Ruolin Li

Jul 30, 2024 | mdpi.com | Ruolin Li |Xiaoyan Ma

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May 10, 2023 | mdpi.com | Ruolin Li |Qi Feng |Yang Cui |Celestin Sindikubwabo

Abstract:Climate extremes pose significant natural threats to socioeconomic activities. Accurate prediction of short-term climate (STC) can provide relevant departments with warnings to effectively reduce this threat. To accurately predict STC in China, this study utilizes machine learning algorithms, particularly the random forest (RF) model, to evaluate the role of both natural and anthropogenic factors.