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Pareto Optimization in Oil Refinery

This article describes the process of multicriteria optimization of a complex industrial control object using Pareto efficiency. The object is being decomposed and viewed as a hierarchy of embedded orgraphs. Performance indicators and controlling factors lists are created based on the orgraphs and t...

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Detalles Bibliográficos
Autores principales: Kostenko, Dmitri, Arseniev, Dmitriy, Shkodyrev, Vyacheslav, Onufriev, Vadim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7351681/
http://dx.doi.org/10.1007/978-981-15-7205-0_3
Descripción
Sumario:This article describes the process of multicriteria optimization of a complex industrial control object using Pareto efficiency. The object is being decomposed and viewed as a hierarchy of embedded orgraphs. Performance indicators and controlling factors lists are created based on the orgraphs and technical specifications of an object, thus allowing to systematize sources of influence. Using statistical data archives to train, the neural network approximates key sensors data to identify the model of the controllable object and optimize it.