Hunan Electric Power ›› 2023, Vol. 43 ›› Issue (2): 108-111.doi: 10.3969/j.issn.1008-0198.2023.02.018

• Experience and Discussion • Previous Articles     Next Articles

Prediction of Power Transmission Project Cost Trend Based on Big Data

DENG Yiqing, SUN Bin, LI Xiaobing, LI Dan, WANG Rongjing   

  1. State Grid Shaanxi Electric Power Co., Ltd. Economic and Technical Research Institute, Xi′an 710075,China
  • Received:2022-11-29 Revised:2023-01-03 Online:2023-04-25 Published:2023-05-06

Abstract: In order to accurately predict the cost of power transmission and transformation projects, control the cost investment in the construction stage, and improve the utilization rate of funds,based on the actual cost data of power transmission and transformation projects in different cities in Shaanxi province, the key influencing factors of power grid project cost are screened by using the entropy weight method, and the BP neural network forecasting model is used to predict the cost of transmission and transformation projects effectively. The forecasting results confirm the validity of the model.

Key words: BP neural network, power transmission and transformation project, prediction model

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