首页|Studies from University of Florence Have Provided New Information about Machine Learning (On the Use of Hydrodynamic Modelling and Random Forest Classifiers for the Prediction of Hypoxia In Coastal Lagoons)
Studies from University of Florence Have Provided New Information about Machine Learning (On the Use of Hydrodynamic Modelling and Random Forest Classifiers for the Prediction of Hypoxia In Coastal Lagoons)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on Machine Learning is now available. According to news reportingoriginating in Florence, Italy, by NewsR x journalists, research stated, “Hypoxia is one of the fundamentalthreats to wa ter quality globally, particularly for partially enclosed basins with limited wa ter renewal,such as coastal lagoons. This work proposes the combined use of a m achine learning technique, fieldobservations, and data derived from a hydrodyna mic and heat exchange numerical model to predict, andforecast up to 10 days in advance, the occurrence of hypoxia in a eutrophic coastal lagoon.”
FlorenceItalyEuropeCyborgsEmergi ng TechnologiesMachine LearningUniversity of Florence
NETL
NSTL
