首页|New Machine Learning Findings Reported from Kielce University of Technology (Exp loring Machine Learning Models To Predict the Unfrozen Water Content In Copper-c ontaminated Clays)
New Machine Learning Findings Reported from Kielce University of Technology (Exp loring Machine Learning Models To Predict the Unfrozen Water Content In Copper-c ontaminated Clays)
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 Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting originating from Kielce, Po land, by NewsRx correspondents, research stated, “The article provides new insig hts into predicting unfrozen water content(unf) n f ) in clays contaminated with copper. The objectives of this study included creating machine learning predict ion models based on Gaussian Process Regression (GPR), Support Vector Machine (S VM), and Random Forest (RF) algorithms.” Financial support for this research came from Faculty of Environmental Engineeri ng, Geomatics and Renewable Energy of the Kielce University of Technology.
KielcePolandEuropeCyborgsEmergin g TechnologiesMachine LearningKielce University of Technology
NETL
NSTL
