首页|Findings from Hefei University of Technology Reveals New Findings on Machine Lea rning (Comprehensive Electrochemical and Machine Learning-based Study of Rancidi ty In Four Edible Oils Over Various Storage Periods)
Findings from Hefei University of Technology Reveals New Findings on Machine Lea rning (Comprehensive Electrochemical and Machine Learning-based Study of Rancidi ty In Four Edible Oils Over Various Storage Periods)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented.According to news reporting out of Hefei, People’s Republic of China, by NewsRx editors, research stated, “This study investigates the rancidit y development in four edible oils (corn, mustard, soybean, and sunflower) over a 12-month storage period using a novel approach combining electrochemical techni ques and machine learning.Cyclic voltammetry, electrochemical impedance spectro scopy, and differential pulse voltammetry were employed to characterize oil oxid ation.”
HefeiPeople’s Republic of ChinaAsiaChemicalsCyborgsElectrochemicalsEmerging TechnologiesMachine LearningHefei University of Technology
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