Local Rainfall Forecast System based on Time Series Analysis and Neural Networks

Buendia Buendia, Fulgencio; Tarquis Alfonso, Ana Maria; Buendia, G. y Andina de la Fuente, Diego (2010). Local Rainfall Forecast System based on Time Series Analysis and Neural Networks. En: "European Geosciences Union General Assembly 2010", 02/05/2010 - 07/05/2010, Viena, Austria.

Descripción

Título: Local Rainfall Forecast System based on Time Series Analysis and Neural Networks
Autor/es:
  • Buendia Buendia, Fulgencio
  • Tarquis Alfonso, Ana Maria
  • Buendia, G.
  • Andina de la Fuente, Diego
Tipo de Documento: Ponencia en Congreso o Jornada (Póster)
Título del Evento: European Geosciences Union General Assembly 2010
Fechas del Evento: 02/05/2010 - 07/05/2010
Lugar del Evento: Viena, Austria
Título del Libro: Geophysical Research Abstracts
Fecha: 2010
Volumen: 12
Materias:
Escuela: E.T.S.I. Agrónomos (UPM) [antigua denominación]
Departamento: Matemática Aplicada a la Ingeniería Agronómica [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Rainfall is one of the most important events in daily life of human beings. During several decades, scientists have been trying to characterize the weather, current forecasts are based on high complex dynamic models. In this paper is presented a local rainfall forecast system based on Time Series analysis and Neural Networks. This model tries to complement the currently state of the art ensembles, from a locally historical perspective, where the model definition is not so dependent from the exact values of the initial conditions. After several year taking data, expert meteorologists proposed this approximation to characterize the local weather behavior, that is being automated by this system in different stages. However the whole system is introduced, it is focused on the different rainfall events situation classification as well as the time series analysis and forecast

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ID de Registro: 8066
Identificador DC: http://oa.upm.es/8066/
Identificador OAI: oai:oa.upm.es:8066
Depositado por: Memoria Investigacion
Depositado el: 03 Ene 2012 11:49
Ultima Modificación: 20 Abr 2016 16:59
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