Optimizing Hydrogen Production in the Co-Gasification Process: Comparison of Explainable Regression Models Using Shapley Additive Explanations
The co-gasification of biomass and plastic waste offers a promising solution for producing hydrogen-rich syngas, addressing the rising demand for cleaner energy. However, optimizing this complex process to maximize hydrogen yield remains challenging, particularly when balancing diverse feedstocks an...
Saved in:
Main Author: | Thavavel Vaiyapuri |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/27/1/83 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Implementasi Algoritma Catboost Dan Shapley Additive Explanations (SHAP) Dalam Memprediksi Popularitas Game Indie Pada Platform Steam
by: Mohammad Teddy Syamkalla, et al.
Published: (2024-08-01) -
A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME
by: Ahmed M. Salih, et al.
Published: (2025-01-01) -
Shapley additive explanation on machine learning predictions of fatigue lifetimes in piston aluminum alloys under different manufacturing and loading conditions
by: Mahmood Matin, et al.
Published: (2024-04-01) -
Investigating the impact of diversion projects on river health using the spherical fuzzy cloud TOPSIS model and the SHapley Additive exPlanation technique
by: Ting Cheng, et al.
Published: (2025-01-01) -
Thermodynamic Assessment of Different Feedstocks Gasification Using Supercritical Water and CO<sub>2</sub> for Hydrogen and Methane Production
by: Luis David García Caraballo, et al.
Published: (2025-01-01)