Mining and analysis of association rules in tower crane accident cases

doi:10.16265/j.cnki.issn 1003-3033.2021.07.019

Abstract

Abstract: In order to make full use of tower crane accidents information and mine deep into tower crane accident characteristics, an improved Apriori algorithm mining pattern was proposed,association characteristics of tower crane accident can be quickly and effectively mined. Firstly, 200 detailed accident investigation reports of tower crane were collected, accident attribute data in accident investigation report were analyzed and extracted, and coded according to the hierarchical structure.Secondly, a pattern suitable for multi-dimensional association characteristic was proposed based on classic Apriori algorithmt, association characteristics between tower crane accident attributes and causes were mined. Finally, tower crane accident association characteristics were analyzed and summarized according to mining results. The results showed that association rules algorithm can effectively utilize investigation of accident reports and mine characteristic of tower crane accidents in a quantitative way. Between tower crane accident attributes and accident causes have a strong association relation.

Key words: tower crane, accident cases, association rules, Apriori algorithm, accident attribute

CLC Number:

X952

KUANG Yuqi, ZHAO Tingsheng, JIANG Ling,ZHANG Wei. Mining and analysis of association rules in tower crane accident cases[J]. China Safety Science Journal, 2021, 31(7): 137-142.

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