| 书目名称 | Evolutionary Computation for Modeling and Optimization | | 编辑 | Daniel Ashlock | | 视频video | | | 概述 | Includes over 100 experiments and over 700 homework problems that introduce the topic with an application-oriented approach.Includes supplementary material: | | 图书封面 |  | | 描述 | .Evolutionary Computation for Optimization and Modeling is an introduction to evolutionary computation, a field which includes genetic algorithms, evolutionary programming, evolution strategies, and genetic programming. The text is a survey of some application of evolutionary algorithms. It introduces mutation, crossover, design issues of selection and replacement methods, the issue of populations size, and the question of design of the fitness function. It also includes a methodological material on efficient implementation. Some of the other topics in this book include the design of simple evolutionary algorithms, applications to several types of optimization, evolutionary robotics, simple evolutionary neural computation, and several types of automatic programming including genetic programming. The book gives applications to biology and bioinformatics and introduces a number of tools that can be used in biological modeling, including evolutionary game theory. Advanced techniques such as cellular encoding, grammar based encoding, and graph based evolutionary algorithms are also covered. ..This book presents a large number of homework problems, projects, and experiments, with a goal | | 出版日期 | Textbook 2006 | | 关键词 | algorithms; bioinformatics; evolutionary algorithm; genetic algorithms; genetic programming; optimization | | 版次 | 1 | | doi | https://doi.org/10.1007/0-387-31909-3 | | isbn_softcover | 978-1-4419-1969-4 | | isbn_ebook | 978-0-387-31909-4 | | copyright | Springer-Verlag New York 2006 |
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发表于 2025-3-21 19:46:41
