Approach to Estimating the Cost of Government-invested Projects Based on FIS and BPNN
Xiaochen Duan · 2007
A new approach is proposed in order to solve the problem that no existing cost estimation methods are suitable for all new projects. In this paper,a new project is discomposed into n Items and is applied with BPNN(Back-propagation Neural Network)to distill the similar from the historical data so that the items of the new project,based on the nonlinear theory,can be estimated.The characteristics of the new project items are analyzed and divided into known and unknown characteristics and,based on their relationship,a fuzzy inference system is built to make the unknown ones known.According to the relationship between the characteristics and the cost,a fuzzy inference system is established to compute the cost of new items.The historical data and the experts' experience are fully used in all the methods above in order to distill the similarities,create reasonable rules and provide new methods for estimating the primary cost of Hi-tech projects.