A New Method to Alarm Large Scale of Flights Delay Based on Machine Learning
Lü Zonglei, Wang Jiandong, Zheng Guansheng · 2008
A new method to alarm large scale of flight delays based on machine learning is presented in this paper. This new method first does unsupervised learning on the data of the flights collected from the airport. The standard of each class of delay can be gotten after the learning process. With these classes of delay, the supervised learning method can be used on the data so that the alarm model could be built. Comparing with the recent manual alarm standard, this model synthesizes more factors to do alarm. Since the recent delay standard is only related to the number of flights, which is helpful only in serious delay case, the new model performs will be more practical value than recent ones.