Predicting Phase Equilibria of CO2 Hydrate in Complex Systems Containing Salts and Organic Inhibitors for CO2 Storage: A Machine Learning Approach
Junghoon Mok,
Woojin Go,
Yongwon Seo
Abstract:In this study, 13 machine learning (ML) models were employed
to
predict the phase equilibrium temperatures of the CO2 hydrate
in systems with salts and organic inhibitors: Multiple Linear Regression
(MLR), Support Vector Regression (SVR), k-Nearest Neighbors (KNN),
Multi-Layer Perceptron (MLP), Decision Tree (DT), Random Forest (RF),
Extra Trees (ET), Adaptive Boosting (AdaBoost), Categorical Boosting
(CatBoost), Gradient Boosting Machine (GBM), Light Gradient Boosting
Machine (LGBM), Histogram-Based Gradient … Show more
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