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Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
Abstract
Biochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts, optimization, and feature selection are critical for improving biomass management techniques. In this research, we explore the influences of these techniques on the accurate forecasting of biochar yield and properties for a range of biomass sources. We emphasize the importance of the interpretability of a model, as this improves human comprehension and trust in ML predictions. Sensitivity analysis is shown to be an effective technique for finding crucial biomass characteristics that influence the synthesis of biochar. Precision prognostics have far-reaching ramifications, influencing industries such as biomass logistics, conversion technologies, and the successful use of biomass as renewable energy. These advances can make a substantial contribution to a greener future and can encourage the development of a circular biobased economy. This work emphasizes the importance of using sophisticated data-driven methodologies such as ML in biochar synthesis, to usher in ecologically friendly energy solutions. These breakthroughs hold the key to a more sustainable and environmentally friendly future.
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Authors (9)
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Giao Van Nguyen
- HUTECH University
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Prabhakar Sharma
- Delhi Skill and Entrepreneurship University
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Ümit Ağbulut
- Düzce University, Turkey
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Huu Son Le
- Van Lang University, Vietnam
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Thanh Hai Truong
- Ho Chi Minh City University of Transport, Vietnam
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Minh Ho Tran
- Dong A University, Danang, Vietnam
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Huu Cuong Le
- Ho Chi Minh City University of Transport
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Viet Dung Tran
- Ho Chi Minh City University of Transport
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Keywords
Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
Biofuels Bioproducts & Biorefining-Biofpr
no. 18,
pages 567 - 593,
ISSN: 1932-104X - Language:
- English
- Publication year:
- 2024
- Bibliographic description:
- Nguyen G. V., Sharma P., Ağbulut Ü., Le H. S., Truong T. H., Dzida M., Tran M. H., Le H. C., Tran V. D.: Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy// Biofuels Bioproducts & Biorefining-Biofpr -Vol. 18,iss. 2 (2024), s.567-593
- DOI:
- Digital Object Identifier (open in new tab) 10.1002/bbb.2596
- Sources of funding:
-
- Free publication
- Verified by:
- Gdańsk University of Technology
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