The Prediction of Undersaturated Crude Oil Viscosity: An Artificial Neural Network and Fuzzy Model Approach

ISSN： 1091-6466

Source： Petroleum Science and Technology, Vol.30, Iss.19, 2012-07, pp. : 2008-2021

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

The Artificial Neural Network's Prediction of Crude Oil Viscosity for Pipeline Safety

By Obanijesu E. O.

Petroleum Science and Technology, Vol. 27, Iss. 4, 2009-01 ,pp. : 412-426

Taylor & Francis Ltd

Access to resources Recommend Favorite

The Development of an Artificial Neural Network Model for Prediction of Crude Oil Viscosities

By Torabi F.

Petroleum Science and Technology, Vol. 29, Iss. 8, 2011-01 ,pp. : 804-816

Taylor & Francis Ltd

Access to resources Recommend Favorite

Viscosity prediction of CRM binders using artificial neural network approach

By Xiao Feipeng Putman Bradley J. Amirkhanian Serji N.

International Journal of Pavement Engineering, Vol. 12, Iss. 5, 2011-10 ,pp. : 485-495

Taylor & Francis Ltd

Access to resources Recommend Favorite

Artificial Neural Network's Prediction of Wax Deposition Potential of Nigerian Crude Oil for Pipeline Safety

By Obanijesu E. O.

Petroleum Science and Technology, Vol. 26, Iss. 16, 2008-01 ,pp. : 1977-1991

Taylor & Francis Ltd

Access to resources Recommend Favorite

Prediction of Undersaturated Crude Oil Density Using Gaussian Process Regression

By Rostami H. Azin R. Dianat R.

Petroleum Science and Technology, Vol. 31, Iss. 4, 2013-02 ,pp. : 418-427

Taylor & Francis Ltd

Access to resources Recommend Favorite