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Title: ARTIFICIAL NEURAL NETWORK VS. LINEAR REGRESSION FOR MODELING REACTOR OF THE CATALYTIC CRACKING PROCESS
ARTIFICIAL NEURAL NETWORK VS. LINEAR REGRESSION FOR MODELING REACTOR OF THE CATALYTIC CRACKING PROCESS

PlumX Article Metrics by Elsevier
Bogdan Doicin; Madalina Carbureanu; Cristina Roxana Popa
10.5593/sgem2024/2.1/s07.04
10.5593/sgem2024/2.1
1314-2704
978-619-7603-69-9
English
24
2.1
•    Prof. DSc. Oleksandr Trofymchuk, UKRAINE 
•    Prof. Dr. hab. oec. Baiba Rivza, LATVIA
Informatics
The paper presents the research and results obtained by authors concerning the reactor modeling of the catalytic cracking process using two methods: artificial neural network (ANN) and multiple linear regression (MLR). This study is structured in four parts. The first part presents the process description, and the existing models in the literature. The second part presents the multiple linear regression method, the reactor model obtained with this method, and the comparison between the output experimental data of the reactor and output variables predicted with the MLR method. The experimental data were taken from a Romanian refinery. The next section describes the steps involved to build the neural network developed by authors for modeling the reactor, and the result of the comparison between the output experimental data of the reactor and output variables predicted with the ANN. The result shows that the neural model developed for the reactor is superior to the statistical model obtained with multiple linear regression.
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conference
https://doi.org/10.5593/sgem2024/2.1/s07.04
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Proceedings of 24th International Multidisciplinary Scientific GeoConference SGEM 2024
24th International Multidisciplinary Scientific GeoConference SGEM 2024, 1 - 7 July, 2024
Proceedings Paper
STEF92 Technology
International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM
SWS Scholarly Society; Acad Sci Czech Republ; Latvian Acad Sci; Polish Acad Sci; Russian Acad Sci; Serbian Acad Sci and Arts; Natl Acad Sci Ukraine; Natl Acad Sci Armenia; Sci Council Japan; European Acad Sci, Arts and Letters; Acad Fine Arts Zagreb Croatia; Croatian Acad Sci and Arts; Acad Sci Moldova; Montenegrin Acad Sci and Arts; Georgian Acad Sci; Acad Fine Arts and Design Bratislava; Russian Acad Arts; Turkish Acad Sci.
27-34
1 - 7 July, 2024
website
9916
catalytic cracking, artificial neural network, regression

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