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
  • [31] Safety Status Prediction Model of Transmission Tower Based on Improved Coati Optimization-Based Support Vector Machine
    Gong, Xinxi
    Zhu, Yaozhong
    Wang, Yanhai
    Li, Enyang
    Zhang, Yuhao
    Zhang, Zilong
    BUILDINGS, 2024, 14 (12)
  • [32] Corporate Misconduct Prediction with Support Vector Machine in the Construction Industry
    Wang, Ran
    Lee, Chia-Jung
    Hsu, Shu-Chien
    Lee, Cheng-Yu
    JOURNAL OF MANAGEMENT IN ENGINEERING, 2018, 34 (04)
  • [33] Study on refined control and prediction model of district heating station based on support vector machine
    Yuan, Jianjuan
    Wang, Chendong
    Zhou, Zhihua
    ENERGY, 2019, 189
  • [34] Wind Power Prediction Based On Improved Genetic Algorithm and Support Vector Machine
    Zhang, Li
    Wang, Kui
    Lin, Wenli
    Geng, Tianxiang
    Lei, Zhen
    Wang, Zheng
    2018 4TH INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND MATERIAL APPLICATION, 2019, 252
  • [35] Photovoltaic Power Prediction Based on Principal Component Analysis and Support Vector Machine
    Song Qijun
    Li Fen
    Qian Jialin
    Zhao Jinbin
    Chen Zhenghong
    2016 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT-ASIA), 2016, : 815 - 820
  • [36] Support vector machine based prediction of photovoltaic module and power station parameters
    Ahmad, Ashfaq
    Jin, Yi
    Zhu, Changan
    Javed, Iqra
    Akram, M. Waqar
    Buttar, Noman Ali
    INTERNATIONAL JOURNAL OF GREEN ENERGY, 2020, 17 (03) : 219 - 232
  • [37] Intelligent Prediction of Transmission Line Project Cost Based on Least Squares Support Vector Machine Optimized by Particle Swarm Optimization
    Yi, Tao
    Zheng, Hao
    Tian, Yu
    Liu, Jin-peng
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2018, 2018
  • [38] Construction Cost Prediction of Main Tunnel in Railway Tunnel Based on Support Vector Machine
    Liu, Shaofei
    Hou, Dashan
    Journal of Railway Engineering Society, 2022, 39 (05) : 108 - 113
  • [39] Study on the VaR model based on the simulation of Support Vector Machine
    Zhang, Guo-Yong
    PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2007, : 2740 - 2744
  • [40] Application of improved support vector machine model in fault diagnosis and prediction of power transformers
    Wang Y.
    Advanced Control for Applications: Engineering and Industrial Systems, 2024, 6 (04):