Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44022
Title: Temperature prediction based on different meteorological series
Authors: Vásquez, José L.
Travieso, Carlos M. 
Travieso, Carlos M. 
Alonso, Jesús B. 
Briceno, Juan C.
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Artificial neural networks , Temperature measurement , Time series analysis , Predictive models , Temperature distribution , Solar radiation , Rain , Temperature prediction , meteorological serie , neural networks
Issue Date: 2012
Journal: Proceedings - 2012 3rd Global Congress on Intelligent Systems, GCIS 2012
Conference: 2012 3rd Global Congress on Intelligent Systems, GCIS 2012 
Abstract: 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
Source: Proceedings - 2012 3rd Global Congress on Intelligent Systems, GCIS 2012 (6449495), p. 104-107
Appears in Collections:Actas de congresos
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