摘要：Under the new situation, with the continuous development of my country's economy and the implementation of power system reforms, higher development requirements have been put forward for the distribution network investment plan. Through the scientific and reasonable calculation of the investment scale of the distribution network, optimizing the investment scale of the distribution network and rationally arranging the investment planning of the distribution network project have become one of the key concerns of the current power grid enterprises. This paper uses fishbone diagram theory to analyze the factors that affect the investment scale of the distribution network, and selects the key factor indicators to construct a distribution network investment trend prediction model based on support vector machines. By selecting a certain region's distribution network investment for empirical forecasting analysis, and comparing with the planned investment of the distribution network in the region, the validity of the model is verified.
其他摘要：Under the new situation, with the continuous development of my country's economy and the implementation of power system reforms, higher development requirements have been put forward for the distribution network investment plan. Through the scientific and reasonable calculation of the investment scale of the distribution network, optimizing the investment scale of the distribution network and rationally arranging the investment planning of the distribution network project have become one of the key concerns of the current power grid enterprises. This paper uses fishbone diagram theory to analyze the factors that affect the investment scale of the distribution network, and selects the key factor indicators to construct a distribution network investment trend prediction model based on support vector machines. By selecting a certain region's distribution network investment for empirical forecasting analysis, and comparing with the planned investment of the distribution network in the region, the validity of the model is verified.
