The usage of artificial neural networks in the classification and forecast of potable water consumption

Authors:
Diego Marinho de Oliveira;André Luís de Oliveira Andrade;Cristiane Neri Nobre;Luis Enrique Zárate
Affiliations:
Applied Computational Intelligence Laboratory and Computer Science, Pontifical Catholic University of Minas Gerais, Belo Horizonte, MG, Brazil;Applied Computational Intelligence Laboratory and Computer Science, Pontifical Catholic University of Minas Gerais, Belo Horizonte, MG, Brazil;Applied Computational Intelligence Laboratory and Computer Science Teacher's, Pontifical Catholic University of Minas Gerais, Belo Horizonte, MG, Brazil;Applied Computational Intelligence Laboratory and Computer Science Teacher's, Pontifical Catholic University of Minas Gerais, Belo Horizonte, MG, Brazil
Venue:
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Year:
2009

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Abstract

This study aimed at identifying the main factors that influence potable water consumption. It was used a neural representation structure to model its consumption, applying geographic and socio-economic variables, as well as Trepan (TREes Parroting Networks), a special tool to to obtain knowledge from trained Artificial Neural Networks. The model was applied to a database of the State of Parana - Brazil.