首页|Findings on Machine Learning Discussed by Investigators at Lanzhou University (M achine Learning-driven Optimization and Application of Bimetallic Catalysts In P eroxymonosulfate Activation for Degradation of Fluoroquinolone Antibiotics)
Findings on Machine Learning Discussed by Investigators at Lanzhou University (M achine Learning-driven Optimization and Application of Bimetallic Catalysts In P eroxymonosulfate Activation for Degradation of Fluoroquinolone Antibiotics)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Machine Learning are discussed in a new report. According to news reporting from Gansu, People’s Republic of China, by NewsRx journalists, research stated, “In this research, th e XGBoost (XGB) and CatBoost (CB) algorithms were utilized to examine the experi mental refinement and deployment of bimetallic catalysts for the activation of p eroxymonosulfate in the removal of fluoroquinolone antibiotics from aqueous solu tions. For the XGB model, shapley additive explanations analysis was utilized to provide model interpretability, identifying the features with significant impac t on model prediction.”
GansuPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningLanzhou University
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