Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/2124
Title: ANN and fuzzy logic models for simulating event-based rainfall-runoff
Authors: Tayfur, Gökmen
Singh, Vijay P.
Keywords: Fuzzy sets
Kinematic wave theory
Neural networks
Rainfall
Runoff
Simulation
Issue Date: Dec-2006
Publisher: American Society of Civil Engineers (ASCE)
Source: Tayfur, G., and Singh, V. P. (2006). ANN and fuzzy logic models for simulating event-based rainfall-runoff. Journal of Hydraulic Engineering, 132(12), 1321-1330. doi:10.1061/(ASCE)0733-9429(2006)132:12(1321)
Abstract: This study presents the development of artificial neural network (ANN) and fuzzy logic (FL) models for predicting event-based rainfall runoff and tests these models against the kinematic wave approximation (KWA). A three-layer feed-forward ANN was developed using the sigmoid function and the backpropagation algorithm. The FL model was developed employing the triangular fuzzy membership functions for the input and output variables. The fuzzy rules were inferred from the measured data. The measured event based rainfall-runoff peak discharge data from laboratory flume and experimental plots were satisfactorily predicted by the ANN, FL, and KWA models. Similarly, all the three models satisfactorily simulated event-based rainfall-runoff hydrographs from experimental plots with comparable error measures. ANN and FL models also satisfactorily simulated a measured hydrograph from a small watershed 8.44 km2 in area. The results provide insights into the adequacy of ANN and FL methods as well as their competitiveness against the KWA for simulating event-based rainfall-runoff processes.
URI: https://doi.org/10.1061/(ASCE)0733-9429(2006)132:12(1321)
http://hdl.handle.net/11147/2124
ISSN: 0733-9429
0733-9429
Appears in Collections:Civil Engineering / İnşaat Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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