首页|Researchers from U.S. Geological Survey (USGS) Report on Findings in Machine Learning (Train, Inform, Borrow, or Combine? Approaches To Process-guided Deep Learning for Groundwaterinfluenced Stream Temperature Prediction)
Researchers from U.S. Geological Survey (USGS) Report on Findings in Machine Learning (Train, Inform, Borrow, or Combine? Approaches To Process-guided Deep Learning for Groundwaterinfluenced Stream Temperature Prediction)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learning have been published. According to newsreporting from East Hartford, Connecticut, by NewsRx journalists, research stated, “Although groundwaterdischarge is a critical stream temperature control process, it is not explicitly represented in many streamtemperature models, an omission that may reduce predictive accuracy, hinder management of aquatichabitat, and decrease user confidence.”
East HartfordConnecticutUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningU.S. Geological Survey (USGS)
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