Biomethane yield of delignified groundnut shell: A SHAP-based interpretability, clustering, and predictive modeling

Keyphrases

• Predictive Modeling 100%
• Shapley Additive Explanations 100%
• Model Interpretability 100%
• Biomethane Yield 100%
• Groundnut Shell 100%
• Delignified 100%
• Natural Deep Eutectic Solvents (NADES) 40%
• Ethyl 40%
• Glycerol 40%
• Choline Chloride 40%
• Anaerobic Digestion 40%
• Pretreatment Conditions 40%
• Deep Eutectic Solvent Pretreatment 40%
• Liquid-to-solid Ratio 40%
• R2 Value 20%
• Digestion 20%
• Nonlinearity 20%
• Performance Prediction 20%
• Machine Learning Models 20%
• XGBoost 20%
• Actionable Insights 20%
• Retention Time 20%
• Learning-based 20%
• Bioenergy Systems 20%
• K-means 20%
• Biomethane 20%
• Black Box 20%
• Lignocellulose 20%
• Traditional Machine Learning 20%
• Biorefinery 20%
• K-means Clustering 20%
• Data-driven Methods 20%
• Model Learning 20%
• Ensemble Learning 20%
• Lignocellulose Biomass 20%
• Importance Estimation 20%
• Biomethane Recovery 20%
• Feature Interpretation 20%
• Predictive Clustering 20%
• Major Challenges 20%
• Advanced Data 20%
• Dominant Drivers 20%
• Machine Learning Ensemble 20%

Chemical Engineering

• Glycerol 100%
• Anaerobic Digestion 100%
• Deep Eutectic Solvent 100%
• Learning System 50%
• Methane 50%
• Xgboost 50%