Optimization of Distribution Control System in Oil Refinery by Applying Hybrid Machine Learning Techniques

Optimization of Distribution Control System in Oil Refinery by Applying Hybrid Machine Learning Techniques

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In this research, prediction of crude oil cuts from the first stage of refining process field is laid out using rough set theory (RST) based adaptive neuro-fuzzy inference system (ANFIS) soft sensor model to enhance the performance of oil refinery process. The RST was used to reduce the fuzzy rule s...

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Bibliographic Details
Main Authors: Ali Hussein Humod Al Jlibawi, Mohammad Lutfi Othman, Aris Ishak, Bahari S. Moh Noor, Al Huseiny M. Sattar Sajitt
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Predictive control system
crude distillation unit (CDU)
embedded soft sensor
machine learning techniques
cascade controllers
reid vapor pressure
Online Access:https://ieeexplore.ieee.org/document/9646957/

Internet

https://ieeexplore.ieee.org/document/9646957/

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