首页|Investigators at University of Cuenca Report Findings in Machine Learning (Enhan cing Runoff Forecasting Through the Integration of Satellite Precipitation Data and Hydrological Knowledge Into Machine Learning Models)
Investigators at University of Cuenca Report Findings in Machine Learning (Enhan cing Runoff Forecasting Through the Integration of Satellite Precipitation Data and Hydrological Knowledge Into Machine Learning Models)
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 – Current study results on Machine Learn ing have been published. According to newsreporting originating from Cuenca, Ec uador, by NewsRx correspondents, research stated, “In this study,we use feature engineering (FE) strategies to enhance the performance of machine learning (ML) modelsin forecasting runoff and peak runoff. We selected a 300-km2 tropical An dean catchment, representativeof rapid response systems where hourly runoff for ecasting is particularly challenging.”
CuencaEcuadorSouth AmericaCyborgsEmerging TechnologiesMachine LearningUniversity of Cuenca