## Abstract The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes
โฆ LIBER โฆ
Model identification of nonlinear time variant processes via artificial neural network
โ Scribed by M. Nikravesh; A.E. Farell; T.G. Stanford
- Publisher
- Elsevier Science
- Year
- 1996
- Tongue
- English
- Weight
- 1004 KB
- Volume
- 20
- Category
- Article
- ISSN
- 0098-1354
No coin nor oath required. For personal study only.
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