Back to Search Start Over

Biomass Gasification and Applied Intelligent Retrieval in Modeling.

Authors :
Meena, Manish
Kumar, Hrishikesh
Chaturvedi, Nitin Dutt
Kovalev, Andrey A.
Bolshev, Vadim
Kovalev, Dmitriy A.
Sarangi, Prakash Kumar
Chawade, Aakash
Rajput, Manish Singh
Vivekanand, Vivekanand
Panchenko, Vladimir
Source :
Energies (19961073); Sep2023, Vol. 16 Issue 18, p6524, 21p
Publication Year :
2023

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19961073
Volume :
16
Issue :
18
Database :
Complementary Index
Journal :
Energies (19961073)
Publication Type :
Academic Journal
Accession number :
172418363
Full Text :
https://doi.org/10.3390/en16186524