摘要
综述国内碳排放预测方法的研究进展,并对统计方法、机器学习模型、混合模型及其他新型方法进行系统梳理,深入剖析各种方法的原理、优缺点及适用场合,探讨碳排放预测在数据质量、模型复杂性和政策不确定性等方面面临的挑战,并展望碳排放预测的未来研究方向,强调多学科交叉、新技术应用及不确定性分析在碳排放预测中的重要性,以期为我国碳排放预测技术的发展提供新思路。
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.
出处
《节能》
2025年第9期156-160,共5页
Energy Conservation
关键词
碳排放预测
统计方法
机器学习
混合方法
carbon emission prediction
statistical methods
machine learning
mixed methods
