Application of Artificial Fish School and K-means Clustering Algorithms for Stochastic GHP

摘要：

In order to make full use of airport capacity and eliminate existing human errors, typical capacity scenarios are produced, based on artificial fish school and K-means clustering algorithms. Then nominal capacity scenarios tree is constructed, which can be used in stochastic GHP model. Compared to case of no-GHP, the delay cost in static and dynamic models is reduced by 37.2％ and 57.2％ respectively. It is concluded that the mixed algorithm is feasible and the nominal capacity scenarios tree is practical.

关键词： Air Traffic Management AFSA Clustering Algorithm Stochastic GHP

作者: Wang Fei Xu Xiao-hao Zhang Jing

作者单位: College of Civil Aviation, Nanjing University of Aeronautics & Astronautics, Nanjing 210016, China College of Civil Aviation, Nanjing University of Aeronautics & Astronautics, Nanjing 210016, China A

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 4280-4283

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）