文件名称:MATLAB
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2012-11-26
- 文件大小：
- 46kb
- 下载次数：
- 0次
- 提 供 者：
- 李**
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
遗传算法（Genetic Algorithm）是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法，它最初由美国Michigan大学J.Holland教授于1975年首先提出来的，并出版了颇有影响的专著《Adaptation in Natural and Artificial Systems》，GA这个名称才逐渐为人所知，J.Holland教授所提出的GA通常为简单遗传算法（SGA）。
-In artificial intelligence, an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses some mechanisms inspired by biological evolution: reproduction, mutation, recombination, and selection. Candidate solutions to the optimization problem play the role of individuals in a population, and the fitness function determines the environment within which the solutions "live" (see also cost function). Evolution of the population then takes place after the repeated application of the above operators. Artificial evolution (AE) describes a process involving individual evolutionary algorithms EAs are individual components that participate in an AE.
-In artificial intelligence, an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses some mechanisms inspired by biological evolution: reproduction, mutation, recombination, and selection. Candidate solutions to the optimization problem play the role of individuals in a population, and the fitness function determines the environment within which the solutions "live" (see also cost function). Evolution of the population then takes place after the repeated application of the above operators. Artificial evolution (AE) describes a process involving individual evolutionary algorithms EAs are individual components that participate in an AE.
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下载文件列表
MATLAB
......\hs_err_pid7400.log
......\NO1.asv
......\NO1.m
......\NO2.asv
......\NO2.m
......\NO3.asv
......\NO3.m
......\rigid.asv
......\rigid.m
......\rigid000.m
......\rigid1.m
......\rigid2.m
......\rigid3.m
......\solu.m
......\数据拟合.asv
......\数据拟合.m
......\运筹大作业
......\..........\aaaaaa.asv
......\..........\delay.asv
......\..........\figureshow.asv
......\..........\figureshow.fig
......\..........\figureshow.m
......\..........\Homework.asv
......\..........\Homework.m
......\..........\NUCNum.asv
......\..........\NUCNum.m
......\..........\reach.asv
......\..........\reach.m
......\..........\read.txt
......\..........\result.txt
......\..........\unload.m
......\..........\untitled.asv
......\..........\untitled.fig
......\..........\untitled1.asv
......\..........\untitled1.fig
......\..........\untitled1.m
......\..........\运筹大作业.asv
......\遗传算法的实现
......\..............\GA.asv
......\..............\GA.m
......\..............\GA.zip
......\hs_err_pid7400.log
......\NO1.asv
......\NO1.m
......\NO2.asv
......\NO2.m
......\NO3.asv
......\NO3.m
......\rigid.asv
......\rigid.m
......\rigid000.m
......\rigid1.m
......\rigid2.m
......\rigid3.m
......\solu.m
......\数据拟合.asv
......\数据拟合.m
......\运筹大作业
......\..........\aaaaaa.asv
......\..........\delay.asv
......\..........\figureshow.asv
......\..........\figureshow.fig
......\..........\figureshow.m
......\..........\Homework.asv
......\..........\Homework.m
......\..........\NUCNum.asv
......\..........\NUCNum.m
......\..........\reach.asv
......\..........\reach.m
......\..........\read.txt
......\..........\result.txt
......\..........\unload.m
......\..........\untitled.asv
......\..........\untitled.fig
......\..........\untitled1.asv
......\..........\untitled1.fig
......\..........\untitled1.m
......\..........\运筹大作业.asv
......\遗传算法的实现
......\..............\GA.asv
......\..............\GA.m
......\..............\GA.zip