Title :
Study on a new approach of municipal hourly water demand prediction
Author :
Xu, Hongze ; Zhang, Wenjing
Author_Institution :
Dept. of Autom., Beijing Jiaotong Univ., China
Abstract :
Various factors that affected the municipal water demand and characteristics of municipal hourly water demand series were analyzed. Based on these, wavelet neural networks´ prediction models with periods of 24 and 168 hours were presented for working days and weekends respectively. In addition, the models were trained with gradient method. Finally, hourly water demand series of one city were predicted and compared with corresponding real values. Simulation results show the effectiveness of the proposed wavelet neural networks prediction models. At the same time, this type of hourly water demand prediction method can meet the demand of modeling and optimal dispatch of water supplying system.
Keywords :
demand forecasting; gradient methods; neural nets; water supply; wavelet transforms; 168 hour; 24 hour; gradient method; hourly water demand prediction method; municipal hourly water demand series; optimal dispatch; water supplying system; wavelet neural networks prediction models; Automation; Cities and towns; Gradient methods; Neural networks; Prediction methods; Predictive models; Water;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1342075
