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, et al
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
Show full item record

SCOPUSTM   
Citations

6
checked on Dec 1, 2024

WEB OF SCIENCETM
Citations

2
checked on Feb 25, 2024

Page view(s)

75
checked on Jan 6, 2024

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.