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

被引：9

作者：

Chen, Haiyan ^{[1
]}

Wang, Jiandong ^{[1
]}

Yan, Xuefeng ^{[1
]}

机构：

[1] Nanjing Univ Aeronaut & Astronaut, Coll Informat Sci & Technol, Nanjing 210016, Peoples R China

来源：

FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 3, PROCEEDINGS | 2008年

关键词：

D O I：

10.1109/FSKD.2008.51

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：331 / 335

页数：5

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