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Application Research on the Artificial Neural Network in the Building Materials Price Prediction

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

Author

Listed:
  • Hongxiang OuYang

    (Business School of Hohai University)

  • Xinjuan Zhang

    (JINQIAO Real Estate Co. Ltd)

  • Cencen Hu

    (Business School of Hohai University)

Abstract

The bidder’s accurate Prediction of the materials’ up and downs during the construction process will undoubtedly improve the reliability of the bidding price and the possibility of winning a bid. This article proposes the material price forecasting model with the BP Neural Network, which uses the materials’ historical price as samples based on analyzing the influence of the materials’ future ups and downs to the construction profit. The case shows that the model has strong nonlinear mapping ability and fault tolerance capability, and can be a reliable method for construction enterprises to predict the materials price trend when bidding.

Suggested Citation

  • Hongxiang OuYang & Xinjuan Zhang & Cencen Hu, 2013. "Application Research on the Artificial Neural Network in the Building Materials Price Prediction," 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 167-175, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-38433-2_19
    DOI: 10.1007/978-3-642-38433-2_19
    as

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