Using Self-Organizing Maps to Elucidate Patterns among Variables in Simulated Syngas Combustion

Using Self-Organizing Maps to Elucidate Patterns among Variables in Simulated Syngas Combustion

This study focused on demonstrating the use of a self-organizing map (SOM) algorithm to elucidate patterns among variables in simulated syngas combustion. The work was implemented in two stages: (1) modelling and simulation of syngas combustion under various feed composition and reactor temperature...

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Bibliographic Details
Main Authors: Dhan Lord B. Fortela, Matthew Crawford, Alyssa DeLattre, Spencer Kowalski, Mary Lissard, Ashton Fremin, Wayne Sharp, Emmanuel Revellame, Rafael Hernandez, Mark Zappi
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Clean Technologies
Subjects:
chemical process simulation
syngas
machine learning
SOM
Online Access:https://www.mdpi.com/2571-8797/2/2/11

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