The usage of Artificial Neural Networks in the classification and forecast of potable water consumption

Author

De Oliveira, Diego Marinho ; De Oliveira Andrade, André Luís ; Nobre, Cristiane Neri ; Zárate, Luis Enrique

Author_Institution

Appl. Comput. Intell. Lab. & Comput. Sci., Pontifical Catholic Univ. of Minas Gerais, Belo Horizonte, Brazil

fYear

2009

fDate

14-19 June 2009

Firstpage

2331

Lastpage

2338

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.

Keywords

data mining; environmental science computing; learning (artificial intelligence); neural nets; pattern classification; socio-economic effects; trees (mathematics); water conservation; water resources; State of Parana database; TREPAN algorithm; artificial neural network training; classification method; data mining; geographic variable; knowledge extraction; neural representation structure; potable water consumption forecasting; socio-economic variable; trees parroting network; water resources renovation; Artificial neural networks; Cities and towns; Computational intelligence; Computer science; Databases; Degradation; Humans; Laboratories; Temperature; Water resources;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2009. IJCNN 2009. International Joint Conference on

Conference_Location

Atlanta, GA

ISSN

1098-7576

Print_ISBN

978-1-4244-3548-7

Electronic_ISBN

1098-7576

Type

conf

DOI

10.1109/IJCNN.2009.5178914

Filename

5178914