Modeling of Electrodialysis Plant at Water Treatment Facility Using Fuzzy Cognitive Map Theory

Water is a fundamental resource for sustainable demographic, social, and economic development. Today, water scarcity is a major challenge due to population growth, industrial expansion, pollution from human activities, and the limited availability of freshwater resources. Therefore, advanced water purification and treatment methods—such as reverse osmosis, chemical precipitation, adsorption, membrane processes, ion exchange, photocatalysis, chemical oxidation and reduction, electrodialysis, and ultrafiltration—are being actively developed to treat wastewater before discharge into the environment. In our study, we propose to use fuzzy cognitive maps (FCM) to analyze the operating factors of an electrodialysis water purification facility. FCM is appropriate for this system due to its complexity and the limited feasibility of conducting numerous experiments to determine direct dependencies. The initial mathematical model based on FCM was constructed using expert knowledge of the electrodialysis water purification process. The initial FCM was then refined using a learning algorithm, enabling the discovery of hidden relationships within the system. The proposed model enables identification of the optimal equipment configuration for operating a water treatment facility to maintain water resource balance.