Product Quality Prediction of 95% Naphtha Cut Point in Crude Distillation Unit Using Artificial Neural Networks

Author:

Al-Shanableh FilizORCID

Publisher

Springer International Publishing

Reference15 articles.

1. BP Statistical Review of World Energy (2020). Accessed 17 Feb 2021, https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/statistical-review/bp-stats-review-2020-full-report.pdf

2. ASTM D86–20b, Standard Test Method for Distillation of Petroleum Products and Liquid Fuels at Atmospheric Pressure. ASTM International, West Conshohocken, PA (2020), www.astm.org

3. KH Bawazeer, A. Zilouchian, Prediction of crude oil production quality parameters using neural networks, in Proceedings of 1997 IEEE International Conference on Neural Networks, New Orleans (1997)

4. L.M. Ochoa-Estopier, M. Jobson, R. Smith, Operational optimization of crude oil distillation systems using artificial neural networks. Comput. Chem. Eng. 59, 178–185 (2013)

5. L.C.K. Liau, T.C.K. Yang, M.T. Tsai, Expert system of a crude oil distillation unit for process optimization using neural networks. Expert Syst. Appl. 2, 247–255 (2004)

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