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Interpretable machine learning for toluene degradation in biological trickling filters: prediction, parameter

Yunfei Liu1, Jue Dai2, Yongzhi Yang1

  • 1School of Resource and Environmental Engineering, Shanghai Polytechnic University, 2360 Jinhai Road, Pudong New Area, Shanghai, 201209, China.

Bioprocess and Biosystems Engineering
|March 26, 2026
PubMed
Summary

No abstract available in PubMed .

Keywords:
Biological trickling filterInterpretabilityMachine learningOptimizationResponse surface methodologySHAP

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