univariate time series prediction with artificial neural network

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.

[Kevin Chng]

refer to the link : https://www.mathworks.com/help/deeplearning/ref/narnet.html. Replace the dataset with your dataset.

[Osman Yakubu]

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]

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

Answer 1

[Kevin Chng]

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));

[Parvathy ravindranath]

Can any one help me solve timeforcasting using deep learning in OCTAVE