首页|Studies from Beijing Normal University Add New Findings in the Area of Machine L earning (A Machine Learning Downscaling Framework Based On a Physically Constrai ned Sliding Window Technique for Improving Resolution of Global Water Storage An omaly)
Studies from Beijing Normal University Add New Findings in the Area of Machine L earning (A Machine Learning Downscaling Framework Based On a Physically Constrai ned Sliding Window Technique for Improving Resolution of Global Water Storage An omaly)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning are pre sented in a new report. According to news reporting from Beijing, People’s Repub lic of China, by NewsRx journalists, research stated, “Terrestrial water storage anomaly (TWSA) and groundwater storage anomaly (GWSA) data are of great importa nce for hydrological research and water resource management. However, products d erived from the Gravity Recovery and Climate Experiment (GRACE) mission and its Follow-On mission (GRACE-FO) are constrained by the satellite design and variati on in processing strategies among different institutions, resulting in multiple suboptimal products.”
BeijingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningBeijing Normal University
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