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

In: The 19th International Conference on Industrial Engineering and Engineering Management

Author

Listed:
  • Meng-su Li

    (Tianjin University)

  • Xing Bi

    (Tianjin University)

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.

Suggested Citation

  • Meng-su Li & Xing Bi, 2013. "A Cost Estimation Model of Government Investment Projects Based on BP Neural Networks," Springer Books, in: Ershi Qi & Jiang Shen & Runliang Dou (ed.), The 19th International Conference on Industrial Engineering and Engineering Management, edition 127, chapter 0, pages 235-241, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-38433-2_26
    DOI: 10.1007/978-3-642-38433-2_26
    as

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