A robust hybrid data driven approach to model biochar yield in terms of biomass pyrolysis.

of 0.98, an MSE of 1.9, and an AARE% of 2.2%, outperforming the other optimization techniques. SHAP analysis revealed that pyrolysis temperature, residence time, and ash content were the most influential parameters governing biochar yield. Comparative benchmarking against previously published models confirmed the superior predictive capability and stability of the proposed framework. The results demonstrate that the DT-BBO model offers a scalable, interpretable, and high-performing solution for biochar yield prediction, contributing to methodological innovation and sustainable biomass valorization.