MATLAB: Testing neural network’s forecasting ability

Deep Learning Toolboxnarxneural networktime series

Hello,
I'm quite new to neural networks, but I'm currently using them to forecast demand per month of a production company. I've build a neural network using the nnstart command and I chose the time series option. The network building, testing and validation is working great, and I can plot a graph of the outcomes of the ANN as well as the "feedback" matrix, which contains the true values. However, I want to test the forecasting abilities by letting the network predict new values WITHOUT RE-TRAINING the network!
I've tried certain things already, but I just cannot get it to work yet. Does anyone have a solution for my problem? In short:
– I built a network, and tested it with data from 3 years
– I want to see how the network forecasts the first 6 months of the 4th year, data that is not included in the training data
Thanks in advance, as I said I'm quite new to Neural Networks so maybe the solution is very easy.

Best Answer

Your code works on the dataset in the documentation
 help narnet
 doc  narnet
However, I did not try it on any of the other NARNET example datasets:
 help nndatasets
 doc nndatasets
I can only quote my general approach :
a. Test code on one or more a MATLAB example datasets
b. Use your data to obtain the best openloop performance of multiple (>=10) designs
c. If closing the loop sufficiently degrades performance, then train netc.
Hope this helps
Thank you for formally accepting my answer
Greg
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