首页|Researchers at Islamic Azad University Target Machine Learning (Improving the st reamflow prediction accuracy in sparse data regions: a fresh perspective on inte grated hydrological-hydrodynamic and hybrid machine learning models)
Researchers at Islamic Azad University Target Machine Learning (Improving the st reamflow prediction accuracy in sparse data regions: a fresh perspective on inte grated hydrological-hydrodynamic and hybrid machine learning models)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on ar tificial intelligence. According to news reportingout of Marvdasht, Iran, by Ne wsRx editors, research stated, “Considering the differences and complexnonlinea r relationships of the observational data, this research integrated the hydrolog ical, hydrodynamicand time series models, including the SWAT+, MIKE21, VMD, SAR IMA, TCN and ADPSO, to increasethe accuracy and efficiency of streamflow simula tions by applying the water yield in scarce-data areas ofthe Doroodzan Reservoi r Dam, Iran.”
Islamic Azad UniversityMarvdashtIranCyborgsEmerging TechnologiesMachine Learning
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