首页|University of Georgia Researcher Discusses Research in Machine Learning (Groundw ater Level Prediction Using Machine Learning and Geostatistical Interpolation Mo dels)
University of Georgia Researcher Discusses Research in Machine Learning (Groundw ater Level Prediction Using Machine Learning and Geostatistical Interpolation Mo dels)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news reporting originating from Athens, Geor gia, by NewsRx correspondents, research stated, “Given the vulnerability of surf ace water to the direct impacts of climate change, the accurate prediction of gr oundwater levels has become increasingly important, particularly for dry regions , offering significant resource management benefits.” Funders for this research include Department of Geology, The University of Georg ia. Our news editors obtained a quote from the research from University of Georgia: “This study presents the first statewide groundwater level anomaly (GWLA) predic tion for Arizona across its two distinct aquifer types-unconsolidated sand and g ravel aquifers and rock aquifers. Machine learning (ML) models were combined wit h empirical Bayesian kriging (EBK) geostatistical interpolation models to predic t monthly GWLAs between January 2010 and December 2019. Model evaluations were b ased on the Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2 ) metrics.”
University of GeorgiaAthensGeorgiaUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachin e Learning
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