Application Of Power-law Committee Machine To Combine Five Machine Learning Algorithms For Enhanced Oil Recovery Screening

This article discusses a new approach for enhanced oil recovery screening using a power-law committee machine (PLCM) that combines the predictions of five different machine learning methods. By utilizing a larger dataset and an additional input variable, this approach aims to overcome the class-imbalance issue and increase the generalization of the models. The study also investigates the impact of input parameters on EOR screening and identifies the most influential factors.