摘要
研究目的:如何界定高铁建设环境影响内容、估算环境成本是高铁实现绿色工程的重要内容。本文在界定高铁建设环境成本的计算内容基础上,运用显著性成本方法(CS)建立高铁建设环境成本数据库,运用BP神经网络方法预测拟建工程全生命建设环境成本,并以长益城际铁路进行实例验证,结果表明该模型适用性强,对高铁全生命建设环境成本预测准确性高。研究结论:(1)通过CS理论提取高铁工程显著性环境成本项目可以大幅简化环境成本估算工作量;(2)BP神经网络在高铁项目环境成本估算方面具有适用性;(3)为更准确估算环境成本,需进一步完善高铁项目建设环境成本数据库;(4)本文提出的高铁建设环境成本估算方法和评价体系,可应用于铁路行业高铁项目的建设环境成本估算和控制等工作。
Research purposes: It is important to analyze construction environmental impact factors and estimate environmental cost for green engineering construction. Content of high - speed railway construction environmental cost was analyzed according to the definitions. The cost -significant (CS) theory was put forward to find out Cost - significant Items (CSIs)based on the data and information of completed projects. BP neural network method was introduced to predict the environmental costs of proposed construction project based on environmental cost database. Changsha -Yiyang inter- city railway environmental costs prediction results proved the accuracy Research conclusions: ( 1 ) Significant cost theory can greatly simplify the workload by finding out cost - significant items when estimating high -speed railway construction environmental cost. (2)BP neural network has applicability in high - speed railway construction environment cost estimation. (3)High -speed railway construction environment cost database need to be supplemented further for more accurate estimation. (4) The construction environmental cost evaluation method, put forward in this paper, can be applied in construction environmental cost estimation and control.
出处
《铁道工程学报》
EI
北大核心
2015年第7期111-116,共6页
Journal of Railway Engineering Society
基金
教育部项目(11YJAZH121)
河北科技厅项目(14456104D)
河北省社科基金项目(HB14GL021)
河北省软科学研究基地项目:工程建设管理研究(12457206D-14)
河北省教育厅人文社科重点基地项目
关键词
绿色高铁
建设环境成本
人工神经网络
显著性成本
green high -speed rail
construction environmental cost
artificial neural network
cost significance