Title :
Application of artificial fish school and K-means clustering algorithms for stochastic GHP
Author :
Fei, Wang ; Xiao-hao, Xu ; Jing, Zhang
Author_Institution :
Coll. of Civil Aviation, Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
Abstract :
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.
Keywords :
air traffic; airports; stochastic processes; K-means clustering algorithms; airport capacity; artificial fish school; ground holding policy; nominal capacity scenarios tree; stochastic GHP model; Airports; Capacity planning; Clustering algorithms; Delay; Dynamic programming; Educational institutions; Marine animals; Neck; Stochastic processes; Traffic control; AFSA; Air Traffic Management; Clustering Algorithm; Stochastic GHP;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5192417
