首页|Study Data from Faculty of Computer Science Update Knowledge of Machine Learning (Smiles-based Machine Learning Enables the Prediction of Corrosion Inhibition C apacity)
Study Data from Faculty of Computer Science Update Knowledge of Machine Learning (Smiles-based Machine Learning Enables the Prediction of Corrosion Inhibition C apacity)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - Investigators publish new report on Ma chine Learning. According to news originating from Semarang, Indonesia, by NewsR x correspondents, research stated, “This study explores the efficacy of using a simplified molecular input line entry system (SMILES) as the sole feature, repla cing quantum chemical properties (QCP), in predicting corrosion inhibition effic iency (CIE) for N-heterocyclic compounds. The gradient boosting regressor (GBR) model outperforms k-nearest neighbors (KNN), support vector regression (SVR), an d other models.”
SemarangIndonesiaAsiaCyborgsEmer ging TechnologiesMachine LearningFaculty of Computer Science
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