Memorias de investigación
Ponencias en congresos:
Feature Extraction Via Multiresolution MODWT Analysis in a Rainfall Forecast System
Año:2008

Áreas de investigación
  • Procesado y análisis de la señal

Datos
Descripción
During 30 years, expert meteorologists have been sampling meteorological measurements directly related to the rainfall event, in order to improve the current forecast procedures. This study performs the Feature Extraction and Feature Selection processes to extract the relevant information in the rainfall event. The Feature Extraction has been performed with a Multiresolution Analysis applying the Maxima OverlapWavelet Transform. The selection of the wavelet decomposition, was obtained applying a Sequential Feature Selection algorithm based on General Regression Neural Networks. In this paper, it is also presented a novel architecture to perform short and medium term weather forecasts based on Neural Networks and time series estimation filters. The preliminary results obtained, present this architecture as a feasible alternative to the current forecast procedures performed by super computer simulation centers.
Internacional
Si
Nombre congreso
The 12th World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2008
Tipo de participación
960
Lugar del congreso
Orlando, FL, EEUU
Revisores
No
ISBN o ISSN
1-934272-30-2
DOI
Fecha inicio congreso
28/06/2008
Fecha fin congreso
02/07/2008
Desde la página
69
Hasta la página
73
Título de las actas
Proceedings of the 12th World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2008. Volume VIII. Port-Conference Issue

Esta actividad pertenece a memorias de investigación

Participantes

Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Automatización en Señal y Comunicaciones (GASC)
  • Departamento: Matemática Aplicada a la Ingeniería Agronómica
  • Departamento: Señales, Sistemas y Radiocomunicaciones
  • Centro o Instituto I+D+i: Centro de Estudios e Investigación para la Gestión de Riesgos Agrarios Medioambientales (CEIGRAM)