Comparative study of machine learning algorithms in predicting asphaltene precipitation with a novel validation technique
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences
Link
https://link.springer.com/content/pdf/10.1007/s12145-023-01075-8.pdf
Reference74 articles.
1. Ahmadi MA (2011) Prediction of asphaltene precipitation using artificial neural network optimized by imperialist competitive algorithm. J Pet Explor Prod Technol 1:99–106. https://doi.org/10.1007/s13202-011-0013-7
2. Ahmadi MA (2012) Neural network based unified particle swarm optimization for prediction of asphaltene precipitation. Fluid Phase Equilib 314:46–51. https://doi.org/10.1016/j.fluid.2011.10.016
3. Ahmadi MA, Ebadi M (2014) Evolving smart approach for determination dew point pressure through condensate gas reservoirs. Fuel 117:1074–1084. https://doi.org/10.1016/j.fuel.2013.10.010
4. Ahmadi P, Aghajanzadeh M, Asaadian H et al (2022) Ion-mediated desorption of asphaltene molecules from carbonate and sandstone structures. Mater Res Express 9:65101. https://doi.org/10.1088/2053-1591/ac784f
5. Ashoori S, Abedini A, Abedini R, Nasheghi KQ (2010) Comparison of scaling equation with neural network model for prediction of asphaltene precipitation. J Pet Sci Eng 72:186–194. https://doi.org/10.1016/j.petrol.2010.03.016
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