Prediction of Construction Cost Based on Integration of Geostatistics and Support Vector Machines
CSTR:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    In order to accurately predict the cost of construction project, according to the sample time dependent and nonlinear characteristics, this study has constructed a prediction model of construction project cost based on the geostatistics and support vector machine. Firstly, the cost data of construction engineering are collected, and then, the embedding dimension of time series is obtained by geostatistics according to time correlation of construction cost sample, and the construction cost learning samples of construction project, support vector machine is used to establish project cost prediction model, and test and analysis of the performance through the prediction example. The results show that the proposed model can effectively fit the construction cost of sample time correlation, and get higher accuracy of construction cost prediction, and the result is much better than the other models.

    Reference
    Related
    Cited by
Get Citation

刘春.地统计学与支持向量机相融合的建筑工程造价预测.计算机系统应用,2018,27(4):272-275

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:July 31,2017
  • Revised:August 14,2017
  • Adopted:
  • Online: April 03,2018
  • Published:
Article QR Code
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063