首页|New Machine Learning Findings Has Been Reported by Investigators at Huazhong Uni versity of Science and Technology (Coupling Swat and Lstm for Improving Daily St reamflow Simulation In a Humid and Semi-humid River Basin)
New Machine Learning Findings Has Been Reported by Investigators at Huazhong Uni versity of Science and Technology (Coupling Swat and Lstm for Improving Daily St reamflow Simulation In a Humid and Semi-humid River Basin)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ma chine Learning. According to news reporting originating in Wuhan, People's Repub lic of China, by NewsRx journalists, research stated, "Simulation of watershed s treamflow is essential for the prevention and control of flood and drought disas ters. To improve streamflow simulation, a coupled SWAT-LSTM model was constructe d by combining a conceptual processbased hydrological model-Soil and Water Asse ssment Tool (SWAT)-with a machine learning model-Long Short-Term Memory (LSTM)." Financial supporters for this research include National Key R&D Pro gram of China, Hubei Provincial Key Laboratory of Construction and Management in Hydropower Engineering, Three Gorges University, China, Science and Technology Plan Projects of Tibet Autonomous Region.
WuhanPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningHuazhong University of Scienc e and Technology
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