MODELING AND PREDICTING SUNSPOT ACTIVITY - STATE-SPACE RECONSTRUCTIONPLUS ARTIFICIAL NEURAL-NETWORK METHODS

Authors
KULKARNI DR PANDYA AS PARIKH JC
Citation
Dr. Kulkarni et al., MODELING AND PREDICTING SUNSPOT ACTIVITY - STATE-SPACE RECONSTRUCTIONPLUS ARTIFICIAL NEURAL-NETWORK METHODS, Geophysical research letters, 25(4), 1998, pp. 457-460
Citations number
12
Categorie Soggetti
Geosciences, Interdisciplinary
Journal title
Geophysical research letters → ACNP
ISSN journal
00948276
Volume
25
Issue
4
Year of publication
1998
Pages
457 - 460
Database
ISI
SICI code
0094-8276(1998)25:4<457:MAPSA->2.0.ZU;2-H
Abstract
Ideas of state space reconstruction of dynamics are combined with nonp arametric artificial neural network approach to model sunspot activity . The structural aspects of the model are for the most part determined from the sunspot data. The model gives a very good fit to the data. F urther it predicts weaker solar activity in the current (23-rd) cycle, with a maximum of 144 +/- 36.