Abstract: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.
刘敬严,陈蕾,宋宁,段晓晨. 绿色高铁建设环境成本CS、BPNN估算方法研究[J]. 铁道工程学报, 2015, 32(7): 111-116.
LIU Jing - yan,CHEN Lei,SONG Ning,DUAN Xiao – chen. Research on the Construction Environmental Cost Estimation of Green High - speed Railway Based on CS and BPNN. 铁道工程学报, 2015, 32(7): 111-116.
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