IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-662-46994-1_37.html
   My bibliography  Save this book chapter

Research on Cost Estimation of Highway Project Based on the GA-BP Algorithm

In: Proceedings of the 19th International Symposium on Advancement of Construction Management and Real Estate

Author

Listed:
  • Yilong Zhang

    (Chongqing Jiaotong University)

  • Yajun Cai

    (Chongqing Jiaotong University)

  • Huanhuan Wu

    (Chongqing Jiaotong University)

Abstract

In order to make up the inadequacy of cost estimation of traditional highway project, this paper combines BP artificial neural network with genetic algorithm to set up the model GA-BP algorithm, and the artificial intelligence algorithm is led to the cost estimation of highway project. Based on the cost information of existing highway project, the eigenvalues and membership grade are found out. Then, based on the MATLAB platform, through the experimental simulation to compare the results of GA-BP algorithm with BP algorithm. Research finding shows the optimized GA-BP algorithm has calculation simple, fast and high calculation precision. Thus it is concluded that the feasibility and effectiveness of the algorithm.

Suggested Citation

  • Yilong Zhang & Yajun Cai & Huanhuan Wu, 2015. "Research on Cost Estimation of Highway Project Based on the GA-BP Algorithm," Springer Books, in: Liyin Shen & Kunhui Ye & Chao Mao (ed.), Proceedings of the 19th International Symposium on Advancement of Construction Management and Real Estate, edition 127, chapter 0, pages 451-462, Springer.
    • Handle: RePEc:spr:sprchp:978-3-662-46994-1_37
    DOI: 10.1007/978-3-662-46994-1_37
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-662-46994-1_37. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.