Analysis of the Relationship Between Electricity Supply and Factors in China: Correlation Exploration and Random Forest Modelling

Abstract

This paper focuses on the relationship between China's electricity supply and various factors, and uses data preprocessing, Pearson correlation coefficient analysis, and random forest modelling to conduct the study. Firstly, through the preprocessing and visualisation analysis of the data of multiple indicators, including the selection of nine indicators such as wind power, nuclear power, thermal power and hydropower, etc., the study is carried out. Second, the Pearson correlation coefficient is applied in the correlation factor analysis, and it is pointed out that China's electricity supply is highly correlated with urbanisation degree, coal consumption and other indicators. Subsequently, a random forest model is used for modelling, and the basic process of random forest, the key steps of training decision trees and the analysis of prediction effect are introduced in detail. The final model demonstrates the importance of hydropower in China's electricity development trend, and predicts that China's electricity will be transformed to urbanisation and clean energy in the future.