Machine learning applications in power system fault diagnosis: Research advancements and perspectives

R Vaish, UD Dwivedi, S Tewari, SM Tripathi - Engineering Applications of …, 2021 - Elsevier
Newer generation sources and loads are posing new challenges to the conventional power
system protection schemes. Adaptive and intelligent protection methodology, based on …

A comparative performance assessment of optimized multilevel ensemble learning model with existing classifier models

M Kumar, K Bajaj, B Sharma, S Narang - Big Data, 2022 - liebertpub.com
To predict the class level of any classification problem, predictive models are used and
mostly a single predictive model is built to predict the class level of any classification …

Electric vehicle energy consumption prediction using stacked generalization: An ensemble learning approach

I Ullah, K Liu, T Yamamoto, M Zahid… - International Journal of …, 2021 - Taylor & Francis
In this paper, we present an ensemble stacked generalization (ESG) approach for better
prediction of electric vehicles (EVs) energy consumption. ESG is a weighted combination of …

Machine Learning in Oil and Gas Exploration-A Review

A Lawal, Y Yang, H He, NL Baisa - IEEE Access, 2024 - ieeexplore.ieee.org
A comprehensive assessment of machine learning applications is conducted to identify the
developing trends for Artificial Intelligence (AI) applications in the oil and gas sector …

Evaluation and development of a predictive model for geophysical well log data analysis and reservoir characterization: Machine learning applications to lithology …

A Mishra, A Sharma, AK Patidar - Natural Resources Research, 2022 - Springer
This work critically evaluated the applicability of machine learning methodology applied to
automated well log creation towards reliable lithology prediction and subsequent reservoir …

[HTML][HTML] A hybrid machine learning approach based study of production forecasting and factors influencing the multiphase flow through surface chokes

W Kaleem, S Tewari, M Fogat, DA Martyushev - Petroleum, 2024 - Elsevier
Surface chokes are widely utilized equipment installed on wellheads to control hydrocarbon
flow rates. Several correlations have been suggested to model the multiphase flow of oil and …

Lithofacies discrimination of the Ordovician unconventional gas-bearing tight sandstone reservoirs using a subtractive fuzzy clustering algorithm applied on the well …

A Cherana, L Aliouane, MZ Doghmane… - Journal of African Earth …, 2022 - Elsevier
The main objective of this paper is to prove the capability of the fuzzy clustering algorithm for
discriminating between lithofacies that are derived from the borehole log data of Ordovician …

A novel and efficient deep learning approach for COVID‐19 detection using X‐ray imaging modality

P Bhardwaj, A Kaur - International Journal of Imaging Systems …, 2021 - Wiley Online Library
With the exponential growth of COVID‐19 cases, medical practitioners are searching for
accurate and quick automated detection methods to prevent Covid from spreading while …

A comparative study of heterogeneous and homogeneous ensemble approaches for landslide susceptibility assessment in the Djebahia region, Algeria

Z Matougui, L Djerbal, R Bahar - Environmental Science and Pollution …, 2024 - Springer
This study aims to compare the performance of ensembles according to their inherent
diversity in the context of landslide susceptibility assessment. Heterogeneous and …

An assessment of ensemble learning approaches and single-based machine learning algorithms for the characterization of undersaturated oil viscosity

TT Akano, CC James - Beni-Suef University Journal of Basic and Applied …, 2022 - Springer
Background Prediction of accurate crude oil viscosity when pressure volume temperature
(PVT) experimental results are not readily available has been a major challenge to the …