DocumentCode
3236505
Title
Temperature Prediction Based on Different Meteorological Series
Author
Vasquez, Jose Luis ; Travieso, Carlos M. ; Perez, T.S. ; Alonso, Jesus B. ; Briceno, J.C.
Author_Institution
Sede del Atlantico, Univ. of Costa Rica, Cartago, Costa Rica
fYear
2012
fDate
6-8 Nov. 2012
Firstpage
104
Lastpage
107
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.
Keywords
climatology; geophysics computing; meteorology; multilayer perceptrons; artificial neural network multilayer perceptron; floating point algorithm; meteorological series; temperature prediction; Artificial neural networks; Predictive models; Rain; Solar radiation; Temperature distribution; Temperature measurement; Time series analysis; Temperature prediction; meteorological serie; neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems (GCIS), 2012 Third Global Congress on
Conference_Location
Wuhan
Print_ISBN
978-1-4673-3072-5
Type
conf
DOI
10.1109/GCIS.2012.103
Filename
6449495
Link To Document