基于Apriori算法的民航不正常事件诱因关联性分析

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中图分类号：V267 文献标志码：A 文章编号：2095-2945（2026）01-0012-05

Abstract：Inorder toexplore thecausesofhigh-frequencyabnormaleventsandtheircorelationwitheachother.This papercombinestheideaofshellmodel，whilesortingoutabnormaleventsintheASISsystemin2024，selectssomecommon causes，anddeterminesamulti-dimensionalandtwo-levelcausesystemthatincludes2levels，4dimensions，and88indicators. ThentheAPRIORIalgorithmwasselectedtominethedata fromJanuary toOctober2O24，andthechi-squaretestwasusedto conductstatisticaltestingontheresultsobtainedbytheAPRIORIalgorithmtoprovethescientificnatureoftheresults.Fialy， thedatafromNovembertoDecember2024isusedtotestthereliabilityofthealgorithmmodel.Itwasconcludedthatusing GPSinterferenceinsingle-causeabnormalevents，likeabortapproach，go-around，andbirdstrike，thesupprtscoreswere significantlyfrequentitems，withsupportscoresofO2O7，O.146，andO.38respectively；inmulti-causeabnormalevents（abort approach，go-around，birdstrike）and（deviationfromcommandaltitude，turbulence）aretypicalcausalcombinationsthatleadt the abnormal event.

Keywords： civil aviation safety； abnormal event;cause system; APRIORI algorithm; chi-square test

航空产业的高质量发展是一个国家在时代大环境中保持核心竞争力的必然要求，也是满足人民美好需求的关键。（剩余5847字）