Airline_passanger_time_series

The repository is the implementation for predicting the time series flight data for a airlines. The prediction results mentioned here is based on the multistep forecasting with LSTM, Simple RNN, GRU and Autoregressive model

Note : This repository illustrates the difference between the Sigle Step and Multi Step Time Series Forecasting

The analysis of prediction from time series is presented below. And from the given examination it is evident that Autoregressive Model performance dominates the LSTM, GRU and Simple RNN in this case

Simple RNN (Multi Step Forecasting)

Simple RNN (Single Step Forecasting)

LSTM (Multi Step Forecasting)

LSTM (Single Step Forecasting)

GRU (Multi Step Forecasting)

GRU (Single Step Forecasting)

Autoregressive (Multi Step Forecasting)

Autoregressive (Single Step Forecasting)