Research on the Forecast Model of Transmission and Distribution Project Cost Based on Support Vector Regression Algorithm. Issue 4 (March 2021)

• Record Type: Journal Article
• Authors: Zhou, Ming; Lu, Shengwei; Ma, Li; Ming, Yue; Sun, Li-ping; Zhou, Qiupeng; Wang, Sicong; Yan, Jiong
• Is Part Of: IOP conference series. Volume 714:Issue 4(2021)
• Publication Date: 2021-03
• Subjects: Transformer Substation -- Neural Network -- Investment Plan -- Investment Surplus Rate.; Earth sciences -- Periodicals; Environmental sciences -- Congresses; Environmental sciences -- Periodicals; 550.5
• DOI: 10.1088/1755-1315/714/4/042009
• Languages: English
• ISSNs: 1755-1307

Abstract

Abstract: Based on historical power transmission and transformation project data, this paper constructs a support vector regression forecasting model by screening the key influencing factors of power transmission and transformation projects, and then predicts the cost of power transmission and transformation projects above 110kV in a certain province. The results show that the support vector regression forecasting model can quickly predict the project cost of power transmission and transformation projects by inputting key factors of the project. The establishment of this prediction model provides a more scientific basis for rationally controlling the cost of power transmission and transformation projects.