Title :
ANNs and GAs for predictive control of water supply networks
Author :
Damas, M. ; Salmerón, M. ; Ortega, J.
Author_Institution :
Dept. de Arquitectura y Tecnologia de Computadores, Granada Univ., Spain
Abstract :
This paper describes a procedure for controlling the water supply system. The controller uses a neural network to predict the water demand levels and a genetic algorithm to determine the feasible operation points in an optimal strategy that is based on dynamic programming. The controller has been executed in parallel in a cluster of computers. This has allowed not only the determination of the control commands in the required times but also the improvement of the control procedure performances
Keywords :
dynamic programming; forecasting theory; genetic algorithms; neural nets; predictive control; water supply; dynamic programming; genetic algorithm; neural network; optimisation; predictive control; water supply networks; Artificial neural networks; Computer networks; Concurrent computing; Control systems; Dynamic programming; Genetic algorithms; Neural networks; Optimal control; Reservoirs; Valves;
Conference_Titel :
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location :
Como
Print_ISBN :
0-7695-0619-4
DOI :
10.1109/IJCNN.2000.860799
