Enhanced prediction of heating value of municipal solid waste using hybrid neuro-fuzzy model and decision tree-based feature importance assessment

Enhanced prediction of heating value of municipal solid waste using hybrid neuro-fuzzy model and decision tree-based feature importance assessment

This study proposes a hybrid network of adaptive neuro-fuzzy inference system (ANFIS) with genetic algorithm (GA) to predict the higher heating value (HHV) of municipal solid waste (MSW). To enhance the robustness and accuracy of the model and optimize its ability to capture the complex non-linear r...

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Bibliographic Details
Main Authors: Oluwatobi Adeleke, Obafemi O. Olatunji, Tien-Chien Jen, Iretioluwa Olawuyi
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Green Energy and Resources
Subjects:
Higher heating value
Municipal solid waste
Feature importance
Genetic algorithm
ANFIS
Decision tree
Online Access:http://www.sciencedirect.com/science/article/pii/S2949720525000062
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http://www.sciencedirect.com/science/article/pii/S2949720525000062

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