MATLAB Answers

TDNN multistep prediction with unknown future data for the target

2 ビュー (過去 30 日間)
Hugo Mendonça
Hugo Mendonça 2015 年 11 月 16 日
コメント済み: Hugo Mendonça 2015 年 11 月 17 日
Hi, everyone!
I am a little bit confused how to use a time delay neural network for multistep ahead prediction.
By my system characteristics, I must use a time delay neural network and not others. So, from previous measurement, I know the input and target time series, where:
Xdata(1:500) (input)
Tdata(1:500) (target)
Let's create the neural network:
net = timedelaynet(1:10,10);
[Xs,Xi,Ai,Ts] = preparets(net,Xdata,Tdata);
net = train(net,Xs,Ts,Xi,Ai);
I can clearly understand all the procedure until this point. However, I do not know how to prepare the new input data to be predicted and to use the net. I mean, in the future, I will just know the input data. So, how I could predict it? For example:
Y1 = net(Xnew1,Xi,Ai);
Ans further, for a new data:
Y2 = net(Xnew2,Xi,Ai);
Would it be the same? With the same Xi and Ai?
Thanks for helping!


Greg Heath
Greg Heath 2015 年 11 月 17 日
In general, PREPARETS will yield the correct inputs. However, for TIMEDELAYNET, just use common sense:
Ai = {} % There is no feedback
Xi = Xnew2(:,1:10);
Xnew2s = Xnew2(:, 10:end);
Hope this helps.
Thank you for formally accepting my answer
PS: See my tutorials
  1 件のコメント
Hugo Mendonça
Hugo Mendonça 2015 年 11 月 17 日
Thank you, Greg!
As I have seen, you are always helpful!
BTW, very god tutorial about NARNET. Maybe, in a very close future, I might use NARNET.
Thank you again!


その他の回答 (0 件)

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by