Adaptive Weighted Hybrid Modeling of Hydrocracking Process and Its Operational Optimization-Reference-Cited by-同舟云学术

Adaptive Weighted Hybrid Modeling of Hydrocracking Process and Its Operational Optimization

Published:2021-02-24 Issue:9 Volume:60 Page:3617-3632
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Song Wenjiang¹^ORCID,Du Wei¹²,Fan Chen¹,Yang Minglei¹,Qian Feng¹^ORCID

Affiliation:

1. Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China

2. Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 200092, China

Funder

National Natural Science Foundation of China

Shanghai Sailing Program

International (Regional) Cooperation and Exchange Project

National Natural Science Fund for Distinguished Young Scholars

National Natural Science Foundation of China (Basic Science Center Program)

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.0c05416

Reference47 articles.

1. Reaction pathways and product yields in mild thermal cracking of vacuum residues: A multi-lump kinetic model

2. A protein inspired RNA genetic algorithm for parameter estimation in hydrocracking of heavy oil

3. Development of Vacuum Residue Hydrodesulphurization–Hydrocracking Models and Their Integration with Refinery Hydrogen Networks

4. Modeling the effect of pressure and temperature on the hydrocracking of heavy crude oil by the continuous kinetic lumping approach

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Just-in-time learning method based on two kinds of local samples combined with two-stage training parallel learner for nonlinear chemical process soft sensing;Measurement;2024-10

2. Reaction network design and hybrid modeling of S Zorb;Chinese Journal of Chemical Engineering;2024-09

3. Transparency: The Missing Link to Boosting AI Transformations in Chemical Engineering;Engineering;2024-08

4. Enhancing interactive optimization with operating condition supervision for distillation units;Control Engineering Practice;2024-07

5. Large-scale optimization of nonconvex MINLP refinery scheduling;Computers & Chemical Engineering;2024-07