Hybrid Strategy Integrating Variable Selection and a Neural Network for Fluid Catalytic Cracking Modeling-Reference-Cited by-同舟云学术

Hybrid Strategy Integrating Variable Selection and a Neural Network for Fluid Catalytic Cracking Modeling

Published:2018-12-18 Issue:1 Volume:58 Page:247-258
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Long Jian¹^ORCID,Li Tianyue¹,Yang Minglei¹,Hu Guihua¹,Zhong Weimin¹^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

Funder

National Natural Science Foundation of China

Ministry of Education of the People's Republic of China

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.8b04821

Reference45 articles.

1. Predictive Modeling of Large-Scale Integrated Refinery Reaction and Fractionation Systems from Plant Data. Part 3: Continuous Catalyst Regeneration (CCR) Reforming Process

2. Fluid Catalytic Cracking (FCC) Process Modeling, Simulation, and Control

3. Molecular-Level-Process Model with Feedback of the Heat Effects on a Complex Reaction Network in a Fluidized Catalytic Cracking Process

4. Advance in China fluid catalytic cracking (FCC) process

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