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Comparison of neural network and McNish and Lincoln methods for the prediction of the smoothed sunspot index

✍ Scribed by Françoise Fessant; Catherine Pierret; Pierre Lantos

Publisher
Springer
Year
1996
Tongue
English
Weight
585 KB
Volume
168
Category
Article
ISSN
0038-0938

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✦ Synopsis

In this paper we propose a comparison between two methods for the problem of hmg-term prediction of the smoothed sunspot index. These two methods are first thc classical method of McNish and Lincoln (as improved by Stewart and Ostrow), and second a neural network method. The results of these two methods are compared in two periods, during the ascending and the declining phases of the current cycle 22 . The predictions with neural networks arc lnuch better than with the MeNish and Lincoln method Ibr the atypical ascending phase of cyclc 22. During the second period thc predictions ;are very similar, and in agreement with observations, when the McNish and l,incoln method is based on the data of declining phases of the cycles.

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