How to do Single step ahead prediction of Lorenz chaotic time series using Feed Forward Backpropogation Neural Network.
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I want to do one step ahead prediction of lorenz chaotic time series data with 3*20000 data.
how to do that.
It will be also help full to get any example to perform one step ahead prediction of chaotic time series using feed forward neural network with delta learning rule.
thanks in advance.
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Accepted Answer
Greg Heath
on 28 Mar 2014
Edited: Greg Heath
on 4 Apr 2014
d = 1
x = f(:,1:N-d);
t = f(:,1+d:N);
rng(0)
H =10 % default
net = fitnet(H);
net.divideFcn = 'dividetrain';
...
help fitnet
doc fitnet
Search using
greg fitnet Ntrials % to find best of multiple designs
2 Comments
Greg Heath
on 4 Apr 2014
Edited: Greg Heath
on 4 Apr 2014
Incorrect.
There is only 1 3-D series. Therefore, the only difference between input and target is a shift in the data. When the input is f(:,1), the predicted output should be f(:,1+d). Therefore, the correct answer is
x =f(:,1:N-d); t = f(:,1+d:N);
I will make the appropriate correction in my accepted answer.
Hope this helps.
Greg
More Answers (1)
Greg Heath
on 24 Mar 2014
Edited: Greg Heath
on 24 Mar 2014
help narnet
doc narnet
For practice
help nndatasets
Also search the NEWSGROUP and ANSWERS using
greg narnet
Hope this helps
Thank you for formally accepting my answer
Greg
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