Time Series Forecasting Using Deep Learning in MATLAB

Question

Amin Karami 2018-5-24

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https://ww2.mathworks.cn/matlabcentral/answers/402350-time-series-forecasting-using-deep-learning-in-matlab

评论： RUDHA 2023-3-31

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 = [ ...
    sequenceInputLayer(inputSize)
    lstmLayer(numHiddenUnits)
    fullyConnectedLayer(numResponses)
    regressionLayer];
%%Training Options
opts = trainingOptions('adam', ...
    'MaxEpochs',500, ...
    'GradientThreshold',1, ...
    'InitialLearnRate',0.005, ...
    'LearnRateSchedule','piecewise', ...
    'LearnRateDropPeriod',125, ...
    'LearnRateDropFactor',0.2, ...
    'Verbose',0, ...
    'Plots','training-progress');
%%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));
end
%%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
figure
plot(data(1:numTimeStepsTrain))
hold on
idx = numTimeStepsTrain:(numTimeStepsTrain+numTimeStepsTest);
plot(idx,[data(numTimeStepsTrain) YPred],'.-')
hold off
xlabel("Month")
ylabel("Cases")
title("Forecast")
legend(["Observed" "Forecast"])
%%Compare the forecasted values with the test data
figure
subplot(2,1,1)
plot(YTest)
hold on
plot(YPred,'.-')
hold off
legend(["Observed" "Forecast"])
ylabel("Cases")
title("Forecast")
subplot(2,1,2)
stem(YPred - YTest)
xlabel("Month")
ylabel("Error")
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.

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diana haron 2020-9-27

Hi, how does your data looks like? Is it similar as the chicken pox example which is just one row with multiple columns?

RUDHA 2023-3-31

I have same problem let mw know if you fix it

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Answer 1

Abolfazl Nejatian 2018-11-23

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https://ww2.mathworks.cn/matlabcentral/answers/402350-time-series-forecasting-using-deep-learning-in-matlab#answer_348568

here is my code,

https://www.mathworks.com/matlabcentral/fileexchange/69506-time-series-prediction

this piece of code predicts time series data by use of deep learning and shallow learning algorithm.

best wish

abolfazl nejatian

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Chris P 2020-9-29

Also, are the predictions forecasting the values of multiple time steps in the future? Or are they updating the network state with the observed values rather than the predicted values?

Refer to the last two sections of this example for further details on what I am asking. I would like my network to have the ability to make predictions multiple timesteps into the future before accesing any new observed values.

Abolfazl Nejatian 2020-12-10

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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Answer 2

Abolfazl Nejatian 2018-6-8

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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.

this is my mail, abolfazl.nejatian@gmail.com

with best wishes

Nejatian

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diana haron 2020-9-27

Hi,

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.

Faris 2022-12-24

Dear Abolfazl Nejatian,

I sent an email including an equation at the same object and your answer will help me to implement my study

Regards

Faris

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Answer 3

xiaowei wang 2018-11-20

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It happened to me as well. I think it is just trick that no one wants to mention...

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Answer 4

qizal ashfaq 2019-9-14

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https://ww2.mathworks.cn/matlabcentral/answers/402350-time-series-forecasting-using-deep-learning-in-matlab#answer_391837

编辑：qizal ashfaq 2019-9-14

How to link this code with deep designer toolbox?I am talking about this.How this model works with that code?

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ANGELIN ANTHONY 2020-3-21

did u get this answer??

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Answer 5

qizal ashfaq 2019-9-14

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Is this code valid for only one row ?

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Chris P 2020-9-30

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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