Description: 敝人最近整理的关于MatLab中的遗传算法工具箱Gads的资料，不敢独享，希望能起到一定的帮助作用-myself recently finishing on the MatLab genetic algorithm toolbox Gads information, not exclusive, hope to play a helpful role Platform: |
Size: 12288 |
Author:遗传算法爱好者 |
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Description: 介绍遗传算法的原理，流程。详细展示了交叉，变异，选择等算子。同时，还介绍了谢菲尔德大学遗传工具箱的使用 。本书对初学遗传算法者很有帮助。-Introduce the principle of genetic algorithms, processes. Detail shows crossover, mutation, selection operator. Meanwhile, the University of Sheffield also introduced the use of genetic toolbox. Genetic algorithms for beginners who book very helpful. Platform: |
Size: 9717760 |
Author:CaoJunlong |
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Description: MATLAB遗传算法工具箱及应用。本书系统介绍MATLAB遗传算法和直接搜索工具箱的功能特点、编程原理及使用方法。全书共分为9章。第一章至第四章介绍遗传算法的基础知识，包括遗传算法的基本原理，编码、选择、交叉、变异，适应度函数，控制参数选择，约束条件处理，模式定理，改进的遗传算法，早熟收敛问题及其防止等。-MATLAB genetic algorithm toolbox and its application. This book describes the features of MATLAB Genetic Algorithm and Direct Search Toolbox, programming principles and use. The book is divided into nine chapters. Chapter to Chapter IV describes the basics of the genetic algorithm, including the basic principles of genetic algorithm, encoding, selection, crossover and mutation, the fitness function, the control parameter selection and processing constraints, schema theorem, improved genetic algorithm, precocious convergence problem and its prevention. Platform: |
Size: 9704448 |
Author:谢 |
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Description: 一本很好的学习遗传算法的书籍，《MATLAB遗传算法工具箱及应用》 雷英杰版-MATLAB genetic algorithm toolbox and its application Ying-jie lei version Platform: |
Size: 9755648 |
Author:张尚然 |
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Description: Matlab 遗传算法(Genetic Algorithm)优化工具箱是基于基本操作及终止条件、二进制和十进制相互转换等操作的综合函数库。其实现步骤包括：通过输入及输出函数求出遗传算法主函数、初始种群的生成函数，采用选择、交叉、变异操作求得基本遗传操作函数。以函数仿真为例，对该函数优化和GA 改进，只需改写函数m 文件形式即可。(The Matlab Genetic Algorithm optimization toolbox is a comprehensive function library based on basic operations and termination conditions, binary and decimal conversion and other operations. The implementation steps include: the main function of genetic algorithm and the generation function of the initial population are obtained by the input and output functions, and the basic genetic operation function is obtained by the selection, crossover and mutation operations. Taking function simulation as an example, the function optimization and GA improvement only need to rewrite function m file form) Platform: |
Size: 9216 |
Author:FZenjoys |
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