An explainable ensemble machine learning model to elucidate the influential drilling parameters based on rate of penetration prediction
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Elsevier BV
Reference88 articles.
1. Drilling rate of penetration prediction of high-angled wells using artificial neural networks;Abbas;J. Energy Resour. Technol.,2019
2. A systematic and critical review on development of machine learning based-ensemble models for prediction of adsorption process efficiency;Abbasi;J. Clean. Prod.,2022
3. B-LIME: an improvement of LIME for interpretable deep learning classification of cardiac Arrhythmia from ECG signals;Abdullah;Processes,2023
4. Hyperparameter optimization using scikit-learn;Agrawal,2021
5. An assessment of ensemble learning approaches and single-based machine learning algorithms for the characterization of undersaturated oil viscosity;Akano;Beni-Suef University Journal of Basic and Applied Sciences,2022
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