DocumentCode :
2788754
Title :
Sunspot numbers forecasting using neural networks
Author :
Li, Ming ; Mehrotra, Kishan ; Mohan, Chilulcuri ; Ranka, Sanjay
Author_Institution :
Sch. of Comput. & Inf. Sci., Syracuse Univ., NY, USA
fYear :
1990
fDate :
5-7 Sep 1990
Firstpage :
524
Abstract :
A recurrent connectionist network has been designed to model sunspot data. The network architecture, sunspot data, and statistical models are described, and experimental results are provided. This preliminary experimental work shows that the network can produce competitive prediction results that compare with those of traditional autoregressive models. The method is not problem specific and could be applied to other problems in dynamical system modeling, recognition, prediction, and control fields
Keywords :
geophysics computing; neural nets; weather forecasting; autoregressive models; competitive prediction; control fields; dynamical system modeling; model sunspot data; neural networks; recurrent connectionist network; statistical models; Artificial neural networks; Biological neural networks; Computer networks; Geology; Information science; Modeling; Neural networks; Predictive models; Statistical analysis; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control, 1990. Proceedings., 5th IEEE International Symposium on
Conference_Location :
Philadelphia, PA
ISSN :
2158-9860
Print_ISBN :
0-8186-2108-7
Type :
conf
DOI :
10.1109/ISIC.1990.128507
Filename :
128507
Link To Document :
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