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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1.–5. rezultāts no 75.
... Genetic Algorithm . . . . 216 4 Clustering and Linear Regression Analysis Using 4.1 Entropy - based Fuzzy Clustering ( EFC ) 217. the Clustered Data . 217 3.3 Fitness Function .. .300 Contributors Ajith Abraham Quality of VIII Contents.
... Linear Regression 219 5 GA - based Tuning of Takagi and Sugeno Approach of FLC . 220 5.1 Genetic - Fuzzy System 221 6 Results and Discussion ... 223 6.1 Modeling of Abrasive Flow Machining ( AFM ) Process 223 6.2 Modeling of Tungsten ...
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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 |