Abstract
In this paper a new approach based on the artificial neural network model is proposed for the prediction of daily water demands The approach is compared with the conventional ones and the results show that the new approach is more reliable and more effective. The fluctuation analysis of daily water demands and the sensitivity analysis of exogenous variables have also been carried out by taking advantage of the ability of neural network models handling with non-linear problems.
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© 1994 Springer Science+Business Media Dordrecht
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Zhang, S.P., Watanabe, H., Yamada, R. (1994). Prediction of Daily Water Demands by Neural Networks. In: Hipel, K.W., McLeod, A.I., Panu, U.S., Singh, V.P. (eds) Stochastic and Statistical Methods in Hydrology and Environmental Engineering. Water Science and Technology Library, vol 10/3. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-3083-9_17
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DOI: https://doi.org/10.1007/978-94-017-3083-9_17
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-4379-5
Online ISBN: 978-94-017-3083-9
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