首页|New Machine Learning Study Findings Have Been Reported by Investigators at Unive rsity of Lorraine (Inversion of Downhole Resistivity Properties Through Infrared Spectroscopy and Whole-rock Geochemistry Using Machine-learning)
New Machine Learning Study Findings Have Been Reported by Investigators at Unive rsity of Lorraine (Inversion of Downhole Resistivity Properties Through Infrared Spectroscopy and Whole-rock Geochemistry Using Machine-learning)
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 - Investigators discuss new findings in Machine Learning. According to news originatingfrom Vandoeuvre-les-Nancy, Franc e, by NewsRx correspondents, research stated, “The electrical propertiesof rock s are widely used in the geophysical exploration of natural resources, such as m inerals, hydrocarbonsand groundwater. In mining exploration, the primary goal i s to map electrically anomalous geologicalfeatures associated with different mi neralization styles, such as clay alteration haloes, metal oxides andsulphides, weathered crystalline rocks or fractured zones.”
Vandoeuvre-les-NancyFranceEuropeCh emistryCyborgsEmerging TechnologiesGeochemistryMachine LearningUnivers ity of Lorraine
NETL
NSTL
