Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/44022
| 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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