摘要
为了降低建筑安全事故率,减少事故损失,将被动的"事后分析"安全管理模式转变为主动的"事前预防"模式,文章深入研究建筑安全事故发生机理后提炼出"4M"因素,在此基础上构建建设工程安全生产危险因素体系。运用数据挖掘技术找到影响建筑施工安全的关键因素,建立基于RS-GA-BP的建筑施工安全预测模型并实例验证,结果表明,该模型具有较好的可行性与有效性;将安全预测应用于生产实践,具有重要意义。
In order to reduce the rate of construction accidents and accident losses,and change the security management model of passive hindsight into a proactive precaution model,this paper refined 4M factors based on the study of the construction accidents mechanism.The risk factors system for the safety production of the construction projects was established.The data mining techniques were used to determine the key factors which have the impacts on the construction safety.The construction safety forecast model was constructed based on the RS-GA-BP algorithms.A case study was conducted,which shows the feasibility and effectiveness of the model,and the significance of applying safety forecast in the production practice.
出处
《工程管理学报》
2010年第6期647-651,共5页
Journal of Engineering Management
关键词
危险因素
粗糙集
遗传算法
BP网络
安全预测
risk factor
rough set
genetic algorithms
back-propagation neural network
safety forecast
