Supplementary Materials for: Comparative Evaluation of Response Surface Methodology and Machine Learning Modeling Approaches for High-Strength Phenol Biodegradation in Engineered Water Treatment Systems

This record contains the supplementary materials supporting the manuscript entitled: “Comparative Evaluation of Response Surface Methodology and Machine Learning Modeling Approaches for High-Strength Phenol Biodegradation in Engineered Water Treatment Systems” submitted to the Journal of Environmental Engineering (ASCE). The supplementary materials include MSM composition, CCD parameter selection rationale, regression diagnostics, SVR performance metrics, full predicted vs experimental dataset, and additional response surface and machine learning diagnostic figures.