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Prediction average of the annual maximum series (index flood) using Artificial Neural Networks

In: Acta Hydrologica Slovaca, vol. 12, no. 1
Viliam Šimor - Kamila Hlavčová - Silvia Kohnová - Milan Čistý
Detaily:
Rok, strany: 2011, 74 - 81
Kľúčové slová:
Artificial Neural Networks (ANNs), annual maximum series forecasting (flood index)
URL originálneho zdroja: http://www.ih.savba.sk/ah
O článku:
PREDICTION AVERAGE OF THE ANNUAL MAXIMUM SERIES (INDEX FLOOD) USING ARTIFICIAL NEURAL NETWORKS. The aim of this paper was to apply artificial neural networks (ANNs) for estimating mean annual maximum discharges (index floods) for 145 small catchments in Slovakia. The catchments were divided into clusters using different geographic characteristic. The ANNs structure was applied as a simple multilayer perceptron. As a training algorithm the back propagation learning algorithm was used. As an activation function the hyperbolic tangents were used in the hidden layer of neurons. For every cluster different predicting characteristic were selected. The efficiency of estimated results was tested by the Nash – Sutcliffe coefficient.
Ako citovať:
ISO 690:
Šimor, V., Hlavčová, K., Kohnová, S., Čistý, M. 2011. Prediction average of the annual maximum series (index flood) using Artificial Neural Networks. In Acta Hydrologica Slovaca, vol. 12, no.1, pp. 74-81. 2644-6291 (printed until 2018).

APA:
Šimor, V., Hlavčová, K., Kohnová, S., Čistý, M. (2011). Prediction average of the annual maximum series (index flood) using Artificial Neural Networks. Acta Hydrologica Slovaca, 12(1), 74-81. 2644-6291 (printed until 2018).