基于改进模糊神经网络的公共建筑节能改造费用估算研究  

Research on Cost Valuation of Public Buildings’ Energy-saving Based on Improved Fuzzy Neural Network

作　　者：张文宇[1] 刘畅[1] 贺珍 ZHANG Wenyu;LIU Chang;HE Zhen(Xi'an University of Post and Telecommunications,Xi'an 710061)

机构地区：[1]西安邮电大学

出　　处：《计算机与数字工程》2019年第10期2517-2523,共7页Computer & Digital Engineering

基　　金：陕西省教育厅专项科研计划项目(编号：2013JK0175)资助

摘　　要：为了解决公共建筑涵盖建筑类型较多同时能耗巨大的问题,应对其进行节能改造,但由于我国公共建筑节能改造费用成本库尚未建立,缺少节能改造费用估算依据。因此,提出运用模糊神经网络方法对节能改造费用进行估算。首先,对节能改造的全生命周期进行划分,并根据节能改造的周期划分识别节能改造的全生命周期费用;其次,将模糊神经网络应用于节能改造费用估算,构建改造实施阶段费用模糊神经网络估算模型;最后,运用实际案例论证模糊神经网络在节能改造费用估算的适用性和准确性。In order to solve the problem that public buildings cover more types of architect projects and consume more energy,energy-saving renovation should be carried out.However,due to the fact that China's public building energy-saving renovation cost datum has not been established,there is no basis for estimating energy-saving renovation costs.Therefore,the fuzzy neural network method is proposed to estimate the cost of energy-saving renovation.Firstly,the whole life cycle of energy-saving retrofit is divided,and the life cycle cost of energy-saving retrofit is identified according to the cycle of energy-saving retrofit.Secondly,the fuzzy neural network is applied to the cost estimation of energy-saving retrofit,and the fuzzy neural network estimation of the cost of constructing the reconstruction phase is established.Finally,the practical case is used to demonstrate the applicability and accuracy of fuzzy neural network in energy saving retrofit cost estimation.

关 键 词：节能改造 公共建筑 模糊神经网络 全生命周期 

分 类 号：TU201.5[建筑科学—建筑设计及理论]