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)
由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-调查人员发布马学习的新报告。根据消息来源来自尼日利亚奥韦里的NewsRx Co Rresponders的研究表明：“本文深入研究了缓蚀性能和抗腐蚀性能预测模型的建立盐酸介质中新型苯并咪唑化合物的性质密度泛函理论利用(DFT)获得分子描述符。17个描述符被视为输入变量在使用方差膨胀系数(VIF)消除冗余变量后，减少到9个。
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 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).”
Key words
Owerri/Nigeria/Africa/Cyborgs/Emergi ng Technologies/K-nearest Neighbor/Machine Learning/Federal University of Tec hnology
NETL
NSTL