Neural network time series prediction with ANN Toolbox
Hello all,
I know this question has been asked several times but I would still want to know. I am a beginner in Matlab and I have been experimenting with ANN toolbox. I have managed to train a NARX neural network with a set of input and target values and now an advanced script is generated. My training input is a 200 day dataset of 5 days each that is it takes input of 5 days and predicts the 6th day.
My question is, how do I feed new inputs to this network to make predictions? That is, now, I wanna just take 5 previous including the current day and predict the value for tomorrow? How do I pass this 5 day input set and predict the target?
NOTE:-
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For NARNET and NARXNET to be useful, target input values used in the openloop (OL) design have to be replaced by feedback from the output. This is accomplished via the CLOSELOOP (CL) command.
Very often, however, the resulting CL configuration is either not as accurate or is completely useless.
UNFORTUNATELY THERE IS NOTHING IN THE help OR doc DOCUMENTATION ABOUT THIS.
I have been struggling to devise a successful technique for improving the accuracy of CL designs. If you search both the NEWSREADER and ANSWERS with
greg closeloopyou will see my efforts to resolve this issue.
All I can recommend at this time is the following
1. Try to obtain the lowest error rate possible with as few delays and hidden nodes as possible using the OL configuration. The fewer weights you have to estimate, the higher your probability of success.
2. The default values ID = 1:2, FD = 1:2, H = 10 are very often inadequate. Nevertheless, since you may have to make tens or even hundreds of OL designs before obtaining a successful CL design, I suggest that you ALWAYS start with the defaults.
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