基于灰色理论和BP神经网络的高耸构筑物拆除费用预测

Prediction of demolition cost of high-rise structures based on grey theory and BP neural network

为提升高耸构筑物拆除费用估算的准确性,应用灰色理论和BP神经网络算法建立模型对拆除费用进行估算.结合工程案例,对比分析了采用该模型获得的高耸构筑物拆除费用与实际工程造价之间的差别.结果表明,本文提出的模型能够有效降低拆除价格估算结果的平均误差,可以显著提高拆除费用计算精度,进而获得合理的拆除费用,为拆除工程提供概预算参考依据,具有一定的理论意义和实践价值.

In order to improve the accuracy of the demolition cost estimation of high-rise structures,the gray theory and BP neural network algorithm are used to establish a model to estimate the demolition cost.Combined with the project case,the difference between the demolition cost of high-rise structures obtained by using the model and the actual project cost is analyzed.The results show that the model proposed in this paper can effectively reduce the average error of demolition price estimation results,significantly improve the accuracy of demolition cost calculation and obtain reasonable demolition cost,and provide a reference basis for the demolition project budget,which has certain theoretical significance and practical value.