disp_res.m

遗传算法的matlab程序集（内有很多问题的具体解决程序）

%绘图显示结果
count=0;
a=fit(max_fit_ind);
b=mean(fit);
c=sqrt(sum((y-y_p).^2)/num_data);
d=mean(str_len);
e=max(str_len);
f=min(str_len);
g=str_len(max_fit_ind);

if i==1,
  FIT = a;
  MEAN_FIT=b;
  MEAN_LEN=d;
  MAX_LEN=e;
else
  FIT = [FIT; a ];
  MEAN_FIT = [MEAN_FIT; b ];
  MEAN_LEN=[MEAN_LEN; d];
  MAX_LEN=[MAX_LEN; e];
end
      
axes(ax1);
hold off
plot(y,'r')
hold on
plot(y_p,'g')
xlabel('样本');
ylabel('实际与预测值');
legend('实际','预测')         
         
axes(ax2);
hold off
plot([1:presults:i]',FIT,'c');        
hold on
plot([1:presults:i]',MEAN_FIT,'b');        
xlabel('代数');
ylabel('适应度');
legend('最大','最小') 
         
axes(ax3);
hold off
hist(str_len)
[bin_value,bin_num]=hist(str_len);
hold on
plot([snip_length snip_length],[0 max(bin_value')],'r')
plot(g,0,'g*')
xlabel('串长');
ylabel('数目');

%简化表达式的屏幕表示

if simp_disp==1,
   x=(pop(max_fit_ind,:));
   
   ns2time1=clock;
   
   x=n_simp2(x);
   
   ns2time2=clock;
   
   ns2time=ns2time+etime(ns2time2,ns2time1);
   
   simp_pop=x;
else   
   simp_pop=(pop(max_fit_ind,:));
end
    
set(text2,'string',simp_pop);
set(text7,'string',num2str(a));
set(text9,'string',num2str(c));