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基于信息敏感性与 CSA-BP 神经网络的“智慧工地系统” 实施风险评价研究
引用本文:韦 良,陈家慧.基于信息敏感性与 CSA-BP 神经网络的“智慧工地系统” 实施风险评价研究[J].工程管理学报,2023,37(1):147-152.
作者姓名:韦 良  陈家慧
作者单位:1,2. 广西大学 土木建筑工程学院;1,2. 广西大学 建筑与土木工程虚拟仿真实验教学中心
摘    要:为提高“智慧工地系统” 在实施过程中的安全性,减少其因应用不当等原因造成的损失。参考 WSR 方法论与信息敏感性理论建立“智慧工地系统” 实施风险评价指标体系。引入 CSA-BP 神经网络算法,该方法通过乌鸦搜索算法(CSA)弥补BP 神经网络易陷入局部最优及收敛速度慢等缺陷,建立了实施风险评价模型。将该模型应用到广西某码头油库项目进行实例验证,评价结果与实际情况相符,表明其可行性较高,具有实际应用价值。根据模型评价结果有针对性地提出建议及措施,为“智慧工地系统” 的推广与实施过程提供理论依据。

关 键 词:信息敏感性  乌鸦搜索算法(CSA)  BP  神经网络  智慧工地  风险评价

The Implementation Risk Assessment of "Smart Construction Site System"Based on Information Sensitivity and CSA-BP Neural Network
WEI Liang,CHEN Jiahui.The Implementation Risk Assessment of "Smart Construction Site System"Based on Information Sensitivity and CSA-BP Neural Network[J].Journal of Engineering Management,2023,37(1):147-152.
Authors:WEI Liang  CHEN Jiahui
Affiliation:1,2. School of Civil Engineering and Architecture, Guangxi University;1,2. Virtual Simulation Experiment Teaching Center of Architecture and Civil Engineering
Abstract:This paper aims to improve the security of the "smart construction site system" during the implementation process andreduce the loss caused by the improper application of the system. The implementation risk assessment index system of "smartconstruction site system" was established by referring to WSR methodology and information sensitivity theory. The CSA-BP neuralnetwork algorithm was introduced. The crow search algorithm( CSA) was used to make up for the defects of the BP neural network,such as easy to fall into local optimum and slow convergence speed, and the implementation risk assessment model was established.The model is applied to a terminal oil depot project in Guangxi, and the evaluation result is consistent with the actual situation, whichindicates that the model is feasible and has practical application value. According to the model evaluation results, targetedsuggestions and measures are put forward to provide a theoretical basis for the promotion and implementation process of "smartconstruction site system".
Keywords:information sensitivity  CSA  BP neural network  smart site  risk assessment
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