首页|Investigators from Wageningen University and Research Center Have Reported New Data on Machine Learning (Machine-learned Actual Evapotranspiration for an Irrigated Pecan Orchard In North- west Mexico)
Investigators from Wageningen University and Research Center Have Reported New Data on Machine Learning (Machine-learned Actual Evapotranspiration for an Irrigated Pecan Orchard In North- west Mexico)
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
Elsevier
2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news reporting orig- inating from Wageningen, Netherlands, by NewsRx correspondents, research stated, “Accurate field-scale estimates of the actual evapotranspiration (ETact) based on readily available input data is indispensable to optimize irrigation in (semi-)arid regions. In this study, at an irrigated pecan orchard in Northwest Mexico we explored the potential for three different machine learning algorithms to improve upon the 30-min ETact estimates provided by the FAO Penman-Monteith method (FAO-PM) when trained and tested on multi-year eddy-covariance measurements.” Funders for this research include WIMEK graduate school (Wageningen University and Research, Netherlands), MEXCID.
WageningenNetherlandsEuropeCyborgsEmerging Tech- nologiesMachine LearningWageningen University and Research Center
NETL
NSTL
Elsevier
