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نمایش تعداد 1-10 از 13

Fuzzy logic-driven and SVM-driven hybrid computational intelligence models applied to oil and gas reservoir characterization

نوع: Journal Paper

نویسنده : Fatai Anifowose; Abdulazeez Abdulraheem

سال: 2011

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Modeling the permeability of carbonate reservoir using type-2 fuzzy logic systems

نوع: Journal Paper

نویسنده : Sunday Olusanya Olatunji; Ali Selamat; Abdulazeez Abdulraheem

ناشر: Elsevier Science

سال: 2011

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Non-linear feature selection-based hybrid computational intelligence models for improved natural gas reservoir characterization

نوع: Journal Paper

نویسنده : Fatai Adesina Anifowose; Jane Labadin; Abdulazeez Abdulraheem

سال: 2014

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Using soft computing techniques to predict corrected air permeability using Thomeer parameters, air porosity and grain density

نوع: Journal Paper

نویسنده : Hasan A. Nooruddin; Fatai Anifowose; Abdulazeez Abdulraheem

سال: 2014

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Recent advances in the application of computational intelligence techniques in oil and gas reservoir characterisation: a comparative study

نوع: Journal Paper

نویسنده : Fatai Anifowose; Suli Adeniye; Abdulazeez Abdulraheem

سال: 2014

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

نوع: Journal Paper

نویسنده : Fatai Anifowose; Jane Labadin; Abdulazeez Abdulraheem

سال: 2015

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Ensemble model of non-linear feature selection-based Extreme Learning Machine for improved natural gas reservoir characterization

نوع: Journal Paper

نویسنده : Fatai Adesina Anifowose; Jane Labadin; Abdulazeez Abdulraheem

سال: 2015

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A hybrid model through the fusion of type-2 fuzzy logic systems and extreme learning machines for modelling permeability prediction

نوع: Journal Paper

نویسنده : S.O. Olatunji; Ali Selamat; Abdulazeez Abdulraheem

سال: 2012

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Integrating seismic and log data for improved petroleum reservoir properties estimation using non-linear feature-selection based hybrid computational intelligence models

نوع: Journal Paper

نویسنده : Fatai Anifowose; Suli Adeniye; Abdulazeez Abdulraheem; Abdullatif Al-Shuhail

سال: 2016

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Development of a new correlation to determine the static Young’s modulus

نوع: Journal Paper

نویسنده : Salaheldin Elkatatny; Mohamed Mahmoud; Ibrahim Mohamed; Abdulazeez Abdulraheem

سال: 2017

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Fuzzy logic-driven and SVM-driven hybrid computational intelligence models applied to oil and gas reservoir characterization

Modeling the permeability of carbonate reservoir using type-2 fuzzy logic systems

Non-linear feature selection-based hybrid computational intelligence models for improved natural gas reservoir characterization

Using soft computing techniques to predict corrected air permeability using Thomeer parameters, air porosity and grain density

Recent advances in the application of computational intelligence techniques in oil and gas reservoir characterisation: a comparative study

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

Ensemble model of non-linear feature selection-based Extreme Learning Machine for improved natural gas reservoir characterization

A hybrid model through the fusion of type-2 fuzzy logic systems and extreme learning machines for modelling permeability prediction

Integrating seismic and log data for improved petroleum reservoir properties estimation using non-linear feature-selection based hybrid computational intelligence models

Development of a new correlation to determine the static Young’s modulus

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Fuzzy logic-driven and SVM-driven hybrid computational intelligence models applied to oil and gas reservoir characterization

Modeling the permeability of carbonate reservoir using type-2 fuzzy logic systems

Non-linear feature selection-based hybrid computational intelligence models for improved natural gas reservoir characterization

Using soft computing techniques to predict corrected air permeability using Thomeer parameters, air porosity and grain density

Recent advances in the application of computational intelligence techniques in oil and gas reservoir characterisation: a comparative study

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

Ensemble model of non-linear feature selection-based Extreme Learning Machine for improved natural gas reservoir characterization

A hybrid model through the fusion of type-2 fuzzy logic systems and extreme learning machines for modelling permeability prediction

Integrating seismic and log data for improved petroleum reservoir properties estimation using non-linear feature-selection based hybrid computational intelligence models

Development of a new correlation to determine the static Young’s modulus