Forecasting PVT properties of crude oil systems based on support vector machines modeling scheme

Journal of Petroleum Science and Engineering ◽

10.1016/j.petrol.2008.12.006 ◽

2009 ◽

Vol 64 (1-4) ◽

pp. 25-34 ◽

Author(s):

Emad A. El-Sebakhy

Keyword(s):

Support Vector Machines ◽

Crude Oil ◽

Support Vector ◽

Pvt Properties ◽

Vector Machines

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Support Vector Machines Framework for Predicting the PVT Properties of Crude Oil Systems

10.2118/105698-ms ◽

2007 ◽

Author(s):

Emad Ahmed El-Sebakhy ◽

Tarek Sheltami ◽

Said Y. Al-Bokhitan ◽

Yasser Shaaban ◽

Putu D. Raharja ◽

...

Keyword(s):

Support Vector Machines ◽

Crude Oil ◽

Support Vector ◽

Pvt Properties ◽

Vector Machines

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Prediction of PVT properties in crude oil systems using support vector machines

2009 3rd International Conference on Energy and Environment (ICEE) ◽

10.1109/iceenviron.2009.5398681 ◽

2009 ◽

Author(s):

Jawad Nagi ◽

Tiong Sieh Kiong ◽

Syed Khaleel Ahmed ◽

Farrukh Nagi

Keyword(s):

Support Vector Machines ◽

Crude Oil ◽

Support Vector ◽

Pvt Properties ◽

Vector Machines

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Electric energy forecasting in crude oil processing using Support Vector Machines and Particle Swarm Optimization

2008 9th Symposium on Neural Network Applications in Electrical Engineering ◽

10.1109/neurel.2008.4685568 ◽

2008 ◽

Author(s):

Milena Petrujkic ◽

Milan R. Rapaic ◽

Boris Jakovljevic ◽

Vesna Dapic

Keyword(s):

Particle Swarm Optimization ◽

Support Vector Machines ◽

Crude Oil ◽

Electric Energy ◽

Particle Swarm ◽

Support Vector ◽

Energy Forecasting ◽

Swarm Optimization ◽

Oil Processing ◽

Vector Machines

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Intelligent prediction of crude oil price using Support Vector Machines

2011 IEEE 9th International Symposium on Applied Machine Intelligence and Informatics (SAMI) ◽

10.1109/sami.2011.5738868 ◽

2011 ◽

Author(s):

Adnan Khashman ◽

Nnamdi I. Nwulu

Keyword(s):

Support Vector Machines ◽

Crude Oil ◽

Oil Price ◽

Support Vector ◽

Crude Oil Price ◽

Vector Machines

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DAILY CRUDE OIL PRICE FORECASTING MODEL USING ARIMA, GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTIC AND SUPPORT VECTOR MACHINES

American Journal of Applied Sciences ◽

10.3844/ajassp.2014.425.432 ◽

2014 ◽

Vol 11 (3) ◽

pp. 425-432 ◽

Author(s):

Ahmed

Keyword(s):

Support Vector Machines ◽

Crude Oil ◽

Oil Price ◽

Support Vector ◽

Forecasting Model ◽

Price Forecasting ◽

Crude Oil Price ◽

Vector Machines

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A New Method for Crude Oil Price Forecasting Based on Support Vector Machines

Computational Science – ICCS 2006 - Lecture Notes in Computer Science ◽

10.1007/11758549_63 ◽

2006 ◽

pp. 444-451 ◽

Author(s):

Wen Xie ◽

Lean Yu ◽

Shanying Xu ◽

Shouyang Wang

Keyword(s):

Support Vector Machines ◽

Crude Oil ◽

Oil Price ◽

Support Vector ◽

Price Forecasting ◽

Crude Oil Price ◽

Vector Machines

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Learning to Generate Optimized Term Weighting for Web Documents Classification - A Parallel Mimetic Approach Based on Support Vector Machines

International Review on Computers and Software (IRECOS) ◽

10.15866/irecos.v11i12.10964 ◽

2016 ◽

Vol 11 (12) ◽

pp. 1147

Author(s):

Abderrahmane Bendahmane ◽

Abdelkader Benyettou

Keyword(s):

Support Vector Machines ◽

Support Vector ◽

Term Weighting ◽

Web Documents ◽

Vector Machines

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Application of nonlinear feature extraction and least square support vector machines for fault diagnosis of chemical process

Journal of Computer Applications ◽

10.3724/sp.j.1087.2010.00236 ◽

2010 ◽

Vol 30 (1) ◽

pp. 236-239 ◽

Author(s):

Liang XU

Keyword(s):

Feature Extraction ◽

Fault Diagnosis ◽

Support Vector Machines ◽

Chemical Process ◽

Least Square ◽

Support Vector ◽

Vector Machines ◽

Nonlinear Feature Extraction ◽

Nonlinear Feature

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Combining Market and Accounting-Based Models for Credit Scoring Using a Classification Scheme Based on Support Vector Machines

SSRN Electronic Journal ◽

10.2139/ssrn.2156220 ◽

2012 ◽

Author(s):

Dimitrios Niklis ◽

Michael Doumpos ◽

C. Zopounidis

Keyword(s):

Support Vector Machines ◽

Classification Scheme ◽

Credit Scoring ◽

Support Vector ◽

Vector Machines

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Reconstructing U.S. Recession Probabilities Using Support Vector Machines

SSRN Electronic Journal ◽

10.2139/ssrn.2779889 ◽

2016 ◽

Author(s):

Roman Armani Garagulagian

Keyword(s):

Support Vector Machines ◽

Support Vector ◽

Vector Machines

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