Using XGBoost Regression to Analyze the Importance of Input Features Applied to an Artificial Intelligence Model for the Biomass Gasification System

Using XGBoost Regression to Analyze the Importance of Input Features Applied to an Artificial Intelligence Model for the Biomass Gasification System

Recently, artificial intelligence models have been developed to simulate the biomass gasification systems. The extant research models use different input features, such as carbon, hydrogen, nitrogen, sulfur, oxygen, and moisture content, in addition to ash, reaction temperature, volatile matter (VM)...

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Bibliographic Details
Main Authors: Hung-Ta Wen, Hom-Yu Wu, Kuo-Chien Liao
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Inventions
Subjects:
artificial intelligence model
biomass gasification
lower heating value
equivalence ratio
feature importance analysis
XGBoost regression
Online Access:https://www.mdpi.com/2411-5134/7/4/126

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https://www.mdpi.com/2411-5134/7/4/126

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