Description: ：基于Matlab语言的遗传算法工具箱支持二进制和浮点数编码方式，并且提供了多种选择、交叉、变异的方法。
通过具体实例对Matlab的遗传算法工具箱的用法进行了说明介绍。-: Based on the Matlab language genetic algorithm toolbox and floating point support for binary encoding, and provides a wide range of selection, crossover and mutation method. Through concrete examples of Matlab genetic algorithm toolbox described the usage of introduction. Platform: |
Size: 100352 |
Author:icyrock |
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Description: MATLAB遗传算法工具箱函数及应用实例，:基于Matlab语言的遗传算法工具箱支持二进制和浮点数编码方式，并且提供了多种选择、交叉、变异的方法。
通过具体实例对Matlab的遗传算法工具箱的用法进行了说明介绍。
-MATLAB genetic algorithm toolbox function and application example: Based on the Matlab language genetic algorithm toolbox and floating point support for binary encoding, and provides a wide range of selection, crossover and mutation method. Through concrete examples of Matlab genetic algorithm toolbox use a note. Platform: |
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Author:李扬宇 |
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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: |
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Author:谢 |
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Description: In this paper, an attractive approach for teaching genetic algorithm has been
presented. This approach is based primarily on using MATLAB in
implementing the genetic operators: crossover, mutation, and selection. An
advantage of using such an approach is that the student becomes familiar with
some advanced features of MATLAB, and furthermore, with the availability of
other MATLAB Toolboxes such as The Control Systems Toolbox, Neural
Network Toolbox and Fuzzy Logic Toolbox, it is possible for the student to
develop genetic algorithm-based approaches to designing intelligent systems,
which could lead to his/ her final year or MSc project. Platform: |
Size: 98304 |
Author:jacob1717 |
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Description: 这本书描述了MATLAB遗传算法的特性和直接搜索工具箱,编程原理和使用方法。这本书分为九章。第一章到第四章介绍了遗传算法的基本知识,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、约束处理,模式定理,改进遗传算法早熟收敛问题及其预防等等。第五章到第七章介绍MATLAB遗传算法工具箱英格兰谢菲尔德谢菲尔德大学,和使用方法,如何编写这个函数的一个示例使用遗传算法工具箱解决实际优化问题的MATLAB程序。-The book describes the characteristics of MATLAB genetic algorithm and direct search toolbox, programming principle and method of use. The book is divided into nine chapters. The first chapter to the fourth chapter introduces the basic knowledge of the genetic algorithm, including the basic principle of genetic algorithm, coding, selection, crossover, mutation, fitness function, control parameters, constraints, processing, schema theorem, improved genetic algorithm premature convergence problem and its prevention and so on. Fifth chapter to the seventh chapter introduces MATLAB genetic algorithm toolbox Sheffield in England at the university of Sheffield, and use a method, an example of how to write this function using MATLAB genetic algorithm toolbox to solve practical optimization problem. Platform: |
Size: 4673536 |
Author:李勃 |
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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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Search - matlab toolbox crossover mutation