A Deep Learning Framework in FCC Process Control
نویسندگان
چکیده
The controlling of exhaust gas from gasoline is crucial for atmospheric environment protection. Research Octane Number (RON) loss and restricted sulphur (S) content matter the quality gasoline. To obtain with high quality, paper proposes a novel data-driven optimization model integrating deep neural network (DNN) genetic algorithm (GA) to Fluid Catalytic Cracking (FCC) process then optimize. begin with, DNN used fit relations between 13 related input variables output in FCC. Subsequently, FCC modelled GA proposed solve model. Ultimately, 305 samples real datasets have been analysed testify feasibility effectiveness method. This provides guideline production
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ژورنال
عنوان ژورنال: Advances in transdisciplinary engineering
سال: 2021
ISSN: ['2352-751X', '2352-7528']
DOI: https://doi.org/10.3233/atde210342