神經(jīng)網(wǎng)絡(luò)的一個例子

本文格式為Word版，下載可任意編輯——神經(jīng)網(wǎng)絡(luò)的一個例子

clear

%數(shù)據(jù)輸入

huanghe_p=[370503434575490420560640558343326405446423422697598377435472451667601689541485425389382707422];

huanghe_t=[5157135867537205677179878104894535896395685959828495196156525999418939997587016305615201040535];

%歸一化處理

p=(huanghe_p-min(huanghe_p))/(max(huanghe_p)-min(huanghe_p));

t=(huanghe_t-min(huanghe_t))/(max(huanghe_t)-min(huanghe_t));

%數(shù)據(jù)輸入2：網(wǎng)絡(luò)有關(guān)參數(shù)

EPOCHS=10000;

GOAL=0.000005;

%建立bp神經(jīng)網(wǎng)絡(luò)，并訓(xùn)練，仿真。其中輸入為p，輸出為t

%隱層神經(jīng)元確定

s=3:15;%s為常向量，表示神經(jīng)元的個數(shù)

res=zeros(size(s));%res將要存儲誤差向量，這里先置零

pn=[p(1:5);p(6:10);p(11:15);p(16:20)];

tn=[t(1:5);t(6:10);t(11:15);t(16:20)];

fori=1:length(s)

net=newff(minmax(pn),[s(i),4],{'tansig','purelin'},'trainlm');

net.iw{1,1}=zeros(size(net.iw{1,1}))+0.5;

net.lw{2,1}=zeros(size(net.lw{2,1}))+0.75;

net.b{1,1}=zeros(size(net.b{1,1}))+0.5;

net.b{2,1}=zeros(size(net.b{2,1}));

net.trainParam.epochs=EPOCHS;

net.trainParam.goal=GOAL;

net=train(net,pn,tn);

y=sim(net,pn);

e=tn-y;

error=mse(e,net);

res(i)=norm(error);

end

%選取最優(yōu)神經(jīng)元數(shù)，number為使得誤差最小的隱層神經(jīng)元個數(shù)

number=find(res==min(res));

if(length(number)1)no=number(1)

elseno=number

end

clearerror，res

%選定隱層神經(jīng)元數(shù)目后，建立網(wǎng)絡(luò)，訓(xùn)練仿真。

net=newff(minmax(pn),[no,4],{'tansig','purelin'},'trainlm');

net.iw{1,1}=zeros(size(net.iw{1,1}))+0.5;

net.lw{2,1}=zeros(size(net.lw{2,1}))+0.75;

net.b{1,1}=zeros(size(net.b{1,1}))+0.5;

net.b{2,1}=zeros(size(net.b{2,1}));

net.trainParam.epochs=EPOCHS;

net.trainParam.goal=GOAL;

net=train(net,pn,tn);

y=sim(net,pn);

e=tn-y;

error=mse(e,net)%error為網(wǎng)絡(luò)的誤差向量

r=norm(error);%r為網(wǎng)絡(luò)的整體誤差

savenet%保存最好的網(wǎng)絡(luò)

%預(yù)計

input=[p(11:15);p(16:20);p(21:25);p(26:30)];

yuce=sim(net,input);

%結(jié)果反歸一化

y1=[y(1,:)y(2,:)y(3,:)y(4,:)];

yuce1=[yuce(1,:)yuce(2,:)yuce(3,:)yuce(4,:)];

t1=y1*(max(huanghe_t(1:20))-min(huanghe_t(1:20)))+min(huanghe_t(1:20));

yuce2=yuce1*(max(huanghe_t(1:20))-min(huanghe_t(1:20)))+min(huanghe_t(1:20));

%計算誤差

wucha=abs(t1-huanghe_t(1:20))./huanghe_t(1:20)

b=minmax(wucha);

average_wucha=mean(wucha);

%作圖

figure(1)

plo