Open AccessROP Prediction with Supervised Machine Learning; a Case Study
Author(s) -
Ganesha R Darmawan,
Dedi Irawan
Publication year - 2022
Publication title -
journal of earth energy engineering/journal of earth energy engineering
Language(s) - English
Resource type - Journals
eISSN - 2540-9352
pISSN - 2301-8097
DOI - 10.25299/jeee.2022.7772
Subject(s) - random forest , rate of penetration , drilling , gradient boosting , computer science , support vector machine , machine learning , boosting (machine learning) , drill , artificial intelligence , predictive modelling , penetration rate , petroleum engineering , engineering , mechanical engineering