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This paper presents Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) methods for predicting future daily water consumption values based on three antecedent records of water consumption and humidity forecast for a given day, which are considered as independent variables. Mean Absolute Percentage Error (MAPE) is obtained for different configurations of the input sets and of the ANN model structure. Additionally, sets of explanatory variables are enhanced with dummy variablesdoi:10.3311/ppci.11930 fatcat:lrbqjnsov5e3jlvx43ijwque2i