基于SMOTE算法的航班正常率预测

打开文本图片集

中图分类号：[U8];U111 文献标志码：A本文引用格式：.基于SMOTE算法的航班正常率预测[J].华东交通大学学报，2025，42（3）：57-66.

Flight Punctuality Rate Prediction Based on SMOTE Algorithm

Zhang Jiayil²，Hu Minghua’，Huang Fangen²

（1.CollegeofCivilAviation，Nanjing UniversityofAeronauticsandAstronautics，Nanjing 2106，China; 2.Air TrafficManagementBureau ofCAAC，Beijing10o022，China）

Abstract： To achieve accurate prediction of the flight punctualityrate，a flight regularity prediction index system was constructed based on data statistics of flight delay reasons，includeing departure airport，destination airport， flow control information，and route characteristics.It proposes a SMOTE algorithm-based XGBoost classification predictionmodel （SM-XGBoost model） and a SMOTE algorithm-based LightGBMclassification prediction model（SM-LightGBMmodel）.Basedon the actual data of major airports inEast China，the validityand progressiveness of the proposed model are verified.The results showed that the SM-XGBoost model and SM-LightGBM model were significantly better than the decision tree and random forest models in terms of prediction accuracy and error.In terms of stabilityof training set and test set， SM-LightGBM model is superior to the SM-XGBoost model， with a maximum prediction accuracy of 88.2% for test set. This method provides a new analytical approach for predicting events in similar complex systems.

Keywords：SMOTE algorithm;flight punctuality rate;XGBoost model

Citation format： ZHANG JY，HU MH，HUANG F G.Flight punctuality rate prediction based on SMOTE algorithm[J]. Journal of East China Jiaotong University，2025，42（3）： 57-66.

随着民航运输业的快速发展，航班延误、正常率较低等相关问题也备受瞩目，对正常率问题的研究既是满足航空运输业快速发展、缓解空域拥挤、提高运行效率的突破口，也是提升国家空域系统资源使用效率和空中交通管制服务品质的必然选择。（剩余13402字）