摘要
Abstract
This paper reviews the research progress of domestic carbon emission prediction methods,systematically sorts out statistical methods,machine learning models,hybrid models and other new methods,deeply analyzes the principles,advantages and disadvantages,and applicable scenarios of various methods,discusses the challenges faced by carbon emission prediction in terms of data quality,model complexity and policy uncertainty,and looks forward to the future research directions of carbon emission prediction.Emphasize the significance of multidisciplinary integration,new technology application and uncertainty analysis in carbon emission prediction,with the aim of providing new ideas for the development of carbon emission prediction technology in China.关键词
碳排放预测/统计方法/机器学习/混合方法Key words
carbon emission prediction/statistical methods/machine learning/mixed methods分类
环境科学
