MATLAB: How to do a production forecast with GA-NN hybrid in MATLAB

Deep Learning Toolboxforecastinggenetic algorithmneural networkprediction

I currently have an undergraduate thesis which requires me to utilize a hybrid of GA and NN. I am supposed to use this to forecast future production values. I have gone through several forums and documentations and I don’t seem to be able to correctly implement the GA-NN hybrid.
I would like to use the GA to optimize the NN weight and bias. I got a neural network with the NN Time Series toolbox with 20 hidden neurons and 4 time delays to be a good network fit ( _ I used NAR and not NARX…hope thats ok? _ )
My data is given under three parameters with about 2100 timesteps ,I want to predict their future values with the NN and optimize the weights and biases with GA

Best Answer

You have a single I = O = 3 dimensional series with N = 2100 timesteps. You have successfully designed a NARNET with NFD = 4 feedback delays and H = 20 hidden neurons. This results in
 Nw = net.numWeightElements = (NFD*O+1)*H+(H+1)*O = 323
Now you wish to design a net using GA. Is that correct?
Are you able to obtain acceptable designs with H < 20 ? ... The fewer, the better.
The NNToolbox does not have a genetic algorithm. However, there are posts that deal with GA designs for a non-timeseries net. Try searching the NEWSGROUP and ANSWERS using
 neural genetic
or
 neural ga
Hope this helps.
Greg
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