univariate time series prediction with artificial neural network
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Osman Yakubu
le 26 Déc 2018
Commenté : Parvathy ravindranath
le 25 Déc 2020
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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Kevin Chng
le 4 Jan 2019
Modifié(e) : madhan ravi
le 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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Kevin Chng
le 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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Parvathy ravindranath
le 25 Déc 2020
Can any one help me solve timeforcasting using deep learning in OCTAVE
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