Construction Project Cost Prediction Based on Genetic Algorithm and Least Squares Support Vector Machine

被引：0
|
作者：
Xu, Ming [1 ]
Xu, Bingfeng [1 ]
Zhou, Lanjiang [2 ]
Wu, Lin [2 ]
机构：
[1] Kunming Univ Sci & Technol, Sch Civil Engn & Architecture, Kunming 650500, Peoples R China
[2] Kunming Univ Sci & Technol, Sch Informat Engn & Automat, Kunming 650500, Peoples R China
来源：
PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON CIVIL ENGINEERING AND TRANSPORTATION 2015 | 2016年 / 30卷
关键词：
construction project cost; forecast model; genetic algorithm; least squares support vectormachines; small-sample learning;
D O I：
暂无
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
For the small sample data and complex nonlinear characteristic of construction project cost, a new hybrid prediction model combing genetic algorithm and small sample learning model based on least squares support vector machines is proposed. First, all the candidate features are ranked by correlation with the dependent variable, the front ranking features are used to initialize part of population for the genetic algorithm to get better feature subset, and then the construction cost prediction model of the least square support vector machine is constructed. Experiments on Jiangsu Province housing project data show an improved performance over other models in prediction accuracy, it is an effective method of project cost forecasting.
引用
收藏
页码：1004 / 1009
页数：6
相关论文
共 50 条
  • [21] Prediction of accelerometer parameters based on grey least squares support vector machine
    Yu, X.-T. (yuxiangtao@163.com), 1600, Editorial Department of Journal of Chinese Inertial Technology (21):
  • [22] Research on Rock Strength Prediction Based on Least Squares Support Vector Machine
    Li W.
    Tan Z.
    Geotechnical and Geological Engineering, 2017, 35 (1) : 385 - 393
  • [23] Study on Water Bloom Prediction Based on Least Squares Support Vector Machine
    Liu Zai-wen
    Wang Xiao-yi
    Lv Si-ying
    2011 INTERNATIONAL CONFERENCE ON MACHINE INTELLIGENCE (ICMI 2011), PT 2, 2011, 4 : 337 - +
  • [24] Least Squares Support Vector Machine based Lithium Battery Capacity Prediction
    Liu, Xin
    Liu, Dan
    Zhang, Yan
    Wang, Qisong
    Wang, Hua
    Zhang, Fang
    2014 INTERNATIONAL CONFERENCE ON MECHATRONICS AND CONTROL (ICMC), 2014, : 1148 - 1152
  • [25] Application on Network Traffic Prediction Based on Least Squares Support Vector Machine
    Ren Yuzhuo
    Xia Kewen
    Wang Yan
    Shi Jun
    INFORMATION TECHNOLOGY FOR MANUFACTURING SYSTEMS, PTS 1 AND 2, 2010, : 364 - +
  • [26] Prediction and dispatching of workshop material demand based on least squares support vector regression with genetic algorithm
    Wang, Shuai
    Wang, Qingming
    INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL, 2012, 15 (01): : 213 - 222
  • [27] Bankruptcy prediction with Least Squares Support Vector Machine Classifiers
    Van Gestel, T
    Baesens, B
    Suykens, J
    Espinoza, M
    Baestaens, DE
    Vanthienen, J
    De Moor, B
    2003 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE FOR FINANCIAL ENGINEERING, PROCEEDINGS, 2003, : 1 - 8
  • [28] An Improvement on the Basic Least Squares Support Vector Machine Algorithm
    Chen Bocheng
    Li Yingjie
    2009 6TH INTERNATIONAL CONFERENCE ON SERVICE SYSTEMS AND SERVICE MANAGEMENT, VOLS 1 AND 2, 2009, : 779 - +
  • [29] Forest coverage prediction based on least squares support vector regression algorithm
    Xiao, Fang
    TRENDS IN CIVIL ENGINEERING, PTS 1-4, 2012, 446-449 : 2978 - 2982
  • [30] Prediction of building energy consumption using an improved real coded genetic algorithm based least squares support vector machine approach
    Jung, Hyun Chul
    Kim, Jin Sung
    Heo, Hoon
    ENERGY AND BUILDINGS, 2015, 90 : 76 - 84
12345