Temperature prediction based on different meteorological series

Título:	Temperature prediction based on different meteorological series
Autores/as:	Vásquez, José L. Travieso, Carlos M. Travieso, Carlos M. Alonso, Jesús B. Briceno, Juan C.
Clasificación UNESCO:	3307 Tecnología electrónica
Palabras clave:	Artificial neural networks , Temperature measurement , Time series analysis , Predictive models , Temperature distribution , Solar radiation , Rain , Temperature prediction , meteorological serie , neural networks
Fecha de publicación:	2012
Publicación seriada:	Proceedings - 2012 3rd Global Congress on Intelligent Systems, GCIS 2012
Conferencia:	2012 3rd Global Congress on Intelligent Systems, GCIS 2012
Resumen:	In this work, a temperature predictor has been designed and implemented based on different series of meteorological data. The prediction is built by an artificial neural network multilayer perceptron, using 5 samples as window size of meteorological data. Besides, the floating point algorithm was evaluated, reaching a mean square error of 0.35, meaning a variation of 0.28 Celsius degrees versus the real temperature. Different approaches will be applied in order to show our best proposal.
URI:	http://hdl.handle.net/10553/44022
ISBN:	9780769548609
ISSN:	2155-6083
DOI:	10.1109/GCIS.2012.103
Fuente:	Proceedings - 2012 3rd Global Congress on Intelligent Systems, GCIS 2012 (6449495), p. 104-107
Colección:	Actas de congresos

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