Flight Delay Prediction System Using Weighted Multiple Linear Regression (International Journal of Engineering and Computer Science, 2015)
Airline delays caused by bad weather, traffic control problems and mechanical repairs are difficult to predict. If your flight is canceled, most airlines will rebook you on the earliest flight possible to your destination, at no additional charge. Unfortunately for airline travelers, however, many of these flights do not leave on-time. The issue of delay is paramount for any airlines. Therefore we intend to aid the airlines by predicting the delays by using certain data patterns from the previous information. This system explores what factors influence the occurrence of flight delays along with the intensity of the delays. Our method is based on archived data at major airports in current flight information systems.Classification in this scenario is hindered by the large number of attributes, which might occlude the dominant patterns of flight delays. The results of data analysis will suggest that flight delays follow certain patterns that distinguish them from on-time flights. Our system also provides current weather details along with the weather delay probability. We have achieved much better accuracy in predicting delays. We may also discover that fairly good predictions can be made on the basis on a few attribute.