基于BP网络-BIM模型的深基坑工程风险量化研究

Research on Risk Quantification of Deep Foundation Pit Engineering Based on BP Neural Network-BIM Model

为了解决深基坑工程综合单价中风险量化的问题,提出BP神经网络模型与BIM模型相结合的形式。先识别深基坑施工风险因素,确定深基坑施工风险等级;再采用MATLAB软件编写代码实现BP神经网络模型的构建、训练以及测试,得到风险量化系数;最后使用Revit软件建立BIM三维可视化模型,即参数化土方开挖族,添加风险信息和造价信息,从而快速得到深基坑工程项目综合单价以及综合合价。通过BP神经网络与BIM模型结合的形式对工程案例进行分析验证,结果表明该方法是可行的。

In order to solve the problem of risk quantification in comprehensive unit price of deep foundation pit engineering,the paper proposes a combination of BP neural network model and BIM model.First identifies the risk factors of the deep foundation pit construction,determines the risk level of the deep foundation pit construction.Then,uses MATLAB software to write code to implement the construction,training and testing of the BP neural network model,and obtains the risk quantification coefficient.Finally,uses Revit software to build a BIM 3D visualization model,that is parametric earth excavation family,to add risk information and cost information,so as to quickly obtain the comprehensive unit price and comprehensive price of deep foundation pit projects.By analyzing and verifying the engineering case through the combination of BP neural network and BIM model,the results show that the method is feasible.