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Application of artificial neural networks in hydrological modeling: A case study of runoff simulation of a Himalayan glacier basinThe simulation of runoff from a Himalayan Glacier basin using an Artificial Neural Network (ANN) is presented. The performance of the ANN model is found to be superior to the Energy Balance Model and the Multiple Regression model. The RMS Error is used as the figure of merit for judging the performance of the three models, and the RMS Error for the ANN model is the latest of the three models. The ANN is faster in learning and exhibits excellent system generalization characteristics.
Document ID
19940030555
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Buch, A. M.
(Indian Space Research Organization Ahmedabad., United States)
Narain, A.
(Indian Space Research Organization Ahmedabad., United States)
Pandey, P. C.
(Indian Space Research Organization Ahmedabad., United States)
Date Acquired
September 6, 2013
Publication Date
May 1, 1994
Publication Information
Publication: NASA. Goddard Space Flight Center, The 1994 Goddard Conference on Space Applications of Artificial Intelligence
Subject Category
Cybernetics
Accession Number
94N35061
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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