how to define the size of feedback delays and number of hidden layer in narnet ?

Hello

I am using NN to predict a single time series. My code is

targetSeries = tonndata(T,false,false);

% Create a Nonlinear Autoregressive Network
feedbackDelays = 1:20;
hiddenLayerSize = 5;
net = narnet(feedbackDelays,hiddenLayerSize);

% Prepare the Data for Training and Simulation
[inputs,inputStates,layerStates,targets] = preparets(net,{},{},targetSeries);

% Setup Division of Data for Training, Validation, Testing
% For a list of all data division functions type: help nndivide
net.divideFcn = 'divideblock';  % Divide data block
net.divideMode = 'time';  % Divide up every value
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;

% Train the Network
[net,tr] = train(net,inputs,targets,inputStates,layerStates);

netc = closeloop(net);

N=240; % multistep ahead
NetworkInput=targetSeries;
for i=1:N;
    [xc,xic,aic,tc]=preparets(netc,{},{},NetworkInput);
    yc=netc(xc,xic,aic);
    NetworkInput(1,end+1)=yc(1,end);
end

My time series is a quasi-periodic signal with a main peaks near 115 time units (with a slower modulation of the successive peaks). My idea is to perform cross-validation to test the impacts of feedbackDelays and hiddenlayerSize, but are they objective methods to define these parameters ? Another question : is it possible to use narnet to forecast a non-linear trend ?

Thank you in advance

Vincent

Answer 1

[Greg Heath]

Estimate the significant autocorrelation lags using nncorr or fft.

Estimate the number of hidden nodes by trial and error.

Search using

 greg nncorr narnet Ntrials