ARTIFICIAL INTELLIGENCE FOR DECISION SUPPORT IN WATER DESALINATION, RECYCLING, AND PURIFICATION
For over 30 years, AI and computational intelligence have been used in water desalination domain (He et al., 2022) for applications like support in the decision making, prediction, optimization, and control with respect to alarm processing, fault detection, load forecasting, and security assessment.
The recent trend to use renewable energy sources for desalination and wastewater treatment makes the decision process more complicated, due to the temporal variability of these sources (Cabrera and Carta, 2019; Harrou et al., 2018; Cheng et al, 2020). AI systems that go beyond the current point solutions are needed to deal with this complexity, while considering a system-wide view and a balanced interaction between the AI systems and human experts. The scientific challenge of this PhD project is to develop hybrid AI solutions that combine advanced prediction methods (e.g. deep learning algorithms), multi-objective optimization and adaptive models with explainable AI decision-making methods from computational intelligence to realize such a balance.
PhD promoters: Dr. Laura Genga and Prof.Dr.Ir. Uzay Kaymak