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(Article of periodic en Anglais - 2007)

Document title

Suspended sediment flux modeling with artificial neural network : an example of the Longchuanjiang River in the Upper Yangtze catchment, China

Authors(s) and Affiliation(s)

ZHU Y.-M. ; LU X.X. ; ZHOU Y. ;

Abstract

In this study, the AA. applied artificial neural network (ANN) to simulate monthly suspended sediment flux from 1960 to 2001 in the Longchuanjiang River. The ANN constructed from climatic variables only (rainfall, temperature) will have a potential of filling missing data in a suspended sediment flux time series and predicting the influence of climatic change on suspended sediment flux. The advantage of ANN were also evaluated by comparing its performance with that of multiple linear regression (MLR) models and power relation (PR) models

Source

Article of periodic

published at : Geomorphology / ISSN 0169-555X

Editor : Elsevier, Amsterdam - PAYS-BAS (1987)

Millesime : 2007, vol. 84, no1-2 [pp. 111-125]

Bibliographic references : 46 ref.

Collation : Illustration ;

Language

Anglais

INIST-CNRS, Cote INIST : 21151

Tous droits réservés © Prodig - Bibliographie Géographique Internationale (BGI), 2007.
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