Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11765/3809
Bayesian networks for probabilistic weather prediction
Title: Bayesian networks for probabilistic weather prediction
Authors: Cofiño, Antonio S.Cano Trueba, RafaelSordo, Carmen MaríaGutiérrez Llorente, José Manuel
Keywords: Time series prediction; Bayesian Networks; Acyclic graph; Rainfall forecast; Probabilistic weather prediction
Issue Date: 2002
Citation: XV European Conference on Artificial Intelligence (2002)
Abstract: Several standard approaches have been introduced for meteorological time series prediction (analog techniques, neural networks, etc.). However, when dealing with multivariate spatially distributed time series (e.g., a network of meteorological stations over the Iberian peninsula) the above methods do not consider all the available information (they consider special independency assumptions to simplify the model). In this work, we introduce Bayesian Networks (BNs) in this framework to model the spatial and temporal dependencies among the different stations using a directed acyclic graph.
Description: Ponencia presentada en: 15th European Conference on Artificial Intelligence celebrada los días 21-26 de julio en Lyon, Francia
URI: http://hdl.handle.net/20.500.11765/3809
Appears in Collections:Otras actas-congresos


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