Prediction of the Smoothed Monthly Mean Sunspot Numbers by Means of RBF (Radial Basic Function) Neural Networks
Author:
Affiliation:
1. National Astronomical Observatories; Chinese Academy of Sciences; Beijing; 100012,; China
Publisher
Wiley
Subject
General Medicine
Link
http://onlinelibrary.wiley.com/wol1/doi/10.1002/cjg2.1190/fullpdf
Reference18 articles.
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2. A method for the prediction of relative sunspot number for the remainder of a progressing cycle with application to cycle 23;Li;A&A,2002
3. Estimating the size and timing of the maximum amplitude of solar cycle 24;Li;ChJAA,2005
4. The Schwabe and Gleissberg periods in the wolf sunspot numbers and the group sunspot numbers;Li;Solar Phys.,2005
5. A method of predicting the smoothed monthly mean sunspot numbers in solar cycle 23;Zhao;ChJAA,2004
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1. A Hybrid Model Based on CEEMDAN-GRU and Error Compensation for Predicting Sunspot Numbers;Electronics;2024-05-13
2. A Hybrid Model for Forecasting Sunspots Time Series Based on Variational Mode Decomposition and Backpropagation Neural Network Improved by Firefly Algorithm;Computational Intelligence and Neuroscience;2018-10-14
3. Predication of Sunspot Number Based on Parallel Process Neural Networks;Applied Mechanics and Materials;2013-09
4. The Hierarchical Hybrid Fuzzy-Neural Network Based on Lasso Function and Its Application to Classification of Remote Sensing Images;Chinese Journal of Geophysics;2011-07
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