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-...

Full description

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