Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/43955
Title: Forecast of temperature using support vector machines
Authors: Pérez-Vega, Abrahán
Travieso, Carlos M. 
Hernández-Travieso, José G.
Alonso, Jesus B. 
Dutta, Malay Kishore
Singh, Anushikha
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Kernel
Support vector machines
Training
Meteorology
Testing
Automation
Databases
Prediction system ,
Support vector machines
Forecast of temperature
Issue Date: 2017
Journal: Proceeding - IEEE International Conference on Computing, Communication and Automation, ICCCA 2016
Conference: 2016 IEEE International Conference on Computing, Communication and Automation, ICCCA 2016 
Abstract: 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
Source: Proceeding - IEEE International Conference on Computing, Communication and Automation, ICCCA 2016 (7813752), p. 388-392
Appears in Collections:Actas de congresos
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