Finally i wrote this code for wind speed prediction with 3 parameters, why does my code has different prediction for the same dataset on each run?
1 Ansicht (letzte 30 Tage)
Ältere Kommentare anzeigen
load('input.mat');
X = tonndata(inputData(:,(1:3)),false,false);
T = tonndata(inputData(:,4),false,false);
N = 100; % Multi-step ahead prediction
inputSeries = X(1:end);
targetSeries = T(1:end);
inputSeriesVal = X(end-N+1:end);
targetSeriesVal = T(end-N+1:end);
delay = 1; %one hour
neuronsHiddenLayer = 10;
% Network Creation
net = narxnet(1:delay,1:delay,neuronsHiddenLayer);
[Xs,Xi,Ai,Ts] = preparets(net,inputSeries,{},targetSeries);
net = train(net,Xs,Ts,Xi,Ai);
view(net)
Y = net(Xs,Xi,Ai);
% Performance for the series-parallel implementation, only
% one-step-ahead prediction
perf = perform(net,Ts,Y);
[Xs1,Xio,Aio] = preparets(net,inputSeries(1:end-delay),{},targetSeries(1:end-delay));
[Y1,Xfo,Afo] = net(Xs1,Xio,Aio);
[netc,Xic,Aic] = closeloop(net,Xfo,Afo);
[yPred,Xfc,Afc] = netc(inputSeriesVal,Xic,Aic);
multiStepPerformance = perform(net,yPred,targetSeriesVal);
view(netc)
figure;
plot([cell2mat(targetSeries),nan(1,N);
nan(1,length(targetSeries)),cell2mat(yPred);]')
legend('Original Targets','Network Predictions')
0 Kommentare
Antworten (0)
Siehe auch
Kategorien
Mehr zu Parallel and Cloud finden Sie in Help Center und File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!