神经网络预测

P = x';T = y';[P1,ps] = mapminmax(P);[T1,ps2] = mapminmax(T);net=newff(minmax(P),[10,1],{'tansig','purelin'},'traingda');net.trainParam.goal=0.001;net.trainParam.show=20;net.trainParam.epochs=5000;net.trainParam.min_grad=1e-10;net.trainParam.mc=0.95;[net,tr]=train(net,P1,T1);t1=sim(net,P1);plot(t1,T1,'.')title('神经网络预测PM2.5')xlabel('实际值')ylabel('预测值')[P2,ps3] = mapminmax(m');t2=sim(net,P2);figureA2 = mapminmax('reverse',t2,ps2);plot(fliplr([y',A2]),'.')title('神经网络预测PM2.5')xlabel('日期')ylabel('PM2.5')set(gca,'xtick',1:365:1210);set(gca,'xticklabel',{'2010\01\02','2011\01\02','2012\01\02','2013\01\02'});