摘要
现行高铁高新技术投资项目估算和概预算方法主要是:将拟建工程与已完成类似工程比较,划分为有类似部分和无类似部分。类似部分通过线性分析模型,或根据概预算定额估算;无类似部分根据专家经验简单比较类推和三点估计法估算。这样不仅估算误差大、可靠性差,而且计算工作量大。本文在全生命周期造价WLC和显著性成本CS理论基础上,通过建立预测全生命高铁投资项目非线性投资估算模型有效拟合造价和诸多影响因素之间的高度非线性关系,通过显著性成本CS方法和专家经验对新建项目显著性成本项目CSIs进行分解,将其划分为有大量时序数据、大量非时序数据、一定量的类似项目和无类似项目的CSIs,对前两种情况分别采用混沌时序分析(类似性通过规定工程特征判断)和BP神经网络解决(类似性通过方法本身判断);一定量的类似项目通过模糊聚类FC方法(类似性通过方法本身判断)预测造价;无类似项目情况下则充分利用专家经验,通过模糊推理系统FIS方法预测CSIs造价和整个项目显著性因子csf数据。该方法通过编制计算机软件,不仅能够明显简化计算工作量和程序,而且能够有效拟合造价历史数据的非线性、随机性、自组织、自相似等趋势特征,提高了预测准确性。
The present investment appraisal and budget estimation methods for the high and new technique in- vestment projects of China high-speed railways are as follows. Comparing with similar completed projects, the project to be built is divided into similar parts and unsimilar parts; the similar parts are estimated by use of the linear analysis model or according to the budget quotas; the unsimilar parts are estimated by empirical analogy or by three time estimation; therefore, great errors, poor reliability and much workload are caused. In this paper, on the basis of the theories of whole life-cycle costs （WLC） and costs-significant （CS）, the nonlinear investment estimation model for prediction of a whole life-cycle high-speed railway project was established to ef- fectively fit the highly nonlinear relationships between costs and mutiple influencing factors. The cost-signifi- cant items （CSIs） of the scheduled project were decomposed into the CSIs with similar and unsimilar data by the CS method and experts＇ experiences. Chaotic time series were used to estimate the similiar CSIs with the plethora of the time series data of similar and finished items. The back-propagation neural network （BPNN） was used to estimate the similiar CSIs with the plethora of the non-time series data of finished items. The fuzzyclustering （FC） method was applied to estimate the similiar CSIs with a certain amount of the data of finished items. When there was no similar finished items, the fuzzy inference system （FIS） was used to make full uas ofexperts experiences and calculate the costs of the CSIs and the csf data of the whole project. Through program- ming computer software, the proposed methods can greatly reduce the workload of calculation, simplify the estimation procedure and effectively improve the accuracy of estimation by fitting the best nonlinear trend curve of the finished historic data.
出处
《铁道学报》
EI
CAS
CSCD
北大核心
2013年第10期114-122,共9页
Journal of the China Railway Society
基金
河北省科技厅重点项目(09055002)
教育部人文社科研究规划项目(11YJAZH121)
关键词
新建高铁工程
全生命周期造价
非线性估算
投资估算
high-speed railway engineering project
whole life-cycle cost
nonlinear estimation
investment es- timation
