Paper Title
Flight Delay Prediction Based on Meteorological Factors using Deep Learning Models

Aviation industry is one of the largest industries in the world. Delays caused in these services are not only an inconvenience to the passengers but also tend to result in huge damages for the airlines. When delays occur, it brings uncertainty into the passenger’s arrival time. Authorizing conventional approaches and analysis techniques does not guarantee the accuracy of the prediction. This research work is to predict the flight delay occurring due to meteorological factors in both USA and Indian aviation by employing deep learning algorithms. The research is carried out using a flight delay data set and different algorithms such as LSTM and Bi-LSTM are employed to produce the result. We are able to obtain a MAE score of around 76.41 for USA and 12.97 for India and RMSE score of 123.87 for USA and 23.21 for India. These scores are much better than most machine learning algorithms such as linear regression. Keywords - Deep Learning, Flight Delay Prediction, Weather, LSTM, Bi-LSTM