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A Fuzzy Support Vector Machine with Weighted Margin for Flight Delay Early Warning

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3 Author(s)
Haiyan Chen ; Coll. of Inf. Sci. & Technol., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing ; Jiandong Wang ; Xuefeng Yan

Flight delay early warning can reduce the negative impact of the delay. Determining the delay grade of each interval is essentially a multi-class classification problem. This paper presents a flight delay early warning model based on a fuzzy support vector machine with weighted margin (WMSVM) , which adjust the penalties to samples and the margins between samples and the hyperplane according to the fuzzy membership to produce a more reasonable optimal hyperplane. Through one-against-one (OAO) method, the original FSVM is extended to solve multi-class classification problem .Experiments show that the method used to establish the early warning model can predict the delay grade effectively and also prove that the OAO-WMSVM has better performance than OAO-SVM.

Published in:

Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on  (Volume:3 )

Date of Conference:

18-20 Oct. 2008