I am trying to develop a neural network which predicts an output based on 4 inputs, one of which is the output of the previous step. Currently I am just using a standard function fitting network (not a time-series prediction).
The neural network works really well (r squared approx. 0.98 - 0.99) when the output of the previous step is given independent of the neural network result.
However, when I use the neural network predicted output as the input to the next prediction, the neural network result is virtually worthless. Also, the results differ greatly every time I re-train the network - i.e. it seems the results are very dependent on the initial weights.
I am not sure if this is a problem of overtraining? Any help would be greatly appreciated.
For the fitting net I assume you are using
x =[input(:,2:end); target(:,1:end-1)];
t = target(:,2:end);
size(input) = ?
size(target) = ?
numHidden = ?
net.divideParam = ?
R2trn ~ 0.985
R2val = ?
R2tst = ?
How is the timeseries net configured? Please include code.
Hope this helps.