da_ga3.m

王小平《遗传算法——理论、应用与软件实现》随书光盘

%
% da_ga3.m
%
% Non-Linear Dynamic GA model
%

%
% Get the Parameters before clearing the screen
%
global stop;
members=ceil(get(sl1,'value'));
members=round(members/2)*2;
pmutate=get(sl2,'value');
pcross=get(sl3,'value');
maxgen=ceil(get(sl4,'value'));
presults=str2num(get(text8,'string'));
d1=str2num(get(text11,'string'));
d2=str2num(get(text13,'string'));
d3=str2num(get(text15,'string'));
d1=[d1 d2 d3]
d4=str2num(get(text17,'string'));
d5=str2num(get(text19,'string'));
d6=str2num(get(text21,'string'));
d2=[d4 d5 d6];
%
% Clear the screen
%
da_front;
drawnow;
set(w1,'NumberTitle','off','Name','Building Dynamic Non-Linear GA Model');

%
% Plot a couple of axes
%
ax1=axes(...
	'Units','pixels',...
	'Position',[60 270 500 130],...
	'Box','on',...
	'Color',[0 0 0],...
	'Visible','on');

ax2=axes(...
	'Units','pixels',...
	'Position',[60 125 230 100],...
	'Box','on',...
	'Color',[0 0 0],...
	'Visible','on');

box1=uicontrol(w1,...
	'style','frame',...
	'position',[400 20 200 30],...
	'backgroundcolor',[0 0 0],...
	'foregroundcolor',[1 1 1]);

box2=uicontrol(w1,...
	'style','frame',...
	'position',[410 25 1 20],...
	'foregroundcolor',[0 0 1],...
	'backgroundcolor',[0 0 1]);

box3=uicontrol(w1,...
	'style','frame',...
	'position',[400 60 200 30],...
	'backgroundcolor',[0 0 0],...
	'foregroundcolor',[1 1 1]);

box4=uicontrol(w1,...
	'style','frame',...
	'position',[410 65 1 20],...
	'foregroundcolor',[0 0 1],...
	'backgroundcolor',[0 0 1]);

text1=da_text(w1,110,28,280,15,'Percentage of current generation complete:',[1 1 1],[1 0 0]);
text2=da_text(w1,110,63,280,15,'Percentage of current generation decoded :',[1 1 1],[1 0 0]);
text3=da_text(w1,440,220,100,15,'0 - Generations',[1 1 1],[0 0 0]);
text4=da_text(w1,400,95,20,15,'0',[1 1 1],[0 0 0]);
text5=da_text(w1,560,95,40,15,'100 %',[1 1 1],[0 0 0]);
text6=da_text(w1,210,410,200,15,'GA RUNNING. Press ^C to stop',[1 1 1],[1 0 0]);

%
% Save model button
%
but1=uicontrol(w1,...
	'style','push',...
	'position',[400 150 200 20],...
	'string','Save model description',...
	'callback','da_svmod;');

but2=uicontrol(w1,...
	'style','push',...
	'position',[400 120 200 20],...
	'string','Save model for OnLine use',...
	'callback','svlin('''',include_var,sdx,mx,sdy,my,c,p,f);');

drawnow;
%
% Set up the x and y variables
%
if sum(output_var) > 1
	[D L]=size(output_var);
	for i = 1 : L
		if output_var(i) == 1
			y=data(:,i);
			break;
		end
	end
else
	y=data(:,output_var);
end

x=pcincl(data,include_var,output_var);
[x mx sdx]=mceng2(x);
[y my sdy]=mceng2(y);


%
% Determine the population size
%

d=[];
d3=[];
d4=[];
[D L]=size(x);
for i = 1:L
	d3(i,:)=d1;
end
for i = 1:L
	d4(i,:)=d2;
end
d=[d3;d4];
[o d b]=decode(0,d,0);
popsize=sum(b);

%
% Create the initial random population
%
chrom=newpop(members,popsize);

%
% Go for a number of generations
%
results=[0 0 0];
count=0;
c=0;
p=0;
f=0;
for i = 1:maxgen
	%
	% Cross and mutate
	%
	[D L]=size(chrom);
	for j = 1 : 2 :members
		chrom(j,:)=mutate(chrom(j,:),0.02);
		chrom(j+1,:)=mutate(chrom(j+1,:),0.02);
		[chrom(j,:) chrom(j+1,:)]=crover(chrom(j,:),chrom(j+1,:),0.02);
	end

	%
	% Select the best
	%
	[chrom coefs pin]=select3(chrom,d,x,y,box2,box4);
	count=count+1;
	set(text3,'string',[num2str(i) ' - Generations']);
	set(box2,'position',[410 25 1 20]);
	set(box4,'position',[410 65 1 20]);
	if count >= presults

		%
		% Decode this popultaion and plot results
		%
		results(i,:)=[min(pin) mean(pin) max(pin)];
		[D L]=size(coefs);
		[D1 L1]=size(x);
		[c,in]=min(pin);
		p=coefs(in,1:L1);
		f=coefs(in,L1+1:L);
		x2=pol2(x,p);
		x2=fil(x2,f);
		c=pinv(x2'*x2)*x2'*y;
		yest=x2*c;
		[c2,in]=max(pin);
	
		axes(ax1);
		plot([resclg(y,my,sdy) resclg(yest,my,sdy)]);
		Xlabel('Sample number');
		Ylabel('Actual & Predicted');
		axes(ax2);
		plot(results(:,1));
		Xlabel('Generation number');
		Ylabel('Error');
		drawnow;
	
		if stop == 1
			break;
		end
		count=0;	
	else
		results(i,:)=[min(pin) mean(pin) max(pin)];
		axes(ax2)
		plot(results(:,1));
		Xlabel('Generation number');
		Ylabel('Error');
		drawnow;
	end
end