Advances in Evolutionary Computing for System Design [electronic resource] / edited by Lakhmi C. Jain, Vasile Palade, Dipti Srinivasan.

By: Jain, Lakhmi C [editor.]Contributor(s): Palade, Vasile [editor.] | Srinivasan, Dipti [editor.] | SpringerLink (Online service)Material type: TextTextLanguage: English Series: Studies in Computational Intelligence: 66Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007Description: VIII, 326 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540723776Subject(s): Engineering | Artificial intelligence | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 519 LOC classification: TA329-348TA640-643Online resources: Click here to access online
Contents:
to Evolutionary Computing in System Design -- Evolutionary Neuro-Fuzzy Systems and Applications -- Evolution of Fuzzy Controllers and Applications -- A Neuro-Genetic Framework for Multi-Classifier Design: An Application to Promoter Recognition in DNA Sequences -- Evolutionary Grooming of Traffic in WDM Optical Networks -- EPSO: Evolutionary Particle Swarms -- Design of Type-Reduction Strategies for Type-2 Fuzzy Logic Systems using Genetic Algorithms -- Designing a Recurrent Neural Network-based Controller for Gyro-Mirror Line-of-Sight Stabilization System using an Artificial Immune Algorithm -- Distributed Problem Solving using Evolutionary Learning in Multi-Agent Systems -- Evolutionary Computing within Grid Environment -- Application of Evolutionary Game Theory to Wireless Mesh Networks -- Applying Hybrid Multiobjective Evolutionary Algorithms to the Sailor Assignment Problem -- Evolutionary Techniques Applied to Hardware Optimization Problems: Test and Verification of Advanced Processors.
In: Springer eBooksSummary: Evolutionary computing paradigms offer robust and powerful adaptive search mechanisms for system design. This book includes thirteen chapters covering a wide area of topics in evolutionary computing and applications including: Introduction to evolutionary computing in system design Evolutionary neuro-fuzzy systems Evolution of fuzzy controllers Genetic algorithms for multi-classifier design Evolutionary grooming of traffic Evolutionary particle swarms Fuzzy logic systems using genetic algorithms Evolutionary algorithms and immune learning for neural network-based controller design Distributed problem solving using evolutionary learning Evolutionary computing within grid environment Evolutionary game theory in wireless mesh networks Hybrid multiobjective evolutionary algorithms for the sailor assignment problem Evolutionary techniques in hardware optimization This book will be useful to researchers in intelligent systems with interest in evolutionary computing, application engineers and system designers. The book can also be used by students and lecturers as an advanced reading material for courses on evolutionary computing.
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to Evolutionary Computing in System Design -- Evolutionary Neuro-Fuzzy Systems and Applications -- Evolution of Fuzzy Controllers and Applications -- A Neuro-Genetic Framework for Multi-Classifier Design: An Application to Promoter Recognition in DNA Sequences -- Evolutionary Grooming of Traffic in WDM Optical Networks -- EPSO: Evolutionary Particle Swarms -- Design of Type-Reduction Strategies for Type-2 Fuzzy Logic Systems using Genetic Algorithms -- Designing a Recurrent Neural Network-based Controller for Gyro-Mirror Line-of-Sight Stabilization System using an Artificial Immune Algorithm -- Distributed Problem Solving using Evolutionary Learning in Multi-Agent Systems -- Evolutionary Computing within Grid Environment -- Application of Evolutionary Game Theory to Wireless Mesh Networks -- Applying Hybrid Multiobjective Evolutionary Algorithms to the Sailor Assignment Problem -- Evolutionary Techniques Applied to Hardware Optimization Problems: Test and Verification of Advanced Processors.

Evolutionary computing paradigms offer robust and powerful adaptive search mechanisms for system design. This book includes thirteen chapters covering a wide area of topics in evolutionary computing and applications including: Introduction to evolutionary computing in system design Evolutionary neuro-fuzzy systems Evolution of fuzzy controllers Genetic algorithms for multi-classifier design Evolutionary grooming of traffic Evolutionary particle swarms Fuzzy logic systems using genetic algorithms Evolutionary algorithms and immune learning for neural network-based controller design Distributed problem solving using evolutionary learning Evolutionary computing within grid environment Evolutionary game theory in wireless mesh networks Hybrid multiobjective evolutionary algorithms for the sailor assignment problem Evolutionary techniques in hardware optimization This book will be useful to researchers in intelligent systems with interest in evolutionary computing, application engineers and system designers. The book can also be used by students and lecturers as an advanced reading material for courses on evolutionary computing.

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