计算机应用与软件2024，Vol.41Issue(5)：72-78,7.DOI:10.3969/j.issn.1000-386x.2024.05.011
基于联邦学习的航班延误预测模型
FLIGHT DELAY PREDICTION MODEL BASED ON FEDERATED LEARNING
摘要
Abstract
In view of the fact that the existing flight delay prediction methods do not consider the problems of multiple data sources and data privacy,this paper proposes a federated learning framework,which integrates logistic regression methods,so that the training data can kept locally without uploading and sharing,and the flight delay can be predicted on the premise of protecting data privacy.At the same time,aimed at the problem of indirect information leakage in the training process,homomorphic encryption technology was adopted to encrypt the transmitted parameters.The experimental results show that the federated modeling method can achieve similar accuracy than the traditional method without sharing data,which provides a practical scheme for optimizing civil aviation business.关键词
航班延误/数据隐私/联邦学习/同态加密Key words
Flight delay/Data privacy/Federated learning/Homomorphic encryption分类
计算机与自动化引用本文复制引用
李国,秦维..基于联邦学习的航班延误预测模型[J].计算机应用与软件,2024,41(5):72-78,7.基金项目
国家自然科学基金项目(U2033205). （U2033205）
