Radial basis function (RBF) network for modeling gasoline properties-Reference-Cited by-同舟云学术

Radial basis function (RBF) network for modeling gasoline properties

Published:2019-03-27 Issue:11 Volume:37 Page:1306-1313
ISSN:1091-6466
Container-title:Petroleum Science and Technology
language:en
Short-container-title:Petroleum Science and Technology

Author:

Tatar Afshin¹,Barati Ali¹,Najafi Adel¹,Mohammadi Amir H.¹

Affiliation:

1. Discipline of Chemical Engineering, School of Engineering, University of KwaZulu-Natal, Howard College Campus, Durban, South Africa

Publisher

Informa UK Limited

Subject

Geotechnical Engineering and Engineering Geology,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering,General Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/10916466.2019.1575878

Reference24 articles.

1. Application of radial basis function networks for solar-array modelling and maximum power-point prediction

2. Specific Gravity, RVP, Octane Number, and Saturates, Olefins, and Aromatics Fractional Composition of Gasoline and Petroleum Fractions by Neural Network Algorithms

3. Determination of ethanol and specific gravity in gasoline by distillation curves and multivariate analysis

4. Using the Doehlert matrix as a tool for studying the influence of gasoline components on octane numbers

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