Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/43955
| Título: | Forecast of temperature using support vector machines | Autores/as: | Pérez-Vega, Abrahán Travieso, Carlos M. Hernández-Travieso, José G. Alonso, Jesus B. Dutta, Malay Kishore Singh, Anushikha |
Clasificación UNESCO: | 3307 Tecnología electrónica | Palabras clave: | Kernel Support vector machines Training Meteorology Testing, et al. |
Fecha de publicación: | 2017 | Publicación seriada: | Proceeding - IEEE International Conference on Computing, Communication and Automation, ICCCA 2016 | Conferencia: | 2016 IEEE International Conference on Computing, Communication and Automation, ICCCA 2016 | Resumen: | This paper proposes a prediction system to make a forecast of temperature which is based on support vector machines. The system uses a database which provides information about weather parameters such as pressure, temperature, wind speed, etc. In order to adapt the input data, the present proposal has applied a pre-processing method before the prediction phases start. The best testing results have reached a mean square error of 0.09°C. | URI: | http://hdl.handle.net/10553/43955 | ISBN: | 9781509016662 | DOI: | 10.1109/CCAA.2016.7813752 | Fuente: | Proceeding - IEEE International Conference on Computing, Communication and Automation, ICCCA 2016 (7813752), p. 388-392 |
| Colección: | Actas de congresos |
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