| 书目名称 | Metaheuristic Procedures for Training Neural Networks | | 编辑 | Enrique Alba,Rafael Martí | | 视频video | | | 概述 | Apart from research efforts bringing together metaheuristic techniques to train artificial neural networks, this is the first book to achieve this objective. This book provides a unified approach to t | | 丛书名称 | Operations Research/Computer Science Interfaces Series | | 图书封面 |  | | 描述 | .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.. | | 出版日期 | Book 2006 | | 关键词 | Approximation; algorithm; algorithms; artificial intelligence; distribution; genetic algorithms; metaheuri | | 版次 | 1 | | doi | https://doi.org/10.1007/0-387-33416-5 | | isbn_softcover | 978-1-4419-4128-2 | | isbn_ebook | 978-0-387-33416-5Series ISSN 1387-666X Series E-ISSN 2698-5489 | | issn_series | 1387-666X | | copyright | Springer-Verlag US 2006 |
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发表于 2025-3-21 19:10:21
