首页|University of South China Reports Findings in Machine Learning (Comparative stud y of five machine learning algorithms on prediction of the height of the water-c onducting fractured zone in undersea mining)
University of South China Reports Findings in Machine Learning (Comparative stud y of five machine learning algorithms on prediction of the height of the water-c onducting fractured zone in undersea mining)
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 – New research on Machine Learning is the subject o f a report. According to news reporting from Hunan, People’s Republic of China, by NewsRx journalists, research stated, “Prediction of water-conducting fracture d zone (WCFZ) of mine overburden is the premise for reducing or eliminating wate r inrush hazards in undersea mining. To obtain a more robust and precise predict ion of WCFZ in undersea mining, a WCFZ prediction dataset with 122 cases of frac tured zones was constructed.”
HunanPeople’s Republic of ChinaAsiaAlgorithmsCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
