Time Series Forecasting Using Deep Learning in MATLAB

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Amin Karami
Amin Karami on 24 May 2018
Commented: Abolfazl Nejatian on 10 Dec 2020
I am using the time series forecasting sample from MathWorks in: Time Series Forecasting Using Deep Learning
I only changed the dataset and ran the algorithm. Surprisingly, the algorithm is not working good with my dataset and generates a line as forecast as follows:
I am really confused and I cannot understand the reason behind that. I might be need to tune parameters in the algorithm that I am not aware on that. The code I am using is:
%%Load Data
%data = chickenpox_dataset;
%data = [data{:}];
data = xlsread('data.xlsx');
data = data';
%%Divide Data: Training and Testing
numTimeStepsTrain = floor(0.7*numel(data));
XTrain = data(1:numTimeStepsTrain);
YTrain = data(2:numTimeStepsTrain+1);
XTest = data(numTimeStepsTrain+1:end-1);
YTest = data(numTimeStepsTrain+2:end);
%%Standardize Data
mu = mean(XTrain);
sig = std(XTrain);
XTrain = (XTrain - mu) / sig;
YTrain = (YTrain - mu) / sig;
XTest = (XTest - mu) / sig;
%%Define LSTM Network
inputSize = 1;
numResponses = 1;
numHiddenUnits = 500;
layers = [ ...
%%Training Options
opts = trainingOptions('adam', ...
'MaxEpochs',500, ...
'GradientThreshold',1, ...
'InitialLearnRate',0.005, ...
'LearnRateSchedule','piecewise', ...
'LearnRateDropPeriod',125, ...
'LearnRateDropFactor',0.2, ...
'Verbose',0, ...
%%Train Network
net = trainNetwork(XTrain,YTrain,layers,opts);
%%Forecast Future Time Steps
net = predictAndUpdateState(net,XTrain);
[net,YPred] = predictAndUpdateState(net,YTrain(end));
numTimeStepsTest = numel(XTest);
for i = 2:numTimeStepsTest
[net,YPred(1,i)] = predictAndUpdateState(net,YPred(i-1));
%%Unstandardize the predictions using mu and sig calculated earlier.
YPred = sig*YPred + mu;
%%RMSE and MAE Calculation
rmse = sqrt(mean((YPred-YTest).^2))
MAE = mae(YPred-YTest)
%%Plot results
hold on
idx = numTimeStepsTrain:(numTimeStepsTrain+numTimeStepsTest);
plot(idx,[data(numTimeStepsTrain) YPred],'.-')
hold off
legend(["Observed" "Forecast"])
%%Compare the forecasted values with the test data
hold on
hold off
legend(["Observed" "Forecast"])
stem(YPred - YTest)
title("RMSE = " + rmse)
And the data.xlsx is in: https://www.dropbox.com/s/vv1apug7iqlocu1/data.xlsx?dl=1
I really appreciate if there is any help.
diana haron
diana haron on 27 Sep 2020
Hi, how does your data looks like? Is it similar as the chicken pox example which is just one row with multiple columns?

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Answers (6)

Abolfazl Nejatian
Abolfazl Nejatian on 23 Nov 2018
here is my code,
this piece of code predicts time series data by use of deep learning and shallow learning algorithm.
best wish
abolfazl nejatian
Abolfazl Nejatian
Abolfazl Nejatian on 10 Dec 2020
Dear Chris,
i have updated my code.
the updated things are listed as below:
time-series prediction with simple CNN network added
time series prediction with a ResNet50 added.
forecasting the future of data added to the code, and also some minor bugs were fixed.

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Abolfazl Nejatian
Abolfazl Nejatian on 8 Jun 2018
dear Amin well I think this might be happened because of your dataset Size, I mean you should use a big one Set or a smaller network. I'm working on time series prediction too in Forex; and I'm disagree with this kind of making input data and target data with one step delay!
if you have any question don't hastate to ask me.
with best wishes
diana haron
diana haron on 27 Sep 2020
Im currently working on something based on this chicken pox example. The data for this example is only 1 row and multiple columns. I am trying to modify it for my data sets which comprises of multple rows and multiple columns. Any chance you know how to do it? Much appreciated.

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xiaowei wang
xiaowei wang on 20 Nov 2018
It happened to me as well. I think it is just trick that no one wants to mention...

qizal ashfaq
qizal ashfaq on 14 Sep 2019
Edited: qizal ashfaq on 14 Sep 2019
How to link this code with deep designer toolbox?I am talking about this.How this model works with that code?Capture.JPG

qizal ashfaq
qizal ashfaq on 14 Sep 2019
Is this code valid for only one row ?
  1 Comment
Chris P
Chris P on 30 Sep 2020
Same question. I'm wondering if I can use an external time series in addition to the time series of interest. I want these two time series inputs to have delays as well.
How should we format the input matrix? 2xn cell where n is the number of time samples in the series? 1xn cell where each cell is dimension 2xd where d is the number of delays?

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