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

Hongxiang OuYang (), Xinjuan Zhang () and Cencen Hu
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Hongxiang OuYang: Business School of Hohai University
Xinjuan Zhang: JINQIAO Real Estate Co. Ltd
Cencen Hu: Business School of Hohai University

Chapter Chapter 19 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 167-175 from Springer

Abstract: 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.

Keywords: Artificial neural network; Bidding price; Material price; Prediction (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_19

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DOI: 10.1007/978-3-642-38433-2_19

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