首页|Centre de Recherche Reports Findings in Machine Learning (Groundwater salinity m odeling and mapping using machine learning approaches: a case study in Sidi Okba region, Algeria)
Centre de Recherche Reports Findings in Machine Learning (Groundwater salinity m odeling and mapping using machine learning approaches: a case study in Sidi Okba region, Algeria)
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 – New research on Machine Learning is th e subject of a report. According to newsreporting originating in Biskra, Algeri a, by NewsRx journalists, research stated, “The groundwater salinizationprocess complexity and the lack of data on its controlling factors are the main challen ges foraccurate predictions and mapping of aquifer salinity. For this purpose, effective machine learning (ML)methodologies are employed for effective modelin g and mapping of groundwater salinity (GWS) in theMio-Pliocene aquifer in the S idi Okba region, Algeria, based on limited dataset of electrical conductivity(E C) measurements and readily available digital elevation model (DEM) derivatives. ”
NETL
NSTL
