Optimization of distribution control system in oil refinery by applying hybrid machine learning techniques
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...
Main Authors: | Al Jlibawi, Ali Hussein Humod, Othman, Mohammad Lutfi, Ishak, Aris, Moh Noor, Bahari S., Al Huseiny, M. Sattar Sajitt |
---|---|
Format: | Article |
Published: |
Institute of Electrical and Electronics Engineers
2021
|
Similar Items
-
Soft sensor modelling for optimization of distribution control system in oil refineries by applying hybrid data mining techniques
by: Al Jlibawi, Ali Hussein Humod
Published: (2021) -
Efficient and sustainable remediation of refinery wastewater using electrocoagulation and advanced oxidation techniques
by: Albrazanjy, Mohammed G., et al.
Published: (2024) -
Hybrid Blo-Membrane Contractori For Refinery Waste Water Treatment
by: Mohd Zulkifli, Mohamad Noor, et al. -
Petroleum refinery manual/
by: 399903 Noel, Henry Martyn
Published: (1959) -
Machine Learning for Downstream Oil & Gas Refineries: Applications for Solvent Deasphalting
by: Dowell, Christian
Published: (2022)