Neural Network-Assisted Modeling of Biodegradation Kinetics in Aerobic Bioreactor Treatment Systems

Abstract

Accurate prediction of biodegradation behavior in aerobic bioreactor systems is essential for improving wastewater treatment efficiency and optimizing operational performance. This study presents a neural network-assisted modeling approach for analyzing biodegradation kinetics in aerobic bioreactor treatment systems under varying environmental and operational conditions. The proposed framework integrates artificial neural network techniques with conventional biodegradation kinetics to enhance the prediction accuracy of contaminant removal and biological treatment performance. Experimental datasets obtained from aerobic bioreactor operations, including parameters such as dissolved oxygen concentration, substrate loading, biomass concentration, pH, temperature, and hydraulic retention time, were utilized to train and validate the neural network model. The developed model was designed to capture complex nonlinear relationships between process variables and biodegradation behavior that are difficult to represent using traditional kinetic equations alone. Performance evaluation demonstrated that the neural network-assisted model achieved high predictive accuracy in estimating organic pollutant degradation rates, biochemical oxygen demand reduction, and microbial activity trends during continuous treatment operations. Comparative analysis revealed superior modeling performance compared to conventional empirical and mechanistic approaches, particularly under fluctuating influent conditions and dynamic operational environments. Furthermore, the integration of intelligent predictive modeling enabled improved process optimization, operational stability, and real-time decision support for aerobic bioreactor management. Sensitivity analysis also identified critical operational parameters influencing biodegradation efficiency and system performance. The findings highlight the effectiveness of neural network-based approaches for advancing intelligent wastewater treatment modeling and process control strategies.