Title :
Initial Flight Delay Modeling and Estimating Based on an Improved Bayesian Network Structure Learning Algorithm
Author :
Liu, Yu-Jie ; Yang, Fan
Author_Institution :
Coll. of Comput. Sci. & Technol., Civil Aviation Univ. of China, Tianjin, China
Abstract :
Flight delay is a nondeterministic problem. Modeling and estimating flight delay is very important in the flight delay research. It is also the precondition to calculate delay propagation. A new Bayesian network structure learning algorithm, named target-fixed stochastic-ordered K2(TSK2), has been proposed in this paper. After using this new algorithm to build the Bayesian network of flight delay, TSK2 has been proved to be suitable to modeling flight delay, and the trained models can use to estimate the delay of arrival and departure flights reliably.
Keywords :
Bayes methods; delay estimation; learning (artificial intelligence); stochastic processes; travel industry; Bayesian network structure learning algorithm; delay propagation; flight delay estimation; flight delay modeling; flight delay research; nondeterministic problem; target-fixed stochastic-ordered K2; Aircraft; Airports; Bayesian methods; Computer networks; Computer science; Delay effects; Delay estimation; Educational institutions; Mathematical model; Propagation delay; Bayesian network; improved algorithm; initial flight delay; modeling; structure learning;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.582