首页|New Machine Learning Study Results from Zhejiang University Described (Predictin g Sulfide Precipitation In Magma Oceans On Earth, Mars and the Moon Using Machin e Learning)
New Machine Learning Study Results from Zhejiang University Described (Predictin g Sulfide Precipitation In Magma Oceans On Earth, Mars and the Moon Using Machin e Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning are pre sented in a new report. According to news reporting out of Hangzhou, People’s Re public of China, by NewsRx editors, research stated, “The sulfur content at sulf ide saturation (SCSS) of a silicate melt can regulate the stability of sulfides and, therefore, chalcophile elements’ behaviors in planetary magma oceans. Many studies have reported high-pressure experiments to determine SCSS using either l inear or exponential regressions to parameterize the thermodynamics of the syste m.” Financial supporters for this research include Fundamental Research Funds for th e Central Universities, National Natural Science Foundation of China (NSFC).
HangzhouPeople’s Republic of ChinaAs iaCyborgsEmerging TechnologiesMachine LearningZhejiang University
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