首页|Researchers from Hebei Normal University Detail Findings in Machine Learning (In tegrating Machine Learning With Thermal-driven Analytical Energy Balance Model I mproved Terrestrial Evapotranspiration Estimation Through Enhanced Surface ...)
Researchers from Hebei Normal University Detail Findings in Machine Learning (In tegrating Machine Learning With Thermal-driven Analytical Energy Balance Model I mproved Terrestrial Evapotranspiration Estimation Through Enhanced Surface ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learn ing have been published. According to newsreporting out of Shijiazhuang, People ’s Republic of China, by NewsRx editors, research stated, “Globalevapotranspira tion modeling faces significant challenges in understanding the complex interpla y betweenaerodynamic and canopy-surface conductance, especially in water-scarce environments. To address thisissue, we developed a hybrid model called HSTIC b y integrating a machine learning (ML) model forestimating surface relative humi dity (RH0) into the analytically-driven Surface Temperature InitiatedClosure (S TIC) model, which is based on thermal remote sensing.”
ShijiazhuangPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningRemote SensingHebei Normal University
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