Issue using LSTM neural network "Time Series Forecasting Using Deep Learning"

Question

Ibrahim Ibrahim 2020-7-25

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/570496-issue-using-lstm-neural-network-time-series-forecasting-using-deep-learning

编辑： per isakson 2021-8-19

在 MATLAB Online 中打开

I am trying to use the LSTM regression

https://au.mathworks.com/help/deeplearning/ug/time-series-forecasting-using-deep-learning.html

The code:

%%Load Sequence Data
%Input data
S=xlsread("AVcigs.csv","AVcigs","C7:C56385");
%Output data
Pmpp=xlsread("AVcigs.csv","AVcigs","F7:F56385");
for i=1:length(Pmpp)
    if Pmpp(i) <0
        Pmpp(i)=0;
    else
        Pmpp(i)=Pmpp(i);
    end
end        
%Partition the training and test data.
numTimeStepsTrain = floor(0.7*numel(S));
dataTrain_S = S(1:numTimeStepsTrain+1);
dataTest_S = S(numTimeStepsTrain+1:end);
dataTrain_Pmpp = Pmpp(1:numTimeStepsTrain+1);
dataTest_Pmpp = Pmpp(numTimeStepsTrain+1:end);
%%Standardize Data
mu_S = mean(dataTrain_S);
sig_S = std(dataTrain_S);
dataTrainStandardized_S = (dataTrain_S - mu_S) / sig_S;
mu_Pmpp = mean(dataTrain_Pmpp);
sig_Pmpp = std(dataTrain_Pmpp);
dataTrainStandardized_Pmpp = (dataTrain_Pmpp - mu_Pmpp) / sig_Pmpp;
%%Prepare Predictors and Responses
XTrain = dataTrainStandardized_S(1:end-1);
XTrain = XTrain';
YTrain = dataTrainStandardized_Pmpp(1:end-1);
YTrain = YTrain';
for i=1:length(YTrain)
    if YTrain(i) <0
        YTrain(i)=0;
    else
        YTrain(i)=YTrain(i);
    end
end
%%Define LSTM Network Architecture
numFeatures = 1;
numResponses = 1;
numHiddenUnits = 200;
layers = [ ...
    sequenceInputLayer(numFeatures)
    lstmLayer(numHiddenUnits)
    fullyConnectedLayer(numResponses)
    regressionLayer];
options = trainingOptions('adam', ...
    'MaxEpochs',250, ...
    'GradientThreshold',1, ...
    'InitialLearnRate',0.005, ...
    'LearnRateSchedule','piecewise', ...
    'LearnRateDropPeriod',125, ...
    'LearnRateDropFactor',0.2, ...
    'Verbose',0, ...
    'Plots','training-progress');
%%Train LSTM Network
net = trainNetwork(XTrain,YTrain,layers,options);
%%Forecast Future Time Steps
%Standardize the test data using the same parameters as the training data.
dataTestStandardized_S = (dataTest_S - mu_S) / sig_S;
dataTrainStandardized_Pmpp = (dataTest_Pmpp - mu_Pmpp) / sig_Pmpp;
net = predictAndUpdateState(net,XTrain);
[net,YPred] = predictAndUpdateState(net,YTrain(end));
YPred = sig_Pmpp*YPred + mu_Pmpp;
XTest=dataTestStandardized_S(1:end-1);
XTest=XTest';
YTest = dataTrainStandardized_Pmpp(1:end-1);
YTest = YTest';
for i=1:length(YTest)
    if YTest(i) <0
        YTest(i)=0;
    else
        YTest(i)=YTest(i);
    end
end
numTimeStepsTest = numel(XTest);
for i = 2:numTimeStepsTest
    [net,YPred(:,i)] = predictAndUpdateState(net,YPred(:,i-1),'ExecutionEnvironment','gpu');
end
YTest = Pmpp(2:end);
rmse = sqrt(mean((YPred-YTest).^2))
figure(1)
plot(dataTrain_Pmpp(1:end-1))
hold on
idx = numTimeStepsTrain:(numTimeStepsTrain+numTimeStepsTest);
plot(idx,[Pmpp(numTimeStepsTrain) YPred],'.-')
hold off
xlabel("Time")
ylabel("Pmpp")
title("Forecast")
legend(["Observed" "Forecast"])
figure(2)
subplot(2,1,1)
plot(YTest)
hold on
plot(YPred,'.-')
hold off
legend(["Observed" "Forecast"])
ylabel("Pmpp")
title("Forecast")
subplot(2,1,2)
stem(YPred - YTest)
xlabel("time")
ylabel("Error")
title("RMSE = " + rmse)
%%Update Network State with Observed Values
net = resetState(net);
net = predictAndUpdateState(net,XTrain);
YPred = [];
numTimeStepsTest = numel(XTest);
for i = 1:numTimeStepsTest
    [net,YPred(:,i)] = predictAndUpdateState(net,XTest(:,i),'ExecutionEnvironment','cpu');
end
YPred = sig_Pmpp*YPred + mu_Pmpp;
rmse = sqrt(mean((YPred-YTest).^2))
figure (3)
subplot(2,1,1)
plot(YTest)
hold on
plot(YPred,'.-')
hold off
legend(["Observed" "Predicted"])
ylabel("Pmpp")
title("Forecast with Updates")
subplot(2,1,2)
stem(YPred - YTest)
xlabel("Time")
ylabel("Error")
title("RMSE = " + rmse)

I keep having the following error:

Out of memory.
Error in stem (line 104)
            h(k) = matlab.graphics.chart.primitive.Stem('Parent', parax, 'YData',matlab.graphics.chart.internal.datachk(y(:,k)),
            xdata{:},...
Error in LSTM_onefeature (line 150)
stem(YPred - YTest)