# How to make prediction from a trained NARX neural network?

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Lavnish Gupta on 16 Aug 2020
Edited: georg enyew on 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);
% '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
view(net)
% 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);
netc.name = [net.name ' - Closed Loop'];
view(netc)
[xc,xic,aic,tc] = preparets(netc,X,{},T);
yc = netc(xc,xic,aic);
closedLoopPerformance = perform(net,tc,yc)
nets = removedelay(net);
nets.name = [net.name ' - Predict One Step Ahead'];
view(nets)
[xs,xis,ais,ts] = preparets(nets,X,{},T);
ys = nets(xs,xis,ais);
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?

Greg Heath on 17 Aug 2020
You forgot to include the intial conditions:
yz = nets(xz,xiz,aiz);
Thank you for formally accepting my answer
Greg
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georg enyew on 5 Feb 2021
this problem happen to the same to me? how it could be? any one who help us i appreciated.