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Optimization of biochar yield using dynamic statistical modeling and machine learning approaches
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DOI：10.1016/j.molliq.2026.129641.png)
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Abstract
En 中文
• Biochar yield predicted using Response Surface Methodology (RSM) and ELT models. • RSM used lab data and ELT integrated literature for robust training. • Model comparison under identical pyrolysis conditions confirmed predictive accuracy. • Analysis of pyrolysis operating conditions; heating rate, residence time, and temperature. • ML-RSM framework optimizes parameters for macroalgae based production.
Keywords:
biochar yield
Response Surface Methodology
machine learning
pyrolysis conditions
macroalgae
Journal
IF:
5.2
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2.5W
Citations:
9.0W
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