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How to make prediction from a trained NARX neural network?

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Lavnish Gupta
Lavnish Gupta am 16 Aug. 2020
Bearbeitet: georg enyew am 5 Feb. 2021
I have got the following code from a research paper which implements a NARX Neural network which trains the network using one exogenous input:
% Anp – The input time series.
% Adtds – The feedback time series.
X = tonndata(Anp,true,false);
T = tonndata(Adtds,true,false);
% 'trainlm' training function is chosen
trainFcn = 'trainlm'; % Levenberg-Marquardt backpropagation.
% Model creation
inputDelays = 1:2;
feedbackDelays = 1:2;
hiddenLayerSize = 10;
net = narxnet(inputDelays,feedbackDelays,hiddenLayerSize,'open',trainFcn);
% Training and simulation data preparation
[x,xi,ai,t] = preparets(net,X,{},T);
% Divide the data for training, validation and testing
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 0/100;
net.divideParam.testRatio = 30/100;
net.divideFcn = 'divideblock';
% Network training
[net,tr] = train(net,x,t,xi,ai);
% Network testing
y = net(x,xi,ai);
e = gsubtract(t,y);
performance = perform(net,t,y)
% Network view
% Plots
figure, plotperform(tr)
figure, plottrainstate(tr)
figure, ploterrhist(e)
figure, plotregression(t,y)
figure, plotresponse(t,y)
figure, ploterrcorr(e)
figure, plotinerrcorr(x,e)
% Closed Loop Network
netc = closeloop(net); = [ ' - Closed Loop'];
[xc,xic,aic,tc] = preparets(netc,X,{},T);
yc = netc(xc,xic,aic);
closedLoopPerformance = perform(net,tc,yc)
% Step-Ahead Prediction Network
nets = removedelay(net); = [ ' - Predict One Step Ahead'];
[xs,xis,ais,ts] = preparets(nets,X,{},T);
ys = nets(xs,xis,ais);
stepAheadPerformance = perform(nets,ts,ys)
I am able to understand that it is training the network. But i am not able to understand how to predict output for new input data which the network has never seen before. I tried using net(input_Series) but it gives me the error that inputs are not sufficient. Could anyone please help me out?

Antworten (1)

Greg Heath
Greg Heath am 17 Aug. 2020
You forgot to include the intial conditions:
yz = nets(xz,xiz,aiz);
Thank you for formally accepting my answer
  2 Kommentare
Lavnish Gupta
Lavnish Gupta am 17 Aug. 2020
Dear Greg,
I tried using the following (grtest is my input for which I want output):
But again I am getting the error: "Number of inputs does not match net.numInputs."
What to use in place of xiz and aiz? xc,aic or xs,ais?
georg enyew
georg enyew am 5 Feb. 2021
Bearbeitet: georg enyew am 5 Feb. 2021
this problem happen to the same to me? how it could be? any one who help us i appreciated.

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