Description: 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.
To Search:
File list (Check if you may need any files):
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
Download