fitsimu.m

nnToolKit 神经网络工具包是基于 MATLAB 神经网络工具箱自行开发的一组神经网络算法函数库

function retstr = FitSimu(ModelNo,NetPara,SeqData,TargetData,DataDir)
NNTWARN OFF

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%ModelNo='1';
%DataDir='.';        %表示当前目录
%NetPara(1)=11;
%NetPara(2)=3;
%NetPara(3)=50;

%NetPara(4)=1900;
%NetPara(5)=2020;
%NetPara(6)=70;
%NetPara(7)=350;

%NetPara(8)=2010;
     
%SeqData = [1900.000000000000000      1910.000000000000000      1920.000000000000000      1930.000000000000000      1940.000000000000000      1950.000000000000000      1960.000000000000000      1970.000000000000000      1980.000000000000000      1990.000000000000000      2000.000000000000000 ];
%TargetData =[    75.99500000     91.97200000    105.71100000    123.20300000    131.66900000    150.69700000    179.32300000    203.21200000    226.50500000    249.63300000    281.42200000 ];
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%保留原目录
olddir=pwd;

%进入数据所在目录
cd(DataDir);

InputDim=NetPara(1);       %样本组数
FitFact=NetPara(2);        %拟合阶数
DataNum=NetPara(3);        %拟合数据点数

MinSeqValue=NetPara(4);    %外推最小值
MaxSeqValue=NetPara(5);    %外推最大值
MinValue=NetPara(6);    %输出最小值
MaxValue=NetPara(7);    %输出最大值

FitPoint=NetPara(8);       %预测点

%读取拟合曲线系数
fcoef=fopen(sprintf('coef%s%s',ModelNo,'.dat'),'r');
[coef,count]=fscanf(fcoef,'%f',[1,inf]);
fclose(fcoef);

pz=polyval(coef,FitPoint); 
 
cd(olddir);

retstr=pz;