Treffer: Rainfall-runoff modelling using three neural network methods
Title:
Rainfall-runoff modelling using three neural network methods
Authors:
Source:
Artificial intelligence and soft computing (Zakopane, 7-11 June 2004)Lecture notes in computer science. :166-171
Publisher Information:
Berlin: Springer, 2004.
Publication Year:
2004
Physical Description:
print, 11 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Apprentissage et systèmes adaptatifs, Learning and adaptive systems, Algorithme rétropropagation, Backpropagation algorithm, Algoritmo retropropagación, Analyse régression, Regression analysis, Análisis regresión, Boucle anticipation, Feedforward, Ciclo anticipación, Fonction base radiale, Radial basis function, Función radial base, Régression linéaire, Linear regression, Regresión lineal, Réseau neuronal, Neural network, Red neuronal, Rétroaction, Feedback regulation, Retroacción
Document Type:
Konferenz
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Istanbul Technical University, Civil Engineering Faculty, Division of Hydraulics, Maslak 34469 Istanbul, Turkey
State Hydraulic Works, 14. Regional Directorate, Kucukcamlica, 34696 Istanbul, Turkey
State Hydraulic Works, 14. Regional Directorate, Kucukcamlica, 34696 Istanbul, Turkey
ISSN:
0302-9743
Rights:
Copyright 2004 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.15852422
Database:
PASCAL Archive
Weitere Informationen
Three neural network methods, feed forward back propagation (FFBP), radial basis function (RBF) and generalized regression neural network (GRNN) were employed for rainfall-runoff modelling of Turkish hydrometeorologic data. It was seen that all three different ANN algorithms compared well with conventional multi linear regression (MLR) technique. It was seen that only GRNN technique did not provide negative flow estimations for some observations. The rainfall-runoff correlogram was successfully used in determination of the input layer node number.