Study on prediction model of construction period of power transmission and transformation project based on support vector machine

被引:0
|
作者
Yan, Qingmeng [1 ]
机构
[1] State Grid Fujian Power Co Ltd, Minist Construct, Fuzhou 350003, Fujian, Peoples R China
关键词
D O I
10.1088/1755-1315/446/4/042049
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
With the improvement of people's living standard, the demand for electric energy is increasingly strong. In order to meet the increasing load, the construction scale of power transmission and transformation project of power grid company is increasing, and the difficulty of progress control of power transmission and transformation project is increasing. In order to control the progress of power transmission and transformation projects, it is necessary to make an accurate and reasonable time prediction to make a realistic and feasible schedule. Firstly, this paper analyses the influencing factors of the construction period of power transmission and transformation projects, and determines the key decision factors. Based on the support vector machine method, a prediction model of the construction period of power transmission and transformation projects is established. The prediction accuracy reaches 95.50%, with high accuracy.
引用
收藏
页数:5
相关论文
共 50 条
  • [21] Fault prediction approach for power transformer based on support vector machine
    Zhu, Yong-Li
    Zhao, Wen-Qing
    Zhai, Xue-Ming
    Zhang, Xiao-Qi
    2007 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION, VOLS 1-4, PROCEEDINGS, 2007, : 1457 - 1461
  • [22] Solar Power Prediction Based on Satellite Images and Support Vector Machine
    Jang, Han Seung
    Bae, Kuk Yeol
    Park, Hong-Shik
    Sung, Dan Keun
    IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2016, 7 (03) : 1255 - 1263
  • [23] Water Quality Prediction Based on Improved Wavelet Transformation and Support Vector Machine
    Liu, Wen
    Wang, Guoyin
    Fu, Jianyu
    Zou, Xuan
    ADVANCES IN ENVIRONMENTAL TECHNOLOGIES, PTS 1-6, 2013, 726-731 : 3547 - +
  • [24] An Improved Support Vector Machine based on Rough Set for Construction Cost Prediction
    Ma HongWei
    2009 INTERNATIONAL FORUM ON COMPUTER SCIENCE-TECHNOLOGY AND APPLICATIONS, VOL 2, PROCEEDINGS, 2009, : 3 - 6
  • [25] Study on Tendency Prediction of Power-Shift Steering Transmission Based on Support Vector Regression
    Zhang, Yingfeng
    Ma, Biao
    Fang, Jing
    Zhang, Hailing
    INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL, 2010, 13 (06): : 1939 - 1946
  • [26] A New Hybrid Model Based on Least Squares Support Vector Machine for Project Selection Problem in Construction Industry
    Behnam Vahdani
    S. Meysam Mousavi
    H. Hashemi
    M. Mousakhani
    S. Ebrahimnejad
    Arabian Journal for Science and Engineering, 2014, 39 : 4301 - 4314
  • [27] A New Hybrid Model Based on Least Squares Support Vector Machine for Project Selection Problem in Construction Industry
    Vahdani, Behnam
    Mousavi, S. Meysam
    Hashemi, H.
    Mousakhani, M.
    Ebrahimnejad, S.
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2014, 39 (05) : 4301 - 4314
  • [28] Dynamic prediction of project success using evolutionary support vector machine inference model
    Cheng, Min-Yuan
    Wu, Yu-Wei
    25TH INTERNATIONAL SYMPOSIUM ON AUTOMATION AND ROBOTICS IN CONSTRUCTION - ISARC-2008, 2008, : 452 - 458
  • [29] Based on Rough Set and Support Vector Machine (SVM) in Jilin Province Power Distribution Network Transformation Project Evaluation
    Min, Liu
    Li, Cong
    Kai, Zhu
    Du Qiushi
    2013 12TH INTERNATIONAL SYMPOSIUM ON DISTRIBUTED COMPUTING AND APPLICATIONS TO BUSINESS, ENGINEERING & SCIENCE (DCABES), 2013, : 202 - 206
  • [30] A Prediction Model of Ice Thickness Based on Grey Support Vector Machine
    Ma Xiao-min
    Gao Jian
    Wu Chi
    He Rui
    Gong Yi-yu
    Li Yi
    Wu Tian-bao
    2016 IEEE INTERNATIONAL CONFERENCE ON HIGH VOLTAGE ENGINEERING AND APPLICATION (ICHVE), 2016,