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Journal Articles
- 2017
[j9]Anifowose Fatai
, Amar Khoukhi, Abdulazeez Abdulraheem:
Investigating the effect of training-testing data stratification on the performance of soft computing techniques: an experimental study. J. Exp. Theor. Artif. Intell. 29(3): 517-535 (2017)- 2015
- [j8]Anifowose Fatai, Jane Labadin, Abdulazeez Abdulraheem:
Improving the prediction of petroleum reservoir characterization with a stacked generalization ensemble model of support vector machines. Appl. Soft Comput. 26: 483-496 (2015) - 2014
- [j7]Hasan A. Nooruddin, Anifowose Fatai, Abdulazeez Abdulraheem:
Using soft computing techniques to predict corrected air permeability using Thomeer parameters, air porosity and grain density. Comput. Geosci. 64: 72-80 (2014) - [j6]Anifowose Fatai, Suli C. Adeniye, Abdulazeez Abdulraheem:
Recent advances in the application of computational intelligence techniques in oil and gas reservoir characterisation: a comparative study. J. Exp. Theor. Artif. Intell. 26(4): 551-570 (2014) - 2013
- [j5]Anifowose Fatai, Jane Labadin, Abdulazeez Abdulraheem:
A least-square-driven functional networks type-2 fuzzy logic hybrid model for efficient petroleum reservoir properties prediction. Neural Comput. Appl. 23(Supplement-1): 179-190 (2013) - 2011
- [j4]Tarek Helmy, Anifowose Fatai, Kanaan A. Faisal:
Corrigendum to "Hybrid computational models for the characterization of oil and gas reservoirs" [Experts Systems with Applications 36 (7) (2010) 5353-5363]. Expert Syst. Appl. 38(3): 2919 (2011) - [j3]Tarek Helmy, Anifowose Fatai, Kanaan A. Faisal:
Corrigendum to "Hybrid computational models for the characterization of oil and gas reservoirs" [Expert Systems with Applications 37 (2010) 5353-5363]. Expert Syst. Appl. 38(4): 4659 (2011) - 2010
- [j2]Tarek Helmy, Anifowose Fatai, Kanaan A. Faisal:
Hybrid computational models for the characterization of oil and gas reservoirs. Expert Syst. Appl. 37(7): 5353-5363 (2010) - [j1]Tarek Helmy, Anifowose Fatai:
Hybrid Computational Intelligence Models for Porosity and Permeability Prediction of Petroleum reservoirs. Int. J. Comput. Intell. Appl. 9(4): 313-337 (2010)
Conference and Workshop Papers
- 2013
- [c5]Anifowose Fatai, Jane Labadin, Abdulazeez Abdulraheem:
Predicting Petroleum Reservoir Properties from Downhole Sensor Data using an Ensemble Model of Neural Networks. MLSDA@AUS-AI 2013: 27 - [c4]Anifowose Fatai, Jane Labadin, Abdulazeez Abdulraheem:
Ensemble model of Artificial Neural Networks with randomized number of hidden neurons. CITA 2013: 1-5 - [c3]Anifowose Fatai, Jane Labadin, Abdulazeez Abdulraheem:
Ensemble Learning Model for Petroleum Reservoir Characterization: A Case of Feed-Forward Back-Propagation Neural Networks. PAKDD Workshops 2013: 71-82 - 2011
- [c2]Anifowose Fatai, Jane Labadin, Abdulazeez Abdulraheem:
A Hybrid of Functional Networks and Support Vector Machine models for the prediction of petroleum reservoir properties. HIS 2011: 85-90 - 2008
- [c1]Tarek Helmy, Anifowose Fatai, El-Sayed Sallam:
An Efficient Randomized Algorithm for Real-Time Process Scheduling in PicOS Operating System. SCSS (2) 2008: 117-122
Coauthor Index
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