| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1769075 | Advances in Space Research | 2006 | 6 Pages |
Abstract
A new approach of exploring, predicting and explaining solar activity is introduced. The Lund Solar Activity Model (LSAM) is based on new wavelet methods and a hybrid physics-based neural network. The model uses as input different kinds of indicators of solar activity. Different time scales of solar activity are selected with scalograms and ampligrams. The processes behind the variability are revealed with wavelet time scale spectra. How new solar laws could be discovered with neural networks and how solar theory could be coded into neural networks are then discussed. Finally, forecasts and explanations are described with LSAM.
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Space and Planetary Science
Authors
H. Lundstedt,