Data mining techniques to improve no-show forecasting

摘要：

In order to maximum the profit of each flight, the airlines always have some over-booking in one flight. Accurate forecasts of the expected number of noshows for each flight can increase airline revenue by reducing the number of spoiled seats and the number of involuntary denied boarding at the departure gate. In this paper, we develop a combined model to predict no-show rates using historical data and specific information on the individual passengers booked on each flight. Meanwhile, we propose some data mining techniques to improve no-show forecasting. A case study and the relative performance of some methods are introduced, together with some discussion on further research.

作者: Rong Zeng Cao Wei Ding Xiang Yang He Hao Zhang

作者单位: IBM Research - China.

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Service Operations and Logistics,and Informations(2010 IEEE 服务、运筹、物流与信息化国际研讨会)

会议地点: 青岛

会议语种:英文

页码: 40-45

在线出版日期: 2010-07-15（万方平台首次上网日期，不代表论文的发表时间）