A new machine learning ensemble model for class imbalance problem of screening enhanced oil recovery methods
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A new machine learning ensemble model for class imbalance problem of screening enhanced oil recovery methods
Authors
Keywords
Classification, Ensemble learning, EOR screening, Class imbalance problem, Mutual information, Hyper-parameter tuning
Journal
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
Volume 198, Issue -, Pages 108214
Publisher
Elsevier BV
Online
2020-12-05
DOI
10.1016/j.petrol.2020.108214
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Review on microbial enhanced oil recovery: Mechanisms, modeling and field trials
- (2020) Jianjie Niu et al. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
- Application of fuzzy decision tree in EOR screening assessment
- (2019) Nastaran Khazali et al. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
- Stacking Ensemble Learning for Short-Term Electricity Consumption Forecasting
- (2018) Federico Divina et al. Energies
- Interval Deep Generative Neural Network for Wind Speed Forecasting
- (2018) Mahdi Khodayar et al. IEEE Transactions on Smart Grid
- Structuring an artificial intelligence based decision making tool for cyclic steam stimulation processes
- (2017) Qian Sun et al. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
- A simple approach for screening enhanced oil recovery methods: Application of artificial intelligence
- (2016) Mohammad Ali Ahmadi et al. PETROLEUM SCIENCE AND TECHNOLOGY
- A Novel Enhanced-Oil-Recovery Screening Approach Based on Bayesian Clustering and Principal-Component Analysis
- (2016) Martina Siena et al. SPE RESERVOIR EVALUATION & ENGINEERING
- MV5: A Clinical Decision Support Framework for Heart Disease Prediction Using Majority Vote Based Classifier Ensemble
- (2014) Saba Bashir et al. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
- Efficient screening of enhanced oil recovery methods and predictive economic analysis
- (2014) Arash Kamari et al. NEURAL COMPUTING & APPLICATIONS
- Mutual Information between Discrete and Continuous Data Sets
- (2014) Brian C. Ross PLoS One
- Multi-class AdaBoost
- (2013) Trevor Hastie et al. Statistics and Its Interface
- A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches
- (2011) M. Galar et al. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND RE
- Analysis of EOR projects and updated screening criteria
- (2011) Ahmad Al Adasani et al. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
- A comparative assessment of ensemble learning for credit scoring
- (2010) Gang Wang et al. EXPERT SYSTEMS WITH APPLICATIONS
- Giant oil field decline rates and their influence on world oil production
- (2009) Mikael Höök et al. ENERGY POLICY
- CLASSIFICATION OF IMBALANCED DATA: A REVIEW
- (2009) YANMIN SUN et al. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationPublish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn More