ArticleBioresources and bioprocessing2026
A robust hybrid data driven approach to model biochar yield in terms of biomass pyrolysis.
Article in Bioresources and bioprocessing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Biochar yield prediction plays a critical role in optimizing pyrolysis processes and advancing sustainable biomass utilization. This study introduces a hybrid machine learning framework that integrates Decision Tree models with four optimization strategies including Tabu Search, Ant Colony Optimization, Evolutionary Strategies, and Batch Bayesian Optimization (DT-BBO). A curated dataset of 211 samples was preprocessed using Leverage outlier detection and normalization to ensure model robustness. Among all tested models, the DT-BBO approach achieved the highest accuracy, with an R
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