A Cost Estimation Model of Government Investment Projects Based on BP Neural Networks

Meng-su Li () and Xing Bi
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Meng-su Li: Tianjin University
Xing Bi: Tianjin University

Chapter Chapter 26 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 235-241 from Springer

Abstract: Abstract An investment estimation model of government investment projects is built in this paper based on BP Neural Networks method. From the viewpoint of minimization of the life circle cost, it can reduce the calculating work furthest with the method of prominence theory and extract the items of significant cost and significant factors from historical information of engineering cost, thus estimate accurately engineering cost of projects. In spite of the error between predictor of BP neural network and actual value may be large, even value of multiple operations can nearly eliminate the random so that the estimation result has high precision.

Keywords: BP neural networks; Government investment projects; Significant factors (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-38433-2_26

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DOI: 10.1007/978-3-642-38433-2_26

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