How to use the trained network to predict future values?

17 ビュー (過去 30 日間)
Dmitrii
Dmitrii 2013 年 10 月 15 日
コメント済み: MUKESH KUMAR 2020 年 5 月 6 日
Hi! I have created neural network using nnstart: NAR; d = 10. After training I saved network in workspase (name: net). Now can I use this trained network to predict future 10 values?

採用された回答

Greg Heath
Greg Heath 2013 年 10 月 17 日
If the new data immediately follows the data used to design and test the net, the following syntax should have been used
[ net tr Ys Es Xsf Asf ] = train(net,Xs,Ts,Xi,Ai);
Xinew = Xsf; Ainew = Asf;
Ysnew = net(Xsnew,Xinew,Ainew);
Otherwise
Xinew = Xnew(:,1:d); Xsnew = Xnew(:,d+1:end)
but Ainew is not known.
I would try the mean of the previously used test target data rather than use zeros. Perhaps several designs using values in the interval [mean-stdv,mean+stdv] would be useful.
Hope this helps.
Thank you for formally accepting my answer
Greg
  1 件のコメント
Greg Heath
Greg Heath 2013 年 10 月 23 日
This is similar to asking for the solution of a 2nd order differential equation when you know the forcing function but don't know the initial conditions.

サインインしてコメントする。

その他の回答 (1 件)

Jonathan LeSage
Jonathan LeSage 2013 年 10 月 15 日
Once you have trained a network, you can use your net as a function. In your case, the outputs of the neural network could be found via outputs = net(inputs).
Here is some additional documentation that you might find helpful:
Hope this helps and best of luck!
  1 件のコメント
MUKESH KUMAR
MUKESH KUMAR 2020 年 5 月 6 日
showing error,
"Error using network/sim (line 266)
Number of inputs does not match net.numInputs."

サインインしてコメントする。

カテゴリ

Help Center および File ExchangeSequence and Numeric Feature Data Workflows についてさらに検索

Community Treasure Hunt

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

Start Hunting!

Translated by