Research on Estimating Whole Life Projects According to CS, BPNN & FIS
The inaccuracy of cost estimation in feasibility study and design stage is one of main reasons that make investment of railway construction projects out of control in China. In those two stages cost estimations are affected by many uncertain factors, and the relationship among them is nonlinear and traditional model is hard to solve them. This paper applies CS (Cost-Significant) theorem to simplify the cost estimation, and sets up the forecasting methods for CSIs Cost-significant Items of WLC Whole Life Costing . Then the BPNN (Back-propagation Neural Network) model is made up according to BP algorithm to distill CSIs from the Plethora of the data and information of performed projects, which provides a practical solution for those problems according to the nonlinear theory. Then the FIS (Fuzzy Inference System) is applied to estimate the CSIs and csf(cost-significant factor) with no performed data. The basic theories of BPNN, CS , FISand WLC are introduced and their applications are illustrated with an example in this paper. From the example, we can see that the relative errors are small enough for accuracy demand of cost estimations after simulation, and test result shows that the model based on CSIs, WLC and BPNN theorems is accurate and successful.
Whole life cost Cost significance Back-propagation Fuzzy Inference system
DUAN Xiaochen ZHANG Xiaoping XING Honghong
Economics and Management, Shijiazhuang Railway Institute Shijiazhuang, China Department of Basic Science, Navel Aeronautical Engineering Institute Yantai, China
国际会议
上海
英文
2007-09-21（万方平台首次上网日期，不代表论文的发表时间）