How to make prediction from a trained NARX neural network?

Question

Lavnish Gupta 2020-8-16

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/580179-how-to-make-prediction-from-a-trained-narx-neural-network

编辑： georg enyew 2021-2-5

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
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)
% Step-Ahead Prediction Network
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);
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?