Engineering Evolutionary Intelligent SystemsAjith Abraham, Crina Grosan, Witold Pedrycz Springer Science & Business Media, 2008. gada 3. janv. - 444 lappuses Evolutionary design of intelligent systems is gaining much popularity due to its capabilities in handling several real world problems involving optimization, complexity, noisy and non-stationary environment, imprecision, uncertainty and vagueness. This edited volume 'Engineering Evolutionary Intelligent Systems' deals with the theoretical and methodological aspects, as well as various evolutionary algorithm applications to many real world problems originating from science, technology, business or commerce. This volume comprises of 15 chapters including an introductory chapter which covers the fundamental definitions and outlines some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed. |
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... Learning Rules 3.4 Recent Applications of Evolutionary Neural Networks in Practice .... 2567∞ 4 Evolutionary Fuzzy Systems 10 4.1 Evolutionary Search of Fuzzy Membership Functions 4.2 Evolutionary Search of Fuzzy Rule Base 12 12 9022 ...
... Learning Using Clustering and Combinatorial Optimization ( RSL - CC ) Kiruthika Ramanathan and Sheng Uei Guan . 1 Introduction ... 2 Some preliminaries 2.1 Notation ... 2.2 Problem formulation for recursive learning 157 157 € 160 160 ...
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Engineering Evolutionary Intelligent Systems Ajith Abraham,Crina Grosan,Witold Pedrycz Ierobežota priekšskatīšana - 2008 |
Engineering Evolutionary Intelligent Systems Ajith Abraham,Crina Grosan,Witold Pedrycz Priekšskatījums nav pieejams - 2010 |