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    Metaheuristic Procedures for Training Neural Networks Metaheuristic Procedures for Training Neural Networks
    Operations Research/Computer Science Interfaces Series

    Metaheuristic Procedures for Training Neural Networks

    Enrique Alba & Rafael Martí
      • $139.99
      • $139.99

    Publisher Description

    Metaheuristic Procedures For Training Neural Networks provides successful implementations of metaheuristic methods for neural network training. Moreover, the basic principles and fundamental ideas given in the book will allow the readers to create successful training methods on their own. Apart from Chapter 1, which reviews classical training methods, the chapters are divided into three main categories. The first one is devoted to local search based methods, including Simulated Annealing, Tabu Search, and Variable Neighborhood Search. The second part of the book presents population based methods, such as Estimation Distribution algorithms, Scatter Search, and Genetic Algorithms. The third part covers other advanced techniques, such as Ant Colony Optimization, Co-evolutionary methods, GRASP, and Memetic algorithms. Overall, the book's objective is engineered to provide a broad coverage of the concepts, methods, and tools of this important area of ANNs within the realm of continuous optimization.

    GENRE
    Business & Personal Finance
    RELEASED
    2006
    August 25
    LANGUAGE
    EN
    English
    LENGTH
    264
    Pages
    PUBLISHER
    Springer US
    SELLER
    Springer Nature B.V.
    SIZE
    6.6
    MB

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