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Influence of ClassImbalance on theQuality ofHydrocracking UnitFailure PredictionModels : доклад,тезисы доклада Nekrasov IvanBukhtoyarov VladimirEremeeva Svetlana2022 год

Influence of Class Imbalance on the Quality of Hydrocracking Unit Failure Prediction Models : доклад, тезисы доклада
доклад, тезисы доклада, статья из сборника материалов конференций

Дополнительные ссылки: eLibrary · Источник статьи
База данных: Каталог библиотеки СФУ
Библиографическое описание: Influence of Class Imbalance on the Quality of Hydrocracking Unit Failure Prediction Models : доклад, тезисы доклада / I. I. Nekrasov, V. V. Bukhtoyarov, S. S. Eremeeva. - [S. l. : s. n.], 2022. - Текст : непосредственный // HYBRID METHODS OF MODELING AND OPTIMIZATION IN COMPLEX SYSTEMS : Proceedings of the International Workshop “Hybrid methods of modeling and optimization in complex systems” (HMMOCS 2022) / Krasnoyarsk Regional Science and Technology City Hall, Russia Siberian Federal University, Reshetnev Siberian State University of Science and Technology ; International Workshop “Hybrid methods of modeling and optimization in complex systems” (HMMOCS 2022) (2022 ; 22.11 - 24.11 ; Krasnoyarsk). - London, United Kingdom : European Proceedings, 2022. - P. 178-185. - ISBN 9781802969603, DOI 10.15405/epct.23021.22.
Аннотация: The paper is devoted to the study of the influence of class imbalance on the quality of hydrocracking unit failure prediction models. The use of machine learning methods finds an increasing response in various industries due to the increase in computing power and the reduction in the cost of creating advanced process control systems. The oil and gas industry are highly profitable and large in terms of its industrial capacity; thousands of pieces of technical equipment within one enterprise are involved in the production of petroleum products and their processing. Therefore, improving the operational reliability of oil refining process equipment is an urgent scientific task. In this paper, we consider a method for modeling a hydrocracking unit for the production of diesel fuels and creating models for predicting plant equipment failures. Particular attention is paid to the influence of class imbalance in data when solving the classification problem. The built-in weighting methods for classes of machine learning models are compared, as well as upsampling and downsampling methods.
Год издания: 2022
Авторы: Nekrasov Ivan , Bukhtoyarov Vladimir , Eremeeva Svetlana
Издательство: European Proceedings, London, United Kingdom
Источник: HYBRID METHODS OF MODELING AND OPTIMIZATION IN COMPLEX SYSTEMS
Номера страниц: 178-185
Держатель оригинала документа: Siberian Federal University
Мероприятие: International Workshop “Hybrid methods of modeling and optimization in complex systems” (HMMOCS 2022) (Krasnoyarsk, 2022 ; 22.11 - 24.11)
Количество экземпляров:
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