DocumentCode :
2014326
Title :
Study on prediction modeling of the artificial neural network from the combination of multivariate analysis and mean generation function
Author :
Long, Jin ; Ying, Luo ; Yonghua, Li
Author_Institution :
Guangxi Meteorological Bur., Nanning, China
Volume :
3
fYear :
2002
fDate :
2002
Firstpage :
2440
Abstract :
A mixed prediction model involving a significant period of a predictand the physical factors influencing the change of predictand is built based on an artificial neural network from the combination of multivariate analysis and mean generation function. The new model is found to have a higher predicative accuracy (due mainly to the reasonable analysis for prediction method), when compared to results from multivariate statistical model or mean generating function prediction model.
Keywords :
geophysics computing; meteorology; modelling; neural nets; statistical analysis; artificial neural network; mean generation function; mixed prediction model; multivariate analysis; predicative accuracy; predictand; prediction modeling; Artificial neural networks; Automation; Intelligent control; Meteorology; Prediction methods; Predictive models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
Type :
conf
DOI :
10.1109/WCICA.2002.1021530
Filename :
1021530
Link To Document :
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