How to do a production forecast with GA-NN hybrid in MATLAB
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Olumide Oladoyin
el 8 de Mayo de 2015
Comentada: Olumide Oladoyin
el 12 de Mayo de 2015
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
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Greg Heath
el 9 de Mayo de 2015
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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Greg Heath
el 11 de Mayo de 2015
Editada: Greg Heath
el 11 de Mayo de 2015
TO DUPLICATE PREVIOUS RUNS YOU HAVE TO INITIALIZE THE RNG TO THE SAME INITIAL VALUE. FOR EXAMPLES SEARCH THE NEWSGROUP AND ANSWERS USING ONE OR MORE OF
GREG RNG(0)
GREG RNG(4151941)
GREG RNG('DEFAULT')
INSTEAD OF THE HISTOGRAM, I JUST LOOK AT THE NORMALIZED MEAN-SQUARE-ERROR AND ASSOCIATED RSQUARE (Fraction of target variance modeled by the net)
NMSE = mse(target-output)/mean(var(target',1))
R2 = 1-NMSE
Hope this helps
Greg
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