Nonlinear forecasting of stream flows using a chaotic approach and artificial neural networks
This paper evaluates the forecasting performance of two nonlinear models, k-nearest neighbor (kNN) and feed-forward neural networks (FFNN), using stream flow data of the Kızılırmak River, the longest river in Turkey. For the kNN model, the required parameters are delay time, number of nearest neigh-...
- Autores:
-
Tongal, Hakan
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2013
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/71914
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/71914
http://bdigital.unal.edu.co/36386/
http://bdigital.unal.edu.co/36386/2/
- Palabra clave:
- Civil Engineering
Hydrology
Statistical and Soft Modeling
Kızılırmak
k-nearest neighbor
and feed-forward neural networks
mutual information function
correlation dimension
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional