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Association analysis of causative factors of fall from height accidents
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作者 Hanjun Guo Yuwei Mo +3 位作者 Fushuai Guo Rongxue Kang Ke Tang Qiuju Ma 《Journal of Safety Science and Resilience》 2025年第4期616-629,共14页
Working at height is widespread across various industries,with frequent and hazardous falls occurring regularly.Such tasks are often linked to multifactorial issues,where the interplay of diverse factors leads to acci... Working at height is widespread across various industries,with frequent and hazardous falls occurring regularly.Such tasks are often linked to multifactorial issues,where the interplay of diverse factors leads to accidents that are challenging to control effectively.This study establishes an index system for the factors influencing falls from height by statistically analyzing 101 incidents,identifying 64 causative elements classified into four categories.These include 17 factors related to operator condition and behavior,13 concerning equipment and facility conditions,7 pertaining to site conditions,and 27 associated with production operations management.Utilizing the Apriori algorithm and Gephi software,the study mined the association rules of causal factors in falls from height and constructed their network diagram.By examining association rules with high support,confidence,and lift,the relationships between key causal factors leading to accidents are clarified,identifying critical operational control points and providing a scientific foundation for reducing the incidence of falls from height.Currently,China's standards related to working at height remain fragmented.This study lays the foundation for the development of comprehensive,systematic,generic safety management standards for working at height,satisfying the needs of the field. 展开更多
关键词 work-at-height accident Apriori algorithm Association rules Analysis of causal factors
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