首页|New Machine Learning Findings from Xi’an Shiyou University Described [Rapid Quantitative Analysis of Three Elements (Al, Mg and Fe) In Molten Zinc Bas ed On Laser-induced Breakdown Spectroscopy Combined With Machine Learning Algori thm]
New Machine Learning Findings from Xi’an Shiyou University Described [Rapid Quantitative Analysis of Three Elements (Al, Mg and Fe) In Molten Zinc Bas ed On Laser-induced Breakdown Spectroscopy Combined With Machine Learning Algori thm]
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - Current study results on Machine Learning have be en published. According to news reporting outof Xi’an, People’s Republic of Chi na, by NewsRx editors, research stated, “Hot-dip galvanizing representsone of t he most cost-effective methods for the prevention of metal corrosion, and is the refore employedextensively across a range of fields. Carrying out the research and development of technology and devices forquantitative analysis of chemical elements in hot-dip galvanising process can provide theoretical basis andtechni cal support for the efficiency of hot-dip galvanising process and reduction of e nergy consumption.”
Xi’anPeople’s Republic of ChinaAsiaAlgorithmsCyborgsEmerging TechnologiesMachine LearningXi’an Shiyou Univ ersity
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