hello everyone..
this my problem…
i am using "nonlinear Autoregressive" for forecasting time series on Neural Time Series Tools..
I have enter my data to predicted in day periode and i have train my data..
and this simple script generated…
**************************************************************************
% Solve an Autoregression Time-Series Problem with a NAR Neural Network
% Script generated by NTSTOOL
% Created Sat Sep 08 23:46:26 EEST 2012
%
% This script assumes this variable is defined:
%% Book1 - feedback time series.
targetSeries = tonndata(Book1,false,false);% Create a Nonlinear Autoregressive Network
feedbackDelays = 1:2;hiddenLayerSize = 10;net = narnet(feedbackDelays,hiddenLayerSize);% 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.
[inputs,inputStates,layerStates,targets] = preparets(net,{},{},targetSeries);% 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,inputs,targets,inputStates,layerStates);% Test the Network
outputs = net(inputs,inputStates,layerStates);errors = gsubtract(targets,outputs);performance = perform(net,targets,outputs)% View the Network
view(net)% Plots
% Uncomment these lines to enable various plots.
%figure, plotperform(tr)
%figure, plottrainstate(tr)
%figure, plotresponse(targets,outputs)
%figure, ploterrcorr(errors)
%figure, plotinerrcorr(inputs,errors)
% 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);[xc,xic,aic,tc] = preparets(netc,{},{},targetSeries);yc = netc(xc,xic,aic);perfc = perform(net,tc,yc)% Early 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);[xs,xis,ais,ts] = preparets(nets,{},{},targetSeries);ys = nets(xs,xis,ais);closedLoopPerformance = perform(net,tc,yc)
**************************************************************************
i have run my script but the result just statistical data, not predicting
and my question…
how script to predict the next day from my Data ??
thank..
Best Answer