Enhancing Precision in Artificial Intelligence – Based Water Quality Prediction: The Advantages of Hybrid Modeling Approaches– Review*

Complex relationships among variables in the field of environmental engineering and water management sector foster numerous advantages when harnessing AI tools in modeling. Non-linear correlation among parameters proposed for ecological state prediction propose utilizing of Artificial Intelligence-based models. Given the highly intricate and dynamic nature of water environments, effective management poses a demanding challenge, particularly in the realm of forecasting. Consequently, there is a critical demand for the development of accurate water quality prediction models to address these complexities and ensure optimal management practices. To achieve highly precise results in predicting water quality, hybrid AI-based models stand as the state-of-the-art solution. Applying hybrid AI-based models in water quality prediction enhances accuracy, robustness, and flexibility by leveraging corresponding strengths of multiple algorithms, leading to optimized performance and improved decision-making in water management.