首页|Studies in the Area of Machine Learning Reported from Chinese Academy of Science s (Integration of Machine Learning and Process-based Model Outputs Via Ensemble Kalman Filter Enhanced Space-time Modelling of Soil Organic Carbon In a Highly H uman ...)
Studies in the Area of Machine Learning Reported from Chinese Academy of Science s (Integration of Machine Learning and Process-based Model Outputs Via Ensemble Kalman Filter Enhanced Space-time Modelling of Soil Organic Carbon In a Highly H uman ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Machine Learning are discussed in a new report. According tonews reporting out of Nanjing, Peopl e’s Republic of China, by NewsRx editors, research stated, “Accurateprediction of soil organic carbon stock (SOCS) dynamics in areas with intensive human activ ities is crucialfor developing sustainable soil management practices and climat e change mitigation strategies. This studyinvestigated the spatiotemporal dynam ics of SOCS by collecting a total of 1219 topsoil samples in southernJiangsu Pr ovince of China in 1980, 2000 and 2015, and compared the performance of three pr edictivemodels: random forest (RF), RothC, and a hybrid model of RF-RothCEnKF.”
NanjingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningChinese Academy of Sciences
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