Interpretable Feedforward Neural Network and XGBoost-Based Algorithms to Predict CO2 Solubility in Ionic Liquids
Ao Yang,
Shirui Sun,
Hongfu Mi
et al.
Abstract:This study investigates the efficacy of feedforward neural network and XGBoost models in screening ionic liquid solvents for CO 2 capture. Both models were integrated with either group contribution (GC), molecular structure descriptors (MSD), or hybrid GC−MSD, to enable performance comparisons. It was demonstrated that the XGBoost models performed better over feedforward neural network models, irrespective of descriptor types. Notably, the XGBoost−GC−MSD model outperformed the artificial neural network with gr… Show more
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