基于BIM技术和BP神经网络的建设项目工程造价管理研究

Zhenyu Xin
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引用次数: 0

摘要

为了进一步降低建设项目的工程成本,提出了一种基于BIM技术和BP神经网络的建设项目工程成本管理预测模型。其中以建设项目指标为输入,采用BIM技术计算工程量。然后将工程量清单作为BP神经网络的输入,对工程造价进行预测。结果表明,在matlab软件中对BP神经网络进行训练后,效果良好。而且,预测模型的拟合效果得到了显著提高。实际预测表明,利用该模型预测的水表费用预测值与水表费用的实际值非常接近,两者之间的最大误差仅为266。结果表明,采用所提出的模型可以提高建设项目工程造价预测的准确性,从而进一步降低建设项目的造价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Engineering Cost Management of Construction Project Based on BIM Technology and BP Neural Network
To further reduce the engineering cost of construction project, an engineering cost management prediction model of construction project based on BIM technology and BP neural network is proposed. Among them, the construction project index is taken as the input, and the BIM technology is used to calculate the project quantity. Then the bill of quantity is taken as the input of BP neural network, so as to predict the cost of the engineering cost. The results show that after the BP neural network is trained in MATLB software. Moreover, the fitting effect of the prediction model is significantly improved. The actual prediction shows that the predicted value of meter cost using this model is very close to the actual value of meter cost, and the maximum error between them is only 266. It shows that using the proposed model can improve the accuracy of engineering cost prediction of construction project, so as to further reduce the cost of the construction project.
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