N2O=[0.101?0.102?0.106?0.109?0.111?0.113?0.114?0.118?0.119?0.122?0.125?0.129?0.132?0.133?...
????0.135?0.137?0.139?0.142?0.144?0.147?0.151?0.153?0.155?0.157?0.159?0.161];
CFCot=[0.091?0.096?0.102?0.108?0.113?0.117?0.124?0.131?0.136?0.141?0.147?0.152?0.156?0.16?...
????0.162?0.165?0.166?0.167?0.169?0.17?0.17?0.171?0.171?0.171?0.171?0.171];
CFCoo=[0.039?0.041?0.043?0.045?0.048?0.05?0.053?0.055?0.058?0.061?0.063?0.065?0.066?0.067?...
????0.067?0.067?0.067?0.067?0.067?0.066?0.066?0.066?0.065?0.065?0.064?0.064];
ozone=[265.7369863?264.4027397?262.1863014?264.6383562?256.2438356?259.8191781?252.5342466?254.7369863?261.5561644...
????251.5287671?257.4383562?253.6383562?258.8690248?250.4506966?247.8975649?257.2696823?255.2685?252.9157609?...
????245.837527?256.2294319?250.4585185?250.3536513?255.4165116?249.8003694?253.9006126?247.8528705];
p=[N2O;CFCot;CFCoo];?????%輸入數(shù)據(jù)矩陣
t=[ozone];???????????????%輸出數(shù)據(jù)矩陣
%對(duì)輸入矩陣r和輸出矩陣c中數(shù)據(jù)進(jìn)行歸一化處理
[p1pn]=mapminmax（p）;
[t1tn]=mapminmax（t）;
%創(chuàng)建一個(gè)BP網(wǎng)絡(luò)，訓(xùn)練函數(shù)為trainlm隱含層為三層，節(jié)點(diǎn)數(shù)分別為1896，傳遞函數(shù)分別為logsigpurelintansig
net=newff（pt[1896]{‘logsig‘‘purelin‘‘tansig‘}‘trainlm‘）;?%建立模型
net.trainParam.show=1000;?????????????%1000次顯示一次結(jié)果
net.trainParam.lr=0.05;???????????????%學(xué)習(xí)速度為0.05
net.trainParam.epochs=5000;???????????%最大訓(xùn)練輪回為5000次
net.trainParam.goal=0.0000004;????????%均方誤差為0.0000004
net=train（netp1t1）;?????????????????%開始訓(xùn)練，p1t1分別為輸入輸出的訓(xùn)練數(shù)據(jù)
%利用原始數(shù)據(jù)（p1）對(duì)BP網(wǎng)絡(luò)仿真檢驗(yàn)?zāi)Ｐ?br/>an=sim（netp1）;???????????????????????%用訓(xùn)練好的模型進(jìn)行仿真
a=mapminmax（‘reverse‘a(chǎn)ntn）;?????????%把仿真得到的數(shù)據(jù)還原為原始的數(shù)量級(jí)；
%本例因樣本容量有限使用訓(xùn)練數(shù)據(jù)進(jìn)行測(cè)試，通常必須用新鮮數(shù)據(jù)進(jìn)行測(cè)試
x=1979:2004;
newo=a（1:）;
plot（xnewo‘r-o‘xozone‘b--+‘）?%繪值公路臭氧總量對(duì)比圖
legend（‘網(wǎng)絡(luò)輸出臭氧總量‘‘實(shí)際臭氧總量‘）;
xlabel（‘年份‘）;ylabel（‘DU‘）;
error=abs（newo-ozone）/ozone;?????????%計(jì)算相對(duì)誤差
%利用訓(xùn)練好的網(wǎng)絡(luò)進(jìn)行預(yù)測(cè)
%用訓(xùn)練好的網(wǎng)絡(luò)對(duì)新數(shù)據(jù)pnew進(jìn)行預(yù)測(cè)時(shí)，也應(yīng)作相應(yīng)的處理
pnew=[0.163?0.164;0.172?0.172;0.063?0.062];??%?2005年和2006年的相關(guān)數(shù)據(jù)
pnewn=mapminmax（pnew）;????%利用原始輸入數(shù)據(jù)的歸一化參數(shù)對(duì)新數(shù)據(jù)進(jìn)行歸一化
anewn=sim（netpnewn）;?????%利用歸一化后的數(shù)據(jù)進(jìn)行仿真
anew=mapminmax（‘reverse‘a(chǎn)newntn）;??%把仿真得到的數(shù)據(jù)還原為原始的數(shù)量級(jí)

?屬性????????????大小?????日期????時(shí)間???名稱
-----------?---------??----------?-----??----
?????文件???????12673??2018-04-14?14:15??基于MATLAB的BP神經(jīng)網(wǎng)絡(luò)的臭氧總量預(yù)測(cè)\net.mat
?????文件????????2366??2018-04-14?14:26??基于MATLAB的BP神經(jīng)網(wǎng)絡(luò)的臭氧總量預(yù)測(cè)\predict_ozone.m
?????文件???????84165??2018-04-14?15:04??基于MATLAB的BP神經(jīng)網(wǎng)絡(luò)的臭氧總量預(yù)測(cè)\補(bǔ)充內(nèi)容.docx
?????目錄???????????0??2020-09-01?13:39??基于MATLAB的BP神經(jīng)網(wǎng)絡(luò)的臭氧總量預(yù)測(cè)\