首页|Data from Federal University of Technology Advance Knowledge in Machine Learning (Machine Learning Models and Computational Simulation Techniques for Prediction of Anti-corrosion Properties of Novel Benzimidazole Derivatives)
Data from Federal University of Technology Advance Knowledge in Machine Learning (Machine Learning Models and Computational Simulation Techniques for Prediction of Anti-corrosion Properties of Novel Benzimidazole Derivatives)
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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 originatingfrom Owerri, Nigeria, by NewsRx co rrespondents, research stated, “The present paper delves into thedevelopment of predictive models for the optimum prediction of inhibition efficiencies and ant i-corrosionproperties of newly designed benzimidazole compounds in an HCl mediu m. Density functional theory(DFT) was used to obtain the molecular descriptors. 17 descriptors considered as input variables werereduced to 9 after redundant variables were eliminated using the variance inflation factor (VIF).”
OwerriNigeriaAfricaCyborgsEmergi ng TechnologiesK-nearest NeighborMachine LearningFederal University of Tec hnology
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