Quantification of the predictive uncertainty of artificial neural network based river flow forecast...
Quantification of the predictive uncertainty of artificial neural network based river flow forecast models
About this item
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Publisher
Berlin/Heidelberg: Springer-Verlag
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Language
English
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Publisher
Berlin/Heidelberg: Springer-Verlag
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Scope and Contents
Contents
The meaningful quantification of uncertainty in hydrological model outputs is a challenging task since complete knowledge about the hydrologic system is still lacking. Owing to the nonlinearity and complexity associated with the hydrological processes, Artificial neural network (ANN) based models have gained lot of attention for its effectiveness i...
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Full title
Quantification of the predictive uncertainty of artificial neural network based river flow forecast models
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TN_cdi_proquest_miscellaneous_1291618307
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_1291618307
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ISSN
1436-3240
E-ISSN
1436-3259
DOI
10.1007/s00477-012-0600-2
