Cover Image

Improving the prediction of petroleum reservoir characterization with a stacked generalization ensemble model of support vector machines

The ensemble learning paradigm has proved to be relevant to solving most challenging industrial problems. Despite its successful application especially in the Bioinformatics, the petroleum industry has not benefited enough from the promises of this machine learning technology. The petroleum industry...

Full description

Saved in:

Bibliographic Details
Main Authors:	Fatai Adesina, Anifowose, Jane, Labadin, Abdulazeez, Abdulraheem
Format:	Article
Language:	English
Published:	Elsevier Ltd. 2015
Subjects:	T Technology (General) TJ Mechanical engineering and machinery
Online Access:	http://ir.unimas.my/id/eprint/12744/1/Improving-the-prediction-of-petroleum%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/12744/ https://www.scopus.com/record/display.uri?eid=2-s2.0-84912062615&origin=inward&txGid=0
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Hybrid of Functional Networks and Support Vector Machine Models for the Prediction of Petroleum Reservoir Properties
by: Fatai Adesina, Anifowose, et al.
Published: (2011)

Predicting Petroleum Reservoir Properties from Downhole Sensor Data using an Ensemble Model of Neural Networks
by: Fatai Adesina, Anifowose, et al.
Published: (2013)

Ensemble model of non-linear feature selection-based Extreme Learning Machine for improved natural gas reservoir characterization
by: Fatai Adesina, Anifowose, et al.
Published: (2015)

Ensemble learning model for petroleum reservoir characterization: A case of feed-forward back-propagation neural networks
by: Fatai, Anifowose, et al.
Published: (2013)

A least-square-driven functional networks type-2 fuzzy logic hybrid model for efficient petroleum reservoir properties prediction
by: Fatai Adesina, Anifowose, et al.
Published: (2013)

Hybrid intelligent systems in petroleum reservoir characterization and modeling: the journey so far and the challenges ahead
by: Fatai Adesina, Anifowose, et al.
Published: (2017)

Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques
by: Anifowose, Fatai Adesina
Published: (2015)

Ensemble model of Artificial Neural Networks with randomized number of hidden neurons
by: Fatai Adesina, Anifowose, et al.
Published: (2013)

An optimized ensemble for predicting reservoir rock properties in petroleum industry
by: Kenari, Seyed Ali Jafari
Published: (2013)

Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
by: Solihin M.I., et al.
Published: (2024)

Ensemble Feed-Forward Neural Network and Support Vector Machine for Prediction of Multiclass Malaria Infection
by: Jimoh, Rasheed Gbenga, et al.
Published: (2022)

FURIA stacking ensemble for ASD classification
by: Ainie Hayati, Noruzman, et al.
Published: (2022)

Ozone prediction based on support vector machine
by: Tanaskuli, M., et al.
Published: (2020)

Ozone prediction based on support vector machine
by: Tanaskuli M., et al.
Published: (2023)

Ensemble support vector machines and dempster-shafer evidence theory for machinery multi fault diagnosis
by: Hui, Kar Hoou
Published: (2019)

Prediction of ventricular fibrillation using support vector machine
by: Heng, Wei Wei, et al.
Published: (2020)

RESERVOIR PROPERTY PREDICTION FROM POST STACK SEISMIC INVERSION DATA
by: AUNG, HEIN HTET
Published: (2020)

RESERVOIR PROPERTY PREDICTION FROM POST STACK SEISMIC INVERSION DATA
by: AUNG, HEIN HTET
Published: (2020)

Enhanced Heterogeneous Stacked Ensemble Machine Learning Model For Detecting Nigerian Politically Motivated Cyberhate
by: Sallau, Mullah Nanlir
Published: (2023)

A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee
by: Wong , Wen Yee
Published: (2023)

Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS
by: Tehrany, Mahyat Shafapour, et al.
Published: (2014)

Experimenting the aplicability of support vector machine regression in rainfall prediction
by: Sulaiman, Junaida
Published: (2005)

Prediction of protein residue contact using support vector machine
by: Chan, Weng Howe, et al.
Published: (2012)

Prediction of protein residue contact using support vector machine
by: Chan, Weng Howe, et al.
Published: (2011)

Protein-protein interactions prediction using support vector machines
by: Ahmed Alashwal, Hany Taher
Published: (2007)

Carbon Dioxide Emission Prediction Using Support Vector Machine
by: Chairul, Saleh, et al.
Published: (2016)

Time series prediction using support vector machine (SVM)
by: Ng Li Koon
Published: (2023)

Petroleum reservoir analogues
by: Ganat, T.A.-A.O.
Published: (2020)

Forecasting photovoltaic power generation with a stacking ensemble model
by: Abdellatif, Abdallah, et al.
Published: (2022)

Manifestation of LiDAR-derived parameters in the spatial prediction of landslides using novel ensemble evidential belief functions and support vector machine models in GIS
by: Jebur, Mustafa Neamah, et al.
Published: (2014)

Flood susceptibility analysis and its verification using a novel ensemble support vector machine and frequency ratio method
by: Tehrany, Mahyat Shafapour, et al.
Published: (2015)

Ensemble based filter feature selection with harmonize Particle Swarm Optimization and Support Vector Machine for optimal cancer classification
by: Tengku Ab. Hamid, Tengku Mazlin, et al.
Published: (2021)

One-class support vector machines for protein-protein interactions prediction
by: Alashwal, H., et al.
Published: (2006)

Predicting uniaxial compressive strength using Support Vector Machine algorithm
by: Zakaria, Hafedz, et al.
Published: (2019)

The effect of kernel functions on cryptocurrency prediction using support vector machines
by: Hitam, Nor Azizah, et al.
Published: (2021)

The effect of Kernel functions on cryptocurrency prediction using support vector machines
by: Hitam, Nor Azizah, et al.
Published: (2022)

The effect of kernel functions on cryptocurrency prediction using support vector machines
by: Hitam, Nor Azizah, et al.
Published: (2022)

The effect of kernel functions on cryptocurrency prediction using support vector machines
by: Hitam, Nor Azizah, et al.
Published: (2021)

The effect of kernel functions on cryptocurrency prediction using support vector machines
by: Ismail, Amelia Ritahani, et al.
Published: (2022)

Soil liquefaction prediction based on bayesian optimization and support vector machines
by: Zhang, Xuesong, et al.
Published: (2022)