XGBoost performance in predicting corrosion inhibition efficiency of Benzimidazole Compounds
DR Ningtias, M Akrom - Journal of Multiscale Materials …, 2024 - dl.futuretechsci.org
In this study, we compare the performance of the XGBoost model with a Support Vector
Machine (SVM) model from the literature in predicting a given task. Performance metrics …
Machine (SVM) model from the literature in predicting a given task. Performance metrics …
Investigation of an amino acid compound as a corrosion inhibitor via ensemble learning
A Lingga Dewi, M Akrom - Journal of Multiscale Materials …, 2024 - dl.futuretechsci.org
In this study, we evaluate the performance of various machine learning models, including
Random Forest (RF), Bagging (BAG), AdaBoost (ADA), Artificial Neural Network (ANN), and …
Random Forest (RF), Bagging (BAG), AdaBoost (ADA), Artificial Neural Network (ANN), and …
Variational quantum algorithm for forecasting drugs for corrosion inhibitor
This study explores the development and evaluation of a Variational Quantum Algorithm
(VQA) for predicting a drug as a corrosion inhibitor, highlighting its advantages over …
(VQA) for predicting a drug as a corrosion inhibitor, highlighting its advantages over …
[PDF][PDF] Journal of Multiscale Materials Informatics
M Akrom - Journal of Multiscale Materials Informatics, 2024 - researchgate.net
Quantum computing has emerged as a promising technology capable of solving complex
computational problems more efficiently than classical computers. Among the various …
computational problems more efficiently than classical computers. Among the various …
[PDF][PDF] Journal of Multiscale Materials Informatics
GA Trisnapradika, M Akrom - Journal of Multiscale …, 2024 - pdfs.semanticscholar.org
This study investigates machine learning-based quantitative structure-property relationship
(QSPR) models for predicting the thermal stability of zinc metal-organic frameworks (Zn …
(QSPR) models for predicting the thermal stability of zinc metal-organic frameworks (Zn …
[引用][C] Investigation of Corrosion Inhibition Efficiency of Pyridine-Quinoline Compounds through Machine Learning
[引用][C] Development of a Machine Learning Model to Predict the Corrosion Inhibition Ability of Benzimidazole Compounds
AN Safitri, GA Trisnapradika, AW Kurniawan… - Journal of Multiscale …, 2024