代码搜索：种群进化

找到约 1,664 项符合「种群进化」的源代码

代码结果 1,664
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www.eeworm.com/read/400054/11584203

dat bookinfo.dat

[General Information] 书名=人工神经网络与模拟进化计算 作者= 页数=435 SS号=0 出版日期= Vss号=82329733
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www.eeworm.com/read/390062/8487673

m genetic_algorithm.m

function gaTSP CityNum=30; [dislist,Clist]=tsp(CityNum); inn=100; %初始种群大小 gnmax=1000; %最大代数 pc=0.8; %交叉概率 pm=0.8; %变异概率 %产生初始种群 for i=1:inn s(i,:)=randperm(CityNum); end [f,p]=ob
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www.eeworm.com/read/287873/8663747

m genetic_algorithm.m

function gaTSP CityNum=30; [dislist,Clist]=tsp(CityNum); inn=100; %初始种群大小 gnmax=1000; %最大代数 pc=0.8; %交叉概率 pm=0.8; %变异概率 %产生初始种群 for i=1:inn s(i,:)=randperm(CityNum); end [f,p]=ob
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www.eeworm.com/read/429832/8787178

m cga.m

%(1)初始化各个参数 function[m_pattern]=CGA(m_pattern,patternNum) popSize=200;%种群大小 %初始化种群体结构 for i=1:popSize m_pop(i).string=zeros(1,patternNum);%个体位串
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www.eeworm.com/read/429554/8803074

txt vbants.txt

#include #include #define M 80 /*//种群大小*/ #define T 200 /* //终止代数*/ #define Pc 0.6 /* //交叉概率*/ #define Pm 0.001 /*//变异概率*/ #define Clength 20 /*//定义编码的码长*/ /*//初始化种群*/ /
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www.eeworm.com/read/375027/9375493

m genetic_algorithm.m

function gaTSP CityNum=30; [dislist,Clist]=tsp(CityNum); inn=100; %初始种群大小 gnmax=500; %最大代数 pc=0.8; %交叉概率 pm=0.8; %变异概率 tic %产生初始种群 for i=1:inn s(i,:)=randperm(CityNum); end [f,p
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www.eeworm.com/read/424747/10417703

m gatsp.m

function gaTSP CityNum=30; [dislist,Clist]=tsp(CityNum); inn=100; %初始种群大小 gnmax=1000; %最大代数 pc=0.8; %交叉概率 pm=0.8; %变异概率 %产生初始种群 for i=1:inn s(i,:)=randperm(CityNum); end [f,p]=ob
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www.eeworm.com/read/464509/7156888

m genetic_algorithm.m

function gaTSP CityNum=30; [dislist,Clist]=tsp(CityNum); inn=100; %初始种群大小 gnmax=1000; %最大代数 pc=0.8; %交叉概率 pm=0.8; %变异概率 %产生初始种群 for i=1:inn s(i,:)=randperm(CityNum); end [f,p]=ob
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www.eeworm.com/read/140902/13053481

txt 用遗传算求最值.txt

#include #include #define M 80 /*//种群大小*/ #define T 200 /* //终止代数*/ #define Pc 0.6 /* //交叉概率*/ #define Pm 0.001 /*//变异概率*/ #define Clength 20 /*//定义编码的码长*/ /*//初始化种群*/ /
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www.eeworm.com/read/139365/13159839

m ga.m

function [x,endPop,bPop,traceInfo] = ga(bounds,eevalFN,eevalOps,startPop,opts,... termFN,termOps,selectFN,selectOps,xOverFNs,xOverOps,mutFNs,mutOps) %输出参数 % x：求得最优解；endPop：最终的种群；bPop：最优种群的一个搜索轨迹；
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