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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