Biomass Gasification and Applied Intelligent Retrieval in Modeling | Библиотека Института психологии РАН

Библиотека Института психологии РАН

Biomass Gasification and Applied Intelligent Retrieval in Modeling

Meena Manish, Kumar Hrishikesh, Chaturvedi Nitin Dutt, Kovalev Andrey A., Bolshev V.E., Kovalev D.A., Sarangi Prakash Kumar, Chawade Aakash, Rajput Manish Singh, Vivekanand Vivekanand, Panchenko Vladimir
Energies SCOPUS WOS
ТИП ПУБЛИКАЦИИ статья в журнале - научная статья
ГОД 2023
ЯЗЫК EN
ЦИТИРОВАНИЙ 1
АННОТАЦИЯ
Gasification technology often requires the use of modeling approaches to incorporate several intermediate reactions in a complex nature. These traditional models are occasionally impractical and often challenging to bring reliable relations between performing parameters. Hence, this study outlined the solutions to overcome the challenges in modeling approaches. The use of machine learning (ML) methods is essential and a promising integration to add intelligent retrieval to traditional modeling approaches of gasification technology. Regarding this, this study charted applied ML-based artificial intelligence in the field of gasification research. This study includes a summary of applied ML algorithms, including neural network, support vector, decision tree, random forest, and gradient boosting, and their performance evaluations for gasification technologies.
ЦИТАТА
Biomass Gasification and Applied Intelligent Retrieval in Modeling / M. Meena, H. Kumar, N.D. Chaturvedi, A.A. Kovalev, V.E. Bolshev, D.A. Kovalev, P.K. Sarangi, A. Chawade, M.S. Rajput, V. Vivekanand, V. Panchenko // Energies. – 2023. – Т. 16. – № 18. – P. 6524
АВТОРЫ

Большев Вадим Евгеньевич

ЛАБОРАТОРИЯ ТЕХНОЛОГИЙ ИИ В ПСИХОЛОГИИ
Научный сотрудник

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