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.

Keywords

gasification technology; machine learning; biomass gasification; energy; applications

Published in

Energies
2023, Volume: 16, number: 18, article number: 6524
Publisher: MDPI

SLU Authors

• Chawade, Aakash

  • Department of Plant Breeding, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Bioenergy
Other Computer and Information Science


Publication identifier

DOI: https://doi.org/10.3390/en16186524

Permanent link to this page (URI)

https://res.slu.se/id/publ/126626