, evolutionary strategies, genetic programming, and the evolution of social behaviors.

商品描述(中文翻譯)

《計算智能範式:理論與應用使用MATLAB》提供了在MATLAB中實現的各種編程示例,介紹了計算智能(CI)方法的理論概念和一般框架,包括人工神經網絡、模糊系統、進化計算、遺傳算法和編程、以及群體智能。本書涵蓋了CI研究中使用的多種智能計算方法和算法。

本書首先聚焦於神經網絡,包括常見的人工神經網絡;基於數據分類、數據關聯和數據概念化的神經網絡;以及神經模糊系統的實際應用。然後討論模糊集合、模糊規則、模糊系統的應用以及不同類型的融合神經模糊系統,並提供了MATLAB中ANFIS、分類和回歸樹、模糊c均值聚類算法、模糊ART映射和高木-菅野推理系統的示例。作者還描述了進化計算的歷史、優點和缺點,並提供了解決不同問題中進化計算實現的MATLAB程序。在探索遺傳算法的運算符和參數之後,他們介紹了遺傳編程的步驟和MATLAB例程。最後一章介紹了群體智能及其應用、粒子群優化和螞蟻群優化。

本書充滿了實例和章末問題,詳細解釋了如何使用MATLAB實現CI技術來解決生物問題。它將幫助讀者在進化動力學、自組織、自然和人工形態生成、新興集體行為、群體智能、進化策略、遺傳編程和社會行為演化等方面的工作。