Computational intelligence: a methodological introduction

✍ Scribed by Rudolf Kruse, Christian Borgelt, Christian Braune, Sanaz Mostaghim;Matthias Steinbrecher

Publisher: Springer London
Year: 2016
Tongue: English
Edition: 2nd edition
Category: Library

No coin nor oath required. For personal study only.

✦ Table of Contents

Introduction.- Part I: Neural Networks.- Introduction.- Threshold Logic Units.- General Neural Networks.- Multi-Layer Perceptrons.- Radial Basis Function Networks.- Self-Organizing Maps.- Hopfield Networks.- Recurrent Networks.- Mathematical Remarks for Neural Networks.- Part II: Evolutionary Algorithms.- Introduction to Evolutionary Algorithms.- Elements of Evolutionary Algorithms.- Fundamental Evolutionary Algorithms.- Computational Swarm Intelligence.- Part III: Fuzzy Systems.- Fuzzy Sets and Fuzzy Logic.- The Extension Principle.- Fuzzy Relations.- Similarity Relations.- Fuzzy Control.- Fuzzy Data Analysis.- Part IV: Bayes and Markov Networks.- Introduction to Bayes Networks.- Elements of Probability and Graph Theory.- Decompositions.- Evidence Propagation.- Learning Graphical Models.- Belief Revision.- Decision Graphs.

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