Download Advances in Evolutionary Computing for System Design by Prof. Lakhmi C. Jain, Shing Chiang Tan (auth.), Prof. Lakhmi PDF

By Prof. Lakhmi C. Jain, Shing Chiang Tan (auth.), Prof. Lakhmi C. Jain, Dr. Vasile Palade, Dipti Srinivasan (eds.)

Evolutionary computing paradigms provide powerful and robust adaptive seek mechanisms for approach layout. This ebook contains 13 chapters overlaying a large sector of subject matters in evolutionary computing and purposes including:

    • Introduction to evolutionary computing in procedure design
    • Evolutionary neuro-fuzzy systems
    • Evolution of fuzzy controllers
    • Genetic algorithms for multi-classifier design
    • Evolutionary grooming of traffic
    • Evolutionary particle swarms
    • Fuzzy good judgment platforms utilizing genetic algorithms
    • Evolutionary algorithms and immune studying for neural network-based controller design
    • Distributed challenge fixing utilizing evolutionary learning
    • Evolutionary computing inside of grid environment
    • Evolutionary online game concept in instant mesh networks
    • Hybrid multiobjective evolutionary algorithms for the sailor project problem
    • Evolutionary thoughts in optimization

This ebook may be priceless to researchers in clever structures with curiosity in evolutionary computing, program engineers and approach designers. The publication is also utilized by scholars and academics as a sophisticated examining fabric for classes on evolutionary computing.

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In: Proc. NAFIPS94, pp. 411–415 67. Hancock PJB (1992) Genetic algorithms and permutation problems: A comparison of recombination operators for neural net structure specification. In Proc. Int. Workshop Combinations of Genetic Algorithms and Neural Networks (COGANN-92), pp. 108–122 68. Hanebeck UD, Schmidt GK (1996) Genetic optimization of fuzzy networks. Fuzzy Sets and Systems 79 (1):59–68 69. Hayashi Y (1994) Neural expert system using fuzzy teaching input and its application to medical diagnosis.

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