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To further enhance the risk management mechanism during flight operations, an early warning for pilot handling smoothness was developed by integrating flight big data. First, core parameters related to unstable approaches were filtered from QAR data. The XGBoost algorithm was then utilized for feature optimization to identify key risk early warning indicators. Subsequently, a dynamic risk identification architecture capable of effectively capturing spatio-temporal dependencies was constructed by incorporating the attention mechanism of Transformer networks. . Finally, the method's performance was validated using flight data from B737-800 aircraft operated by an airline in Shandong. The results indicate that this method can effectively predict in-flight risk events, particularly in providing high-accuracy risk warnings during critical phases before landing. Compared with traditional warning methods, the approach demonstrates significant advantages in identification accuracy, model generalization capability, and feature extraction efficiency.

, authors=Wenchao WANG¹, Jian HE^{**, 1}, Lei WANG¹, Hangbin ZHANG², authorsList=Wenchao WANG, Jian HE, Lei WANG, Hangbin ZHANG, authorCompany=null, correspAuthors=Jian HE, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1282032459533488730, articleId=1282032451442676308, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=融合XGBoost与Transformer的飞行员操纵风险预警方法, columnId=1149733269727526997, journalTitle=中国安全科学学报, columnName=安全工程技术, runingTitle=null, highlight=null, articleAbstract=

为强化飞行过程中的风险管理机制，提出一种融合飞行大数据的飞行员操纵风险性预警方法。首先，从快速存取记录仪（QAR）数据中筛选与不稳定进近相关的核心参数，并利用梯度提升决策树（XGBoost）算法进行特征优化，确定关键风险预警指标。然后，融合Transformer网络的注意力机制，构建有效捕捉时空依赖性的动态风险识别架构。最后，以山东某航空公司B737-800型机的航班数据为例，验证方法性能。结果表明：该方法能够有效预测飞行中的风险事件，尤其在降落前的关键时刻，方法可提供高精度的风险预警。与传统预警方法相比，该方法在识别精度、方法泛化性以及特征提取效能方面表现出显著优势。

, authors=王文超副教授¹, 何健^{**, 1}, 汪磊研究员¹, 张航宾工程师², authorsList=王文超副教授, 何健, 汪磊研究员, 张航宾工程师, authorCompany=null, correspAuthors=何健, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=zG7eUlMdDuAl7Y7XjpbTRw==, magXml=rf75H0weBny8RGE4bIxFaA==, pdfUrl=null, pdf=6P3lf7SLiXdlSMtpj/r1iQ==, pdfFileSize=2007261, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=jwadG9R0BpKqHL4JzOIPFw==, mapNumber=null, fund=null)}, authors=[Author(id=1282032469629178469, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282032451442676308, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=wenchaowang@163.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1282032471655027303, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282032451442676308, authorId=1282032469629178469, language=EN, stringName=Wenchao WANG, firstName=Wenchao, middleName=null, lastName=WANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹College of Safety Science and Engineering, Civil Aviation University of China, Tianjin 300300, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1282032472137372264, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282032451442676308, authorId=1282032469629178469, language=CN, stringName=王文超副教授, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹中国民航大学 安全科学与工程学院，天津 300300, bio={"content":"

王文超（1982—），男，河北承德人，博士，副教授，主要从事民航安全风险管理及人因工程等方面的研究。E-mail: wenchaowang@163.com。

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王文超（1982—），男，河北承德人，博士，副教授，主要从事民航安全风险管理及人因工程等方面的研究。E-mail: wenchaowang@163.com。

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