Modeling UrbanWater Demand Using Agent-based Simulation: A Case Study in Salvador
Resumo
This paper uses a data-driven reasoning model and inference rules to propose a Multi-Agent System (MAS) for water demand forecasting in the Metropolitan Region of Salvador (MRS). For implementation, the GAMA platform (GIS Agent-Based Modeling Architecture), its language, GAML (GAMA Modeling Language), and Python were used for simulation, preprocessing, and normalizing input data. The model considers population growth, average consumption per household, and housing type, enabling more individualized mediumand long-term forecasting. The results demonstrate the feasibility of using Multi-Agent Systems to support agencies and entities responsible for water resource management, providing valuable contributions to water supply’s strategic and managerial planning.
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