DocumentCode :
1857020
Title :
Forecasting Sunspot Numbers with Recurrent Neural Networks (RNN) Using ´Sunspot Neural Forecaster´ System
Author :
Samin, Reza Ezuan ; Kasmani, Ruhaila Md ; Khamis, Azme ; Isa, Syahirbanun
Author_Institution :
Fac. of Electr. & Electron. Eng., Univ. Malaysia Pahang, Kuantan, Malaysia
fYear :
2010
fDate :
2-3 Dec. 2010
Firstpage :
10
Lastpage :
14
Abstract :
This paper presents the investigations of forecasting performance of different type of Recurrent Neural Networks (RNN) in forecasting the sunspot numbers. Recurrent Neural Network will be used in this investigation by using different learning algorithms, sunspot data models and RNN transfer functions. Simulations are done using Matlab 7 where customized Graphic User Interface (GUI) called `Sunspot Neural Forecaster´ have been developed for analysis. A complete analysis for different learning algorithms, sunspot data models and RNN transfer functions are examined in terms of Mean Square Error(MSE) and correlation analysis. Finally, the best optimized RNN parameters will be used to forecast the sunspot numbers.
Keywords :
astronomy computing; sunspots; Matlab 7; RNN transfer functions; correlation analysis; forecasting performance; graphic user interface; learning algorithms; mean square error; recurrent neural networks; sunspot data models; sunspot neural forecaster system; sunspot numbers; Algorithm design and analysis; Analytical models; Artificial neural networks; Forecasting; Mathematical model; Predictive models; Recurrent neural networks; Mean Square Error (MSE); Recurrent Neural Networks (RNN); Sunspot numbers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Computing, Control and Telecommunication Technologies (ACT), 2010 Second International Conference on
Conference_Location :
Jakarta
Print_ISBN :
978-1-4244-8746-2
Electronic_ISBN :
978-0-7695-4269-0
Type :
conf
DOI :
10.1109/ACT.2010.50
Filename :
5675853
Link To Document :
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