基于BP神经网络的装配式建筑投资估算  

Investment estimation of prefabricated building based on BP neural network

作　　者：胡庆国[1] 蔡璧蔓 何忠明[1] 戴卓炜 HU Qing-guo;CAI Bi-man;HE Zhong-ming;DAI Zhuo-wei(School of Civil Engineering and Architecture, Changsha University of Science and Technology, Changsha 410114, China)

机构地区：[1]长沙理工大学交通运输工程学院,湖南长沙410114

出　　处：《长沙理工大学学报（自然科学版）》2018年第4期66-72,86,共8页Journal of Changsha University of Science and Technology:Natural Science

基　　金：湖南省发改委2017年度第一批重大课题(201733)

摘　　要：针对装配式建筑造价高于传统建筑、容易出现投资失控这一前沿科学问题,在总结分析装配式建筑结构的相关特点的基础上,利用显著性特征理论得出装配式建筑投资预算特征参数;将得出的特征参数作为输入向量引入BP神经网络模型,经过反复多次训练,建立估算模型;最后将长沙某小学装配式建筑作为检验样本来检验该模型的现实可行性。研究结果表明,检验样本的数据模拟输出值与样本真实值之间有较高的吻合度,结果误差均在3%以内,符合装配式建筑前期决策阶段对投资估算误差的要求标准,具有现实可行性,可以用来进行装配式建筑的投资估算。In view of the frontier scientific problem that the cost of the prefabricated building is higher than the traditional building,and prefabricated building is easy to out of control of the investment.According to the related literature and the related characteristics of the prefabricated architecture,the characteristic parameters of the investment estimation for prefabricated building by using the significance characteristic theory are obtained.The related characteristic parameters are introduced into the BP neural network model as the input vector,repeated training and the established the estimated model.The prefabricated project of a primary school in Changsha is taken as a sample to test the feasibility of the model.The results show that there is a high degree of coincidence between the simulated output value of the sample,and the result error is within3%.The accuracy of the result can reach the requirement standard of the investment estimation error in the early decision stage of the prefabricated building project.It has practical feasibility and can be used for the investment of the prefabricated building estimates.

关 键 词：BP神经网络 显著性理论 装配式建筑 投资估算 模型 样本 

分 类 号：TU12[建筑科学—建筑理论]