Trabalho apresentado em evento
Using neural networks for estimation of aquifer dynamical behavior
Fecha
2000-01-01Registro en:
Ijcnn 2000: Proceedings of the IEEE-inns-enns International Joint Conference on Neural Networks, Vol Vi. Los Alamitos: IEEE Computer Soc, p. 203-207, 2000.
1098-7576
10.1109/IJCNN.2000.859397
WOS:000089240600034
0783942619645974
Autor
Universidade Estadual Paulista (Unesp)
Resumen
The systems of water distribution from groundwater wells can be monitored using the changes observed on its dynamical behavior. In this paper, artificial neural networks are used to estimate the depth of the dynamical water level of groundwater wells in relation to water flow, operation time and rest time. Simulation results are presented to demonstrate the validity of the proposed approach. These results have shown that artificial neural networks can be effectively used for the identification and estimation of parameters related to systems of water distribution.