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Climate Predictions Using Machine Learning Approaches

Maitituerdi Aihemaiti, Abuduaini Niyazi, Rexiati Dilimulati


In contrast to modern climate models, which predict that precipitation will increase as temperatures rise, the Horn of Africa has experienced severe and recurring droughts over the past few decades. The region's agriculture-based economies have suffered greatly as a result of these droughts. Therefore, the quality of long-term weather prediction has become fundamentally important. In this project, we use multiple past climate proxy records to build a machine learning model to determine whether we can predict the future climate of the Horn of Africa.

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