Robotics & Machine Learning Daily News2024,Issue(Apr.19) :21-22.

Studies from University of Tennessee at Knoxville Add New Findings in the Area o f Machine Learning (Predicting Silicate Glass Geochemistry Using Raman Spectrosc opy and Supervised Machine Learning: Partial Least Square Applications To Amorph ous …)

Robotics & Machine Learning Daily News2024,Issue(Apr.19) :21-22.

Studies from University of Tennessee at Knoxville Add New Findings in the Area o f Machine Learning (Predicting Silicate Glass Geochemistry Using Raman Spectrosc opy and Supervised Machine Learning: Partial Least Square Applications To Amorph ous …)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reportingoriginating from Knoxville, Tennesse e, by NewsRx correspondents, research stated, “Here, Raman spectroscopyis used to develop a univariate partial least squares (PLS) calibration capable of quant ifyinggeochemistry in synthetic and natural silicate glass samples. The calibra tion yields eight oxide-specificmodels that allow predictions of silicon dioxid e (SiO2), sodium oxide (Na2O), potassium oxide (K2O),calcium oxide (CaO), titan ium dioxide (TiO2), aluminum oxide (Al2O3), ferrous oxide (FeOT), andmagnesium oxide (MgO) (wt%) in glasses spanning a wide range of compositions, while also providingcorrelation-coefficient matrices that highlight the import ance of specific Raman channels in the regressionof a particular oxide.”

Key words

Knoxville/Tennessee/United States/Nor th and Central America/Chemistry/Cyborgs/Emerging Technologies/Geochemistry/Machine Learning/Minerals/Silicates/Silicic Acid/University of Tennessee at Knoxville

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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