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【转】 模糊神经网络算法之MATLAB实现
2011-05-07 12:59
转载自 HYPERLINK "/share" \t "blank" 分享
最终编辑 HYPERLINK "/whutzxl" \t "blank" whutzxl
function retstr = FnnTrain(dt,ld,tt,sp) retstr=-1; %%%% 输入参数赋值开始 %%%%%%%%%%%%%%%%%%%%%%% % 方便调试程序用，程序调试时去掉这部分的注释 % dt=4;????? %学习阈值 % ld=0.05;??? %学习进度 % tt=10;????? %训练次数 % sp='data\sample.txt';??? %一个点的监测数据 %%%% 输入参数赋值结束 %%%%%%%%%%%%%%%%%%%%%%%% global recordDimention; global sampleNumber; global weightNumber; global distanceThread; global WW; global learningDegree; global epochsNumber; distanceThread=dt; learningDegree=ld; traintimes=tt; A=load(sp); ?? [Arow Acol]=size(A); %样本个数 sampleNumber=Arow; recordDimention=Acol; disp(sampleNumber); WW=A(1,:); WW=[WW [1]]; weightNumber=1; epochsNumber=1; ?? for jj=2:1:sampleNumber ????? TrainNN2(A(jj,:)); end for jt=1:traintimes-1 ????? for jt2=1:sampleNumber ????????? TrainNN2(A(jj,:)); ????? end end % 将训练结果写入权值文件 dlmwrite('data\w.dat',WW,'\t'); % % 训练子函数 % function TrainNN2(a) global recordDimention; global sampleNumber; global weightNumber; global distanceThread; global WW; global learningDegree; global epochsNumber; Ldistance=zeros(2,weightNumber); for j1=1:weightNumber ????? Ldistance(2,j1)=j1; end % %%%%%输入输出空间的模糊分割 for j2=1:weightNumber ????? Lx=0; ????? for j3=1:recordDimention ????????? Lx=Lx + (a(j3) - WW(j2,j3)) .* (a(j3) - WW(j