Application of data prediction models in a real water supply network: comparison between arima and artificial neural networks
André Carlos da Silva,
Fernando das Graças Braga da Silva,
Victor Eduardo de Mello Valério
et al.
Abstract:Research around the world has focused on developing ways to predict hydraulic parameters in water distribution systems. The application of these forecasts can contribute to the decision-making of water distribution systems managers, aiming to ensure that the demand is met, and even to reduce water losses. The present work sought, among two data prediction models (ARIMA and Multi-Layer Perceptron Artificial Neural Networks), to assess which one can perform best predictions of pressure and discharge rate data. T… Show more
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