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建筑施工安全事故死亡人数预测与影响因素分析 被引量:14

Analysis on the forecast of construction death and its influence factors
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摘要 建筑施工安全事故死亡人数预测及敏感因素分析可以为制定施工现场管理制度和举措提供依据,对预防建筑施工安全事故具有重要意义。为合理精准地预测建筑施工安全事故死亡人数,明确相应的敏感因素,以2005—2019年全国建筑施工安全事故死亡人数为依据,建立了灰色马尔柯夫模型对建筑施工安全事故死亡人数进行预测;同时,根据灰色关联度分析,建立了考虑建筑施工安全事故死亡人数主要影响因素的GM(1,N)模型,基于模型预测准确性评价分析其敏感因素。结果表明:由灰色马尔柯夫预测模型得到的2010—2019年建筑施工安全事故死亡人数与实际值的平均相对误差为7.08%,模型较可靠;依据该模型预测2020—2022年的建筑施工安全事故死亡人数分别为819、799和779人;灰色关联GM(1,N)模型的预测精度为89.71%,建筑施工安全事故死亡人数的敏感因素主要为建筑企业数量和从业人数。 The prediction of the death toll and the analysis of sensitive factors in the construction safety accidents can provide the basis of the construction management and the measures,which are very significant for the prevention of construction accidents.To predict the death toll of construction safety accidents accurately and to clarify the corresponding sensitive factors reasonably,the death toll of construction safety accidents in China from 2005 to 2019 is investigated in this paper,and a grey Markov prediction model is established based on the data.After the accuracy verification of the model,the death toll prediction of construction safety accidents is done.Meanwhile,the GM(1,N)model considering the main influencing factors of the death toll in the construction accidents is established according to the grey relational analysis,and the sensitive factors are analyzed by evaluating the prediction accuracy of the GM(1,N)model.The results show that the average relative error between the prediction value of the grey Markov model and the actual data on the death toll of construction safety accidents from 2010 to 2019 is 7.08%,which means the grey Markov model is reliable.By the application of the developed grey Markov model,the predicted death toll of construction accidents from 2020 to 2022 is 819,799,and 779,respectively.Considering that the grey correlation degree among the construction enterprises number,the employee number,and the death number of construction accidents is high,the grey correlation GM(1,N)model based on these influence factors is established,and its prediction accuracy can reach 89.71%.Thus,the sensitive factors for the death number of construction accidents are mainly the number of construction enterprises and the employees.
作者 董利飞 陈飞宇 王苗 秦茂龙 郭正超 胡科 DONG Li-fei;CHEN Fei-yu;WANG Miao;QIN Mao-long;GUO Zheng-chao;HU Ke(College of Civil Engineering,Chongqing Three Gorges University,Chongqing 404120,China;Chongqing Engineering Research Center of Disaster Prevention&Control for Banks and Structures in Three Gorges Reservoir Area,Chongqing 404120,China;College of Mathematics and Statistics,Chongqing Three Gorges University,Chongqing 404120,China)
出处 《安全与环境学报》 CAS CSCD 北大核心 2022年第3期1430-1435,共6页 Journal of Safety and Environment
基金 重庆市教育委员会科学技术研究计划青年项目(KJQN202001203,KJQN202001202) 重庆市三峡水库岸坡与工程结构灾变防控工程技术研究中心开放基金项目(SXAPGC18YB04) 重庆三峡学院校级青年项目(19QN10)。
关键词 安全社会工程 灰色马尔柯夫模型 GM(1 N)模型 死亡人数 影响因素 safety social engineering grey Markov model GM(1,N)model death toll influence factors
作者简介 董利飞,副教授,从事岩石物理与工程安全、非常规油气开发等研究;通信作者:王苗,助教,从事应用数学、大数据分析技术研究,wangm_dls@163.com。
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