IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-642-35548-6_120.html
   My bibliography  Save this book chapter

A Combination Forecasting Model for Fast Cost Estimating in Civil Engineering

In: Proceedings of the 17th International Symposium on Advancement of Construction Management and Real Estate

Author

Listed:
  • Xun Liang

    (Guangdong University of Technology)

Abstract

This paper tries to make a model based on fuzzy mathematics, Grey model and regression model, exploring methods to estimate the project cost quickly. Firstly, the similar projects are found by the similarity measures in the fuzzy mathematics. Secondly, Grey interconnects degree helps to find the main factors affecting the project cost. Finally, these main factors establish the regression equation. This model is applied to analyze data from the construction projects cost in Guangzhou, indicating the effectiveness and practicality of the model. By comparison with the single models, the civil engineering cost is estimated quickly and accurately, while the combined model improves the limitations of a single model, accuracy and reduce the prediction errors.

Suggested Citation

  • Xun Liang, 2014. "A Combination Forecasting Model for Fast Cost Estimating in Civil Engineering," Springer Books, in: Jiayuan Wang & Zhikun Ding & Liang Zou & Jian Zuo (ed.), Proceedings of the 17th International Symposium on Advancement of Construction Management and Real Estate, edition 127, chapter 0, pages 1183-1190, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-35548-6_120
    DOI: 10.1007/978-3-642-35548-6_120
    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:978-3-642-35548-6_120. 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.