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- W2098982781 abstract "Accurate application of the longitudinal dispersion model requires that specially designed experimental studies are performed in the river reach under consideration. Such studies are usually very expensive, so in order to quantify the longitudinal dispersion coefficient, as an alternative approach, various researchers have proposed numerous empirical formulae based on hydraulic and morphometric characteristics. The results are presented of the application of artificial neural networks as a parameter estimation technique. Five different cases were considered with the network trained for different arrangements of input nodes, such as channel depth, channel width, cross-sectionally averaged water velocity, shear velocity and sinuosity index. In the case where the sinuosity index is included as an input node, the results turned out to be better than those presented by other authors. Resume L'application precise du modele de dispersion longitudinale necessite la mise en œuvre d'etudes experimentales specifiques dans le cours d'eau considere. De telles etudes sont en general tres couteuses, si bien que, dans le but de quantifier de maniere alternative le coefficient de dispersion longitudinale, plusieurs chercheurs ont propose de nombreuses formules empiriques basees sur des caracteristiques hydrauliques et morphometriques. Nous presentons les resultats de l'application de reseaux de neurones artificiels comme technique d'estimation des parametres. Cinq cas differents ont ete consideres, avec, pour l'apprentissage, des combinaisons variees de nœuds d'entree, dont la profondeur du chenal, la largeur du chenal, la vitesse moyenne de l'eau a travers la section, la vitesse de cisaillement et l'indice de sinuosite. Lorsque l'indice de sinuosite est pris en compte comme nœud d'entree, les resultats sont ameliores par rapport a ceux d'autres auteurs." @default.
- W2098982781 created "2016-06-24" @default.
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- W2098982781 date "2005-01-01" @default.
- W2098982781 modified "2023-09-27" @default.
- W2098982781 title "Are Artificial Neural Network Techniques Relevant for the Estimation of Longitudinal Dispersion Coefficient in Rivers" @default.
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