Where is output for this net ??

Im new in matlab now is day 2 i use matlab..

i use input 100 time series data on this.

i want get output from net at time 96 97 98 99 100 & predicted data 101 102 103 104 **4 before and 4 after 100

here the code

% Solve an Autoregression Problem with External Input with a NARX Neural Network
% Script generated by Neural Time Series app
% Created 12-May-2016 20:10:18
%
% This script assumes these variables are defined:
%
%   TestIn - input time series.
%   TestOut - feedback time series.

clear;
load TestIn.csv;
load TestOut.csv;

X = tonndata(TestIn,false,false);
T = tonndata(TestOut,false,false);

% Choose a Training Function
% For a list of all training functions type: help nntrain
% 'trainlm' is usually fastest.
% 'trainbr' takes longer but may be better for challenging problems.
% 'trainscg' uses less memory. Suitable in low memory situations.
trainFcn = 'trainlm';  % Levenberg-Marquardt backpropagation.

% Create a Nonlinear Autoregressive Network with External Input
inputDelays = 1:2;
feedbackDelays = 1:2;
hiddenLayerSize = 10;
net = narxnet(inputDelays,feedbackDelays,hiddenLayerSize,'open',trainFcn);

% Prepare the Data for Training and Simulation
% The function PREPARETS prepares timeseries data for a particular network,
% shifting time by the minimum amount to fill input states and layer
% states. Using PREPARETS allows you to keep your original time series data
% unchanged, while easily customizing it for networks with differing
% numbers of delays, with open loop or closed loop feedback modes.
[x,xi,ai,t] = preparets(net,X,{},T);

% Setup Division of Data for Training, Validation, Testing
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;

% Train the Network
[net,tr] = train(net,x,t,xi,ai);

% Test the Network
y = net(x,xi,ai);
e = gsubtract(t,y);
performance = perform(net,t,y);

% View the Network
view(net)

% Plots
% Uncomment these lines to enable various 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
% Use this network to do multi-step prediction.
% The function CLOSELOOP replaces the feedback input with a direct
% connection from the outout layer.
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
% For some applications it helps to get the prediction a timestep early.
% The original network returns predicted y(t+1) at the same time it is
% given y(t+1). For some applications such as decision making, it would
% help to have predicted y(t+1) once y(t) is available, but before the
% actual y(t+1) occurs. The network can be made to return its output a
% timestep early by removing one delay so that its minimal tap delay is now
% 0 instead of 1. The new network returns the same outputs as the original
% network, but outputs are shifted left one timestep.
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);

please help me , i really need your help. what code to get output as i describe before and write it to external output csv file ?

thank you.

Answer 1

[Staffan]

Dear Bridget,

Have you only used Matlab for two days? Impressive!

I am also working with predictions using narxnet and narnet, I can't solve your question completely but I would like to advice you to have a look at the following newsgroup threads:

http://se.mathworks.com/matlabcentral/newsreader/view_thread/341175?s_tid=srchtitle https://se.mathworks.com/matlabcentral/newsreader/view_thread/345189

Wish you the best, (if you have the time,) please share your progress. I have a few of my own questions in progress, this one might be interesting for you to follow:

https://se.mathworks.com/matlabcentral/answers/276269-narx-network-for-multi-step-prediction-possible-to-use-extrapolation-time-vectors

Regards

Staffan

[Staffan]

When you have created the vector with the predicted values, just use

http://se.mathworks.com/help/matlab/ref/dlmwrite.html or

http://se.mathworks.com/help/matlab/ref/xlswrite.html

...to write to file.

Regards

Staffan