Introduction to Artificial Intelligence in Optimization of Wastewater Treatment Processes

Wastewater treatment is an important and challenging task for environmental protection and resource recovery. Artificial intelligence (AI) techniques can provide effective solutions for optimizing wastewater treatment processes. In this paper, we review the recent research progress on AI methods for improving wastewater treatment efficiency, reducing wastewater treatment costs, and minimizing wastewater treatment emissions. We compare and evaluate different AI methods and models, such as neural networks, fuzzy logic, genetic algorithms, and their applications and performance in various wastewater treatment process optimizations. Furthermore, we review the multi-objective optimization problems based on artificial neural networks and genetic algorithms, including methods, principles, pareto sets selection and evaluation of solving multi-objective optimization problems. In this study, we present the prediction and optimization results of the model, and analyze the model performance and advantages and disadvantages. We conclude the limitations and improvement directions of this paper, and the future development trends and challenges of AI in wastewater treatment field.