首页|University of Southern Florida Details Findings in Machine Learning (Leveraging Explainable Machine Learning for Enhanced Management of Lake Water Quality)
University of Southern Florida Details Findings in Machine Learning (Leveraging Explainable Machine Learning for Enhanced Management of Lake Water Quality)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Machine Learning is th e subject of a report. According to newsreporting from Tampa, Florida, by NewsR x journalists, research stated, “Freshwater lakes worldwide sufferfrom eutrophi cation caused by excessive nutrient loads, particularly nitrogen (N) and phospho rus (P)from wastewater and runoff, affecting aquatic life and public health. Us ing a large (1800 km2) subtropicallake as an example (Lake Okeechobee, Florida, USA), this study aims to (1) predict key water qualityparameters using machine learning (ML) algorithms based on easily measurable variables, (2) identify spatial patterns of these parameters, and (3) determine environmental drivers influ encing turbidity levels.”
TampaFloridaUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningUniversity o f Southern Florida
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