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(Article of periodic en Anglais - 1995)

Document title

Application of artificial neural networks in climatology: a case study of sunspot prediction and solar climate trends

Authors(s) and Affiliation(s)

GOPAL S. ; SCUDERI L. ;

Abstract

Global temperature trends on time scales of years to centuries have recently been shown to be related to volcanic aerosols, carbon dioxide levels, and solar activity. The most visible and well-studied indicators of solar variability are dark areas or sunspots on the surface of the Sun, with sunspot numbers directly related to the level of solar activity. In this paper the AA. show some preliminary findings in using feedforward neural networks for the prediction of peak sunspot cycle amplitude and discuss the climatic implications of the findings

Source

Article of periodic

published at : Geographical analysis / ISSN 0016-7363

Editor : Ohio State University Press, Columbus, OH - ETATS-UNIS (1969)

Millesime : 1995, vol. 27, no1 [pp. 42-59]

Bibliographic references : 57 ref.

Collation : Illustration ;

Language

Anglais

INIST-CNRS, Cote INIST : 17078

Tous droits réservés © Prodig - Bibliographie Géographique Internationale (BGI), 1995.
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