Finally we conclude that we RNN is the best time series model for this dataset because we got the accurate result and it can be used for deep learning analysis.

Thanks for all your appreciations jury members. The approaches which we would recommend to remove seasonality from time-series is Seasonal ARIMA( Auto regressive Integrated Moving Average models . Seasonal difference is a crude form of additive seasonal adjustment: the “index” which is subtracted from each value of the time series is simply the value that was observed in the same season for one year. Seasonal Autoregressive Integrated Moving Average (SARIMA) models can satisfactorily describe time series that exhibit non-stationary behaviors both within and across seasons.