Enhanced nitrogen prediction and mechanistic process analysis in high-salinity wastewater treatment using interpretable machine learning approach.

• Tác giả: Qing Wei, Zuxin Xu, Hailong Yin
• Ngôn ngữ: eng
• Ký hiệu phân loại: 006.3363 Artificial intelligence
• Thông tin xuất bản: England : Bioresource technology , 2025
• Bộ sưu tập: NCBI
• ID: 711167

Tóm tắt

This study introduces an interpretable machine learning framework to predict nitrogen removal in membrane bioreactor (MBR) treating high-salinity wastewater. By integrating Shapley additive explanations (SHAP) with Categorical Boosting (CatBoost), we address the critical gap in linking predictive accuracy to operational decision-making for saline systems. CatBoost achieved the best performance, with an coefficient of determination (R