Analysis of a gaussian process and feed-forward neural networks based filter for forecasting short rainfall time series

In this paper, an analysis of kernel (GP) and feed-forward neural networks (FFNN) based filter to forecast short rainfall time series is presented. For the FFNN, the learning rule used to adjust the filter weights is based on the Levenberg-Marquardt method and Bayesian approach by the assumption of...

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Detalles Bibliográficos
Autores principales: Rodriguez Rivero, C., Pucheta, J., Patiño, H., Baumgartner, J., Laboret, S., Sauchelli, V.
Formato: conferenceObject
Lenguaje:Inglés
Publicado: 2022
Materias:
Artificial neural networks
Rainfall forecast
Hursts parameter
Analysis of kernel
Bayesian adjustment
Acceso en línea:http://hdl.handle.net/11086/29596
Aporte de:
Repositorio Digital Universitario (UNC) de Universidad Nacional de Córdoba

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