I am planning to predict the temperature as a output while providing the input parameter as a current. I have uploaded my time series data data. i am training with same data set and testing on same data. but i am getting a unsatisfied result. Beforehand i have trained with this time series data set and test with another time series data set, but i did not get the result, which i was expecting. Now i am trying to Traing and Testing with same data set to find out if my Model is learning with this dataset or not, still it is not working. i am not getting satisfied result, even i am trying to train and test same data set. why? here is my Narxnet code
Data = readtable('Data.xlsx');
Current = table2array(Data(:,"I_DC")); % Input Value (Current)
Output = table2array(Data(:,"T_AGG")); % Target value (Temperature)
X_Train = tonndata(Current(1:end,:),false,false);
Y_Train = tonndata(Output(1:end),false,false);
trainFcn = 'trainlm'; %
inputDelays = 1:2;
feedbackDelays = 1:2;
hiddenLayerSize = 5;
net = narxnet(inputDelays,feedbackDelays,hiddenLayerSize,'open',trainFcn);
[x,xi,ai,t] = preparets(net,X_Train,{},Y_Train);
[net,tr] = train(net,x,t,xi,ai);
% Test the Network
[y,Xf,Af] = net(x,xi,ai);
e = gsubtract(t,y);
performance = perform(net,t,y)
% closed loop the same data for Testing multiple time step prediction
[netc,Xic,Aic] = closeloop(net,xi,ai);
view(netc)
Yc = netc(X_Test,Xic,Aic);
figure, plotregression(Y_Test,Yc)
figure, plotresponse(Y_Test,Yc)
It would be very helpful for me, if you could help me with this issue? I am not getting what i am doing wrong. or data is not appropriate to learn for Narxnet time series? Any suggestion would be helpful....Thanks in advance
