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univariate time series prediction with artificial neural network

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Osman Yakubu
Osman Yakubu on 26 Dec 2018
Edited: madhan ravi on 4 Jan 2019
I am new to MATLAB and time series and need help. I have a two column data of electricity consumption (Date, Consumption in kWd). I need a MATLAB code or procedure to enable me predict consumptions. I have 154 days of data and I want to prediction each consumption and plot it on a graph (actual, predicted) and calculate the root mean squared error. Thanks.

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Osman Yakubu
Osman Yakubu on 27 Dec 2018
Thanks for your reply, it was really helpful. How do I plot the predicted and actual values? I also need the RMSE.
Please help.
Thanks
Kevin Chng
Kevin Chng on 4 Jan 2019
Sorry for my late reply,
(Actual - Predicted) % Errors
(Actual - Predicted).^2 % Squared Error
mean((Actual - Predicted).^2) % Mean Squared Error
RMSE = sqrt(mean((Actual - Predicted).^2)); % Root Mean Squared Error

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Accepted Answer

Kevin Chng
Kevin Chng on 4 Jan 2019
refer to the link : https://www.mathworks.com/help/deeplearning/ref/narnet.html. Replace the dataset with your dataset.
For Calculating RMSE,
RMSE = sqrt(mean((Actual - Predicted).^2));

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