还是把程序贴出来吧:
clc
clear
p=[0.8800 0.7800 0.6700;0.8900 0.7900 0.6800;0.9000 0.8000 0.6900;0.9100 0.8100 0.7000;0.9200 0.8200 0.7100;0.9000 0.8000 0.7200;0.9800 0.8900 
0.7300;0.9500 0.8500 0.7400;0.9600 0.8800 0.7500;0.9700 0.8700 0.7600;0.9800 0.8800 0.7700;0.9900 0.8900 0.7800;0.8500 0.9800 0.7900;0.8600 
0.9100 0.8000;0.8700 0.9200 0.8100;0.8800 0.9300 0.8200;0.8900 0.9400 0.8300;0.9000 0.9500 0.8400;0.9100 0.9600 0.8500;0.9200 0.9700 
0.8600;0.9300 0.9800 0.8700;0.9400 0.9900 0.8800;0.9500 0.9800 0.8900;0.9000 0.9100 0.9000;0.9700 0.9200 0.9100;0.8800 0.9300 0.9200;0.8900 
0.9400 0.9300;1.0000 0.9500 0.9400;1.0100 0.9600 0.9500;1.0200 0.9700 0.9600;1.0300 1.0800 1.0300;1.0400 0.9800 0.9800;1.0500 0.9100 
0.9900;1.0600 0.9200 1.0000;1.0700 0.9300 1.0100;1.0800 0.9400 1.0200;1.0900 0.9500 1.0300;1.1000 1.1500 1.0400;1.1100 1.1600 1.0500;0.7700 
0.6500 0.5500;0.7600 0.6400 0.5400;0.7500 0.6300 0.5300;0.7400 0.6200 0.5200;0.7300 0.6100 0.5100;0.7200 0.6000 0.5000;0.7100 0.5900 
0.4900;0.7000 0.5800 0.4800;0.6900 0.5700 0.4700;0.6800 0.5600 0.4600;0.6700 0.5500 0.4500;0.6600 0.5400 0.4400;0.6500 0.5300 0.4300;0.6400 
0.5200 0.4200;0.6300 0.5100 0.4100;0.6200 0.5000 0.4000;0.6100 0.4900 0.3900;0.6000 0.4800 0.3800;0.5900 0.4700 0.3700;0.5800 0.4600 
0.3600;0.5700 0.4500 0.3500;0.5600 0.4400 0.3400;0.5500 0.4300 0.3300;0.5400 0.4200 0.3200;0.5300 0.4100 0.3100;0.5200 0.4000 0.3000;0.5100 
0.3900 0.2900;0.5000 0.3800 0.2800;0.4900 0.3700 0.2700;0.4800 0.3600 0.2600;0.4700 0.3500 0.2500;0.4600 0.3400 0.2400;0.4500 0.3300 
0.2300;0.4400 0.3200 0.2200;0.4300 0.3100 0.2100;0.4200 0.3000 0.2000;0.4100 0.2900 0.1900;0.4000 0.2800 0.1800;0.3900 0.2700 0.1700;0.3800 
0.2600 0.1600;0.3700 0.2500 0.1500;0.3600 0.2400 0.1400;0.3500 0.2300 0.1300;0.3400 0.2200 0.1200;0.3300 0.2100 0.1100;0.3200 0.2000 
0.1000;0.3100 0.1900 0.0900;0.3000 0.1800 0.0800;0.2900 0.1700 0.0700;0.2800 0.1600 0.0600;0.2700 0.1500 0.0500;0.2600 0.1400 0.0400;0.2500 
0.1300 0.1200;0.2400 0.1200 0.1100;0.2300 0.1100 0.1000;0.2200 0.1000 0.0900;0.2100 0.0900 0.0800;0.2000 0.0800 0.0700;0.1900 0.0700 
0.0600;0.1800 0.0600 0.0500;0.1700 0.0500 0.0400];
t=[1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1  0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ];
[y,ps] =mapminmax(p,-1,1);
[normInput,ps] = mapminmax(p);
[normTarget,ts] = mapminmax(t);
[trainV,valV,testV] = dividevec(p,t,valPercent,testPercent);
testPercent = 0.20;  
validatePercent = 0.20;  
[trainSamples,validateSamples,testSamples] = dividevec(normInput,normTarget,validatePercent,testPercent);
NodeNum1 = 20; 
NodeNum2=40;   
TypeNum = 1;  
TF1 = 'tansig';TF2 = 'tansig'; TF3 = 'tansig';
net=newff(minmax(normInput),[NodeNum1,NodeNum2,TypeNum],{TF1 TF2 TF3},'traingdx');
net.trainParam.epochs=10000;
net.trainParam.goal=1e-6;
net.trainParam.lr=0.01;
net.trainFcn = 'trainrp'; 
[net,tr] = train(net,trainSamples.P,trainSamples.T,[],[],validateSamples,testSamples);
normTrainOutput,Pf,Af,E,trainPerf] = sim(net,trainSamples.P,[],[],trainSamples.T);
[normValidateOutput,Pf,Af,E,validatePerf] = sim(net,validateSamples.P,[],[],validateSamples.T);
[normTestOutput,Pf,Af,E,testPerf] = sim(net,testSamples.P,[],[],testSamples.T);
trainOutput = mapminmax('reverse',normTrainOutput,ts);
trainInsect = mapminmax('reverse',trainSamples.T,ts);
validateOutput = mapminmax('reverse',normValidateOutput,ts);
validateInsect = mapminmax('reverse',validateSamples.T,ts);
testOutput = mapminmax('reverse',normTestOutput,ts);
testInsect = mapminmax('reverse',testSamples.T,ts);
figure
plot(1:12,[trainOutput validateOutput],'b-',1:12,[trainInsect validateInsect],'g--',13:15,testOutput,'m*',13:15,testInsect,'ro');
title('o为真实值,*为预测值')
xlabel('项目');
ylabel('结论');