Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches

IF 3.1 4区工程技术 Q3 ENERGY & FUELS

International Journal of Green Energy Pub Date : 2024-03-14 DOI:10.1080/15435075.2024.2326076

Van Giao Nguyen, Prabhakar Sharma, Ümit Ağbulut, Huu Son Le, Dao Nam Cao, Marek Dzida, Sameh M. Osman, Huu Cuong Le, Viet Dung Tran

引用次数: 0

Abstract

Examining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent a...

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通过实施易用的机器学习方法，改进对各种生物质来源的生物炭产量的预测

本研究探讨了可解释机器学习技术改变游戏规则的可能性，探索了快速发展的生物炭生产预测领域。论文展示了最近的机器学习技术是如何...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Green Energy 工程技术-能源与燃料

CiteScore

6.60

自引率

9.10%

发文量

112

审稿时长

3.7 months

期刊介绍： International Journal of Green Energy shares multidisciplinary research results in the fields of energy research, energy conversion, energy management, and energy conservation, with a particular interest in advanced, environmentally friendly energy technologies. We publish research that focuses on the forms and utilizations of energy that have no, minimal, or reduced impact on environment, economy and society.