tree_ga2.m

这是好用的源代码

%      注意: 必须先运行ga_ini来初始化参数
% 函数调用: pcincl.m, equ_gen3.m, opt_par.m, mutato3.m, x_over2.m,
%           fit_fun2.m, strrem.m, strep2.m, fps.m, lin_seed, disp_res,
%           permut.m

close all
clear p e1 e2 e3
a=0;
count=0;
results=[0 0 0];

% 设置随机数种子 
rand('seed',sum(100*clock)) 
randn('seed',sum(100*clock)) 
% 初始化屏幕
% 清屏
main=figure('Number','Off',...
        'Name','遗传算法GA For MATLAB',...
        'Resize','off',...
        'Units','Pixels',...
        'Position',[2 2 636 455]);
drawnow;
ax1=axes(...
        'Units','pixels',...
        'Position',[60 270 520 130],...
        'Box','on',...
        'Color',[0 0 0],...
        'Visible','on');

ax2=axes(...
        'Units','pixels',...
        'Position',[60 110 230 100],...
        'Box','on',...
        'Color',[0 0 0],...
        'Visible','on');

ax3=axes(...
        'Units','pixels',...
        'Position',[350 110 230 100],...
        'Box','on',...
        'Color',[0 0 0],...
        'Visible','on'); 
% 为调用ad_just2 初始化串
% 在群体选择之前最大的方案个数
%  => pop_size
y_front='y_est(:,1)=';
colons=';';
for i=2:pop_size,
   y_front=str2mat2(y_front,['y_est(:,' num2str(i) ')=']);
   colons=str2mat2(colons,';');
end
% 设置输入(u) 输出(y)变量
[D L]=size(output_var);
for i = 1 : L
   if output_var(i) == 1
      y=data(:,i);
      break;
   end
end
% 输入数据矩阵赋值
u=pcincl(data,include_var,output_var);
[num_data,num_inp]=size(u);
stdy = std(y);

%用线性模型生成种子群体 
lin_seed
[seed_num,xxx]=size(seed_pop);
seed_flag=1;
% 初始化输入
for i=1:num_inp,
         eval(['u' num2str(i) '= u(:,' num2str(i) ');']);
end
%产生初始群体

if seed_flag==0
   pop = equ_gen3(s_length,num_inp,equ_par,fun_set,num_fun_arg_set,user_def_fun);
   pop=opt_par(pop,u,y,num_inp,options,time_out);
else
   pop = seed_pop;
end

for i=seed_num+1:pop_size,

   x2 = equ_gen3(s_length,num_inp,equ_par,fun_set,num_fun_arg_set, user_def_fun);
   x2=opt_par(x2,u,y,num_inp,options,time_out);
   pop = str2mat2(pop, x2);
   
end
% 绘图初始化
theta=[0 0]';
text3=ga_text(main,210,410,200,15,'0 - 代',[1 1 1],[0 0 0]);
text1=ga_text(main,20,35,600,15,'当前代最佳树:',[1 1 1],[1 0 0]);
text2=ga_text(main,20,20,600,15,'',[1 1 1],[1 0 0]);
text6=ga_text(main,20,2,145,15,'适应度:',[1 1 1],[1 0 0]);
text7=ga_text(main,165,2,145,15,'',[1 1 1],[1 0 0]);
text8=ga_text(main,300,2,145,15,'误差均方根:',[1 1 1],[1 0 0]);
text9=ga_text(main,435,2,185,15,'',[1 1 1],[1 0 0]);
MAX_FIT=[];
% 代循环
for i=1:num_gen,
  [Q,R]=size(pop);
  disp(['Generation ' num2str(i)])
% 确定每个个体（方程）在群体中的适应度
  [fit,pop,mod_size,str_len]=fit_fun2(ffunc,pop,pop_size,u,y,num_data,num_inp,stdy,y_front,colons,snip_length);
  [max_fit,max_fit_ind]=max(fit);
  [min_fit,min_fit_ind]=min(fit);

  set(text3,'string',[num2str(i) ' - 代']);
% 求出最佳串，并计算theta值
out=['y_e = ' pop(max_fit_ind,:) ';'];
% 去掉 '{', '}', '<1', '<2', '<3' and '>'  
out=strrem(out);      
out = strep2(out);
eval(out);
if ffunc=='ccf',
   data=[y_e ones( num_data,1)];
   theta=inv(data'*data)*data'*y;
   y_est1=y_e;
   y_p1=data*theta;

   y_p=y_p1;
   
elseif ffunc=='mse',
   y_p = y_e;
end


count = count +1;
drawnow; 
a=fit(max_fit_ind);       
if count >= presults,
   % 显示结果
   disp_res
   count=0;
end
% 做存储间隔检查
  if rem(i,dump_num) == 0,
    if i==dump_num,
       save_theta=theta';
       save_pop=pop(max_fit_ind,:);
       save_fit=a;
    else
       save_theta=[save_theta; theta'];
       save_pop=str2mat2(save_pop,pop(max_fit_ind,:));
       save_fit=[save_fit; a];
    end
  save save_pop save_theta save_pop save_fit
  end 

   %确定下一代的大小

   new_size=floor((1-p_old)*mod_size);

   % 挑选遗传算子
   
  new_pop=[];
  j=0;
  while j < new_size,
     p_gen=rand(1);
     if p_gen < p_mutate,                % 转变
        fps_num=fps(fit);
        
        deblank_pop = deblank(pop(fps_num,:));
        pop_mut = mutato3(deblank_pop,u,y,num_inp,p_c2u,mut_fun_wgt,...
  mut_fun_set,mut_num_fun_arg_set,fun_name,num_fun_arg,user_def_fun,equ_par);
        if strcmp(deblank(pop(fps_num,:)),pop_mut) == 0,
           pop_mut=opt_par(pop_mut,u,y,num_inp,options,time_out);
        end
        
        j=j+1;
        if j==1,
           new_pop=pop_mut;
        else   
           new_pop=str2mat2(new_pop,pop_mut);
        end
     elseif p_gen < p_mutate + p_cross,  % 交叉
        x_fps_num=fps(fit);
        y_fps_num=fps(fit);
        
        [xnew,ynew]=x_over2(deblank(pop(x_fps_num,:)),deblank(pop(y_fps_num,:)));
        xnew=opt_par(xnew,u,y,num_inp,options,time_out);
        ynew=opt_par(ynew,u,y,num_inp,options,time_out);
        
        if j < new_size-1,
           j=j+2;
           if j==2,
              new_pop=xnew;
              new_pop=str2mat2(new_pop,ynew);
           else   
              new_pop=str2mat2(new_pop,xnew,ynew);
           end
        else
           j=j+1;
           new_pop=str2mat2(new_pop,xnew); 
        end
     elseif p_gen < p_mutate + p_cross + p_perm, % 转换
        fps_num=fps(fit);
        
        deblank_pop = deblank(pop(fps_num,:));
        pop_perm = permut(deblank_pop,num_inp,fun_set,num_fun_arg_set,fun_name,...
                     num_fun_arg,user_def_fun);
 
        if strcmp(deblank(pop(fps_num,:)),pop_perm) == 0,
           pop_perm=opt_par(pop_perm,u,y,num_inp,options,time_out);
        end
        
        j=j+1;
        if j==1,
           new_pop=pop_perm;
        else   
           new_pop=str2mat2(new_pop,pop_perm);
        end
     else                                % 直接再生
        fps_num=fps(fit);
     
        j=j+1;
        if j==1,
           new_pop=pop(fps_num,:)
        else
           new_pop=str2mat2(new_pop,pop(fps_num,:));
        end        
     end
 
  end
  % 旧世代排序
  sort_pop = pop;
  sort_fit = fit;
  for j=1:pop_size,
     [max_fit,max_fit_ind]=max(sort_fit);
     sort_pop(j,:) = pop(max_fit_ind,:);
     sort_fit(max_fit_ind) = -inf;
  end
  % 旧世代存活成员加入
  keep_pop=sort_pop(1:pop_size-new_size,:);
  pop=str2mat(new_pop,keep_pop);
 
% 重新初始化检查
  if rem(i,rein_num) == 0,
      best_pop=keep_pop(1,:);
      clear pop
      pop=best_pop; 
     for j=2:pop_size,
        x2 = equ_gen3(s_length,num_inp,equ_par,fun_set,num_fun_arg_set,user_def_fun)
        x2=opt_par(x2,u,y,num_inp,options,time_out);
        pop = str2mat2(pop, x2);
     end   
  end 
  clear new_pop keep_pop
% 混合群体
pop=shuffle(pop);
end