基于粗糙集和支持向量机的航班运行风险预测

doi:10.16265/j.cnki.issn1003-3033.2017.09.027

中国安全科学学报 ›› 2017, Vol. 27 ›› Issue (9): 158-163.doi: 10.16265/j.cnki.issn1003-3033.2017.09.027

基于粗糙集和支持向量机的航班运行风险预测

王岩韬讲师, 唐建勋, 赵嶷飞教授

中国民航大学空管运行安全技术国家重点实验室,天津 300300

收稿日期:2017-06-26 修回日期:2017-08-02 出版日期:2017-09-20 发布日期:2020-11-16
作者简介:王岩韬 (1982—),男,吉林磐石人,硕士,讲师,中国民航大学民航航务研究所主任、飞行运行控制系副主任,主要从事飞行运行安全与管理等方面研究。 E-mail: CAUCwyt@126.com。
基金资助:
国家重点研发计划 (2016YFB0502400);国家自然科学基金资助(71701202,U1433111);民航局科技项目(20150204)。

Prediction of risks in flight operations based on rough sets and support vector machine

WANG Yantao, TANG Jianxun, ZHAO Yifei

National Air Traffic Safety Technology Laboratory, Civil Aviation University of China, Tianjin 300300,China

Received:2017-06-26 Revised:2017-08-02 Online:2017-09-20 Published:2020-11-16

摘要/Abstract

摘要： 为提高航班运行风险预测精确度,参照民航局咨询通告《航空承运人运行控制风险管控系统实施指南》,首先分析山东航空航班控制工作流程,初步筛选出15个航班运行风险评估指标项;然后精选100个航班历史数据,根据粗糙集理论,结合遗传算法和Johnson算法约简评估项,获取8个核心指标;最后,利用支持向量机(SVM)算法建立风险预测模型,并用Matlab进行仿真。结果表明:对于高中低3类风险等级,用该方法所得样本分类正确率可达82.22%,该方法可用于航班运行风险的评估和分级。

关键词: 航班运行, 风险预测, 粗糙集, 遗传算法, Johnson算法, 支持向量机(SVM)

Abstract: In order to improve the accuracy of prediction of risks in flight operations, Shandong airlines flight control workflow was analyzed first, and fifteen risk items were taken initially as flight operation risk assessment indicators according to the Civil Aviation Authority Advisory Circular "Air Carrier Operation Control Risk Management System Implementation Guide". Then, on the basis of the data on 100 historical flights of Shandong airlines, the number of risk items was reduced to eight by using the rough set theory, the genetic algorithm and the Johnson's algorithm. Finally, a risk prediction model was built by means of the SVM algorithm. A simulation was carried out with Matlab. The results show that the overall correct rate of sample classification can reach 82.22% for high, medium, low-three types of risk level, and that the method can be used to realize the assessment and classification of risks in flight operations.

Key words: flight operations, prediction of risk, rough sets, genetic algorithm, Johnson's algorithm, support vector machine(SVM)

中图分类号:

X949
U8

王岩韬, 唐建勋, 赵嶷飞. 基于粗糙集和支持向量机的航班运行风险预测[J]. 中国安全科学学报, 2017, 27(9): 158-163.

WANG Yantao, TANG Jianxun, ZHAO Yifei. Prediction of risks in flight operations based on rough sets and support vector machine[J]. China Safety Science Journal, 2017, 27(9): 158-163.

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基于粗糙集和支持向量机的航班运行风险预测

Prediction of risks in flight operations based on rough sets and support vector machine

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