資源簡介
本代碼主要利用MATLAB工具進行模糊神經網絡的預測算法的仿真,實現水質評價的模擬

代碼片段和文件信息
web?browser?http://www.ilovematlab.cn/thread-65145-1-1.html
%%?清空環境變量
clc
clear
%%?參數初始化
xite=0.001;
alfa=0.05;
%網絡節點
I=6;???%輸入節點數
M=12;??%隱含節點數
O=1;???%輸出節點數
%系數初始化
p0=0.3*ones(M1);p0_1=p0;p0_2=p0_1;
p1=0.3*ones(M1);p1_1=p1;p1_2=p1_1;
p2=0.3*ones(M1);p2_1=p2;p2_2=p2_1;
p3=0.3*ones(M1);p3_1=p3;p3_2=p3_1;
p4=0.3*ones(M1);p4_1=p4;p4_2=p4_1;
p5=0.3*ones(M1);p5_1=p5;p5_2=p5_1;
p6=0.3*ones(M1);p6_1=p6;p6_2=p6_1;
%參數初始化
c=1+rands(MI);c_1=c;c_2=c_1;
b=1+rands(MI);b_1=b;b_2=b_1;
maxgen=100;?%進化次數
%網絡測試數據,并對數據歸一化
load?data1?input_train?output_train?input_test?output_test
%選連樣本輸入輸出數據歸一化
[inputninputps]=mapminmax(input_train);
[outputnoutputps]=mapminmax(output_train);
[nm]=size(input_train);
%%?網絡訓練
%循環開始,進化網絡
for?iii=1:maxgen
????iii
????for?k=1:m????????
????????x=inputn(:k);
????????
????????%輸出層結算
????????for?i=1:I
????????????for?j=1:M
????????????????u(ij)=exp(-(x(i)-c(ji))^2/b(ji));
????????????end
????????end
????????
????????%模糊規則計算
????????for?i=1:M
????????????w(i)=u(1i)*u(2i)*u(3i)*u(4i)*u(5i)*u(6i);
????????end????
????????addw=sum(w);
????????
????????for?i=1:M
????????????yi(i)=p0_1(i)+p1_1(i)*x(1)+p2_1(i)*x(2)+p3_1(i)*x(3)+p4_1(i)*x(4)+p5_1(i)*x(5)+p6_1(i)*x(6);
????????end
????????
????????addyw=yi*w‘;
????????%網絡預測計算
????????yn(k)=addyw/addw;
????????e(k)=outputn(k)-yn(k);
????????
????????%計算p的變化值
????????d_p=zeros(M1);
????????d_p=xite*e(k)*w./addw;
????????d_p=d_p‘;
????????
????????%計算b變化值
????????d_b=0*b_1;
????????for?i=1:M
????????????for?j=1:I
????????????????d_b(ij)=xite*e(k)*(yi(i)*addw-addyw)*(x(j)-c(ij))^2*w(i)/(b(ij)^2*addw^2);
????????????end
????????end??
????????
????????%更新c變化值
????????for?i=1:M
????????????for?j=1:I
????????????????d_c(ij)=xite*e(k)*(yi(i)*addw-addyw)*2*(x(j)-c(ij))*w(i)/(b(ij)*addw^2);
????????????end
????????end
????????
????????p0=p0_1+?d_p+alfa*(p0_1-p0_2);
????????p1=p1_1+?d_p*x(1)+alfa*(p1_1-p1_2);
????????p2=p2_1+?d_p*x(2)+alfa*(p2_1-p2_2);
????????p3=p3_1+?d_p*x(3)+alfa*(p3_1-p3_2);
????????p4=p4_1+?d_p*x(4)+alfa*(p4_1-p4_2);
????????p5=p5_1+?d_p*x(5)+alfa*(p5_1-p5_2);
????????p6=p6_1+?d_p*x(6)+alfa*(p6_1-p6_2);
????????????
????????b=b_1+d_b+alfa*(b_1-b_2);??????
????????c=c_1+d_c+alfa*(c_1-c_2);
???
????????p0_2=p0_1;p0_1=p0;
????????p1_2=p1_1;p1_1=p1;
????????p2_2=p2_1;p2_1=p2;
????????p3_2=p3_1;p3_1=p3;
????????p4_2=p4_1;p4_1=p4;
????????p5_2=p5_1;p5_1=p5;
????????p6_2=p6_1;p6_1=p6;
????????c_2=c_1;c_1=c;???
????????b_2=b_1;b_1=b;
????????
????end???
????E(iii)=sum(abs(e));
end
figure(1);
plot(outputn‘r‘)
hold?on
plot(yn‘b‘)
hold?on
plot(outputn-yn‘g‘);
legend(‘實際輸出‘‘預測輸出‘‘誤差‘‘fontsize‘12)
title(‘訓練數據預測‘‘fontsize‘12)
xlabel(‘樣本序號‘‘fontsize‘12)
ylabel(‘水質等級‘‘fontsize‘12)
%%?網絡預測
%數據歸一化
inputn_test=mapminmax(‘apply‘input_testinputps);
[nm]=size(inputn_test)
for?k=1:m
????x=inputn_test(:k);
?????????
?????%計算
?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件???????9939??2009-10-02?09:48??案例24?模糊神經網絡的預測算法-嘉陵江水質評價\data1.mat
?????文件???????1954??2009-10-22?21:51??案例24?模糊神經網絡的預測算法-嘉陵江水質評價\data2.mat
?????文件???????7911??2010-02-02?12:08??案例24?模糊神經網絡的預測算法-嘉陵江水質評價\FuzzyNet.m
?????目錄??????????0??2018-08-07?18:28??案例24?模糊神經網絡的預測算法-嘉陵江水質評價
-----------?---------??----------?-----??----
????????????????19804????????????????????4
- 上一篇:灰色神經網絡的預測算法—訂單需求預測
- 下一篇:MATLAB車牌識別系統設計+圖片庫
評論
共有 條評論