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- Title
Runoff Modelling Through Back Propagation Artificial Neural NetworkWith Variable Rainfall-Runoff Data.
- Authors
Agarwal, Avinash; Singh, R. D.
- Abstract
Multi layer back propagation artificial neural network (BPANN) models have been developed to simulate rainfall-runoff process for two sub-basins of Narmada river (India) viz. Banjar up to Hridaynagar and Narmada up to Manot considering three time scales viz. weekly, ten-daily and monthly with variable and uncertain data sets. The BPANN runoff models were developed using gradient descent optimization technique and were generalized through cross-validation. In almost all cases, the BPANN developed with the data having relatively high variability and uncertainty learned in less number of iterations, with high generalization. Performance of BPANN models is compared with the developed linear transfer function (LTF) model and was found superior.
- Subjects
NARMADA River (India); INDIA; ARTIFICIAL neural networks; RUNOFF; WATER management; SIMULATION methods &; models; TRANSFER functions; MATHEMATICAL optimization; ITERATIVE methods (Mathematics)
- Publication
Water Resources Management, 2004, Vol 18, Issue 3, p285
- ISSN
0920-4741
- Publication type
Article
- DOI
10.1023/B:WARM.0000043134.76163.b9