How to implement LSTM Time-series prediction using multi-features?

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Mohamed Nedal
Mohamed Nedal on 15 Jan 2020
Commented: Asli on 21 May 2021
Hello everyone,
I have the attached code and the attached data file here. I want to modify that code to proceed time-series prediction for 1 output using 5 inputs.
When I the training finishes I get the following error:
The prediction sequences are of feature dimension 1 but the input layer expects sequences of feature dimension 4.
Error in multi_lstmOMNI_noStand (line 110)
[net,YPred] = predictAndUpdateState(net,YTrain);
Can you please tell me how to fix it?
I appreciate your help.
Mohamed Nedal
Mohamed Nedal on 3 Jul 2020
Hi @Marcelo,
I tried to add a few lines of code to predict new future values of the target output, here's what I added:
%% Forecast the Future
net = resetState(net);
Yforecast = [];
numTimeStepsTest = numel(XTest) + 500; % to forecast new 500 steps in the future
for i = 1:numTimeStepsTest
[net, Yforecast(:,i)] = predictAndUpdateState(net, XTest(:,i), 'ExecutionEnvironment','cpu');
but I got this error:
Conversion to double from cell is not possible.
Error in LSTM_multi_motores (line 82)
[net, Yforecast(:,i)] = predictAndUpdateState(net, XTest(:,i),
Can you please tell me how to fix this part?

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Accepted Answer

Marcelo Olmedo
Marcelo Olmedo on 6 May 2020
Hello people; I found the problem; the key is in the correct loading of data as the published documents say. I attach my code and used tables so you don't have problems to run it; I upload data from excel to train and test. I do not use standardized data. The model fits quite well. Cheers
Asli on 21 May 2021
Hi Marcelo, i am really new in this topic and i am trying to predict time series of Y depending on two external variables (X1 and X2). I have two questions. (i) Why don’t you use the “predictAndUpdateState” and why do you use the “predict” statement? Is it used for time series prediction? (ii) Why are the previous y values not input into this function? Only x values are input.

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