首页|Hohai University Reports Findings in Machine Learning (Attribution of hydrologic al droughts in large river-connected lakes: Insights from an explainable machine learning model)
Hohai University Reports Findings in Machine Learning (Attribution of hydrologic al droughts in large river-connected lakes: Insights from an explainable machine learning model)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting from Nanjing, People’s Republ ic of China, by NewsRx journalists, research stated, “Large lakes play an import ant role in water resource supply, regional climate regulation, and ecosystem su pport, but they face threats from frequent extreme drought events, necessitating an understanding of the mechanisms behind these events. In this study, we devel oped an explainable machine learning (ML) model that combines the Bayesian optim ized (BO) long short-term memory (LSTM) model and the integrated gradients (IG) interpretation method to simulate and explain lake water level variations.”
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