AbstractNowadays operational models for solar activity forecasting are still based on the statistical relationship between solar activity and solar magnetic field evolution. In order to set up this relationship, many parameters have been proposed to be the measures. Conventional measures are based on the sunspot group classification which provides limited information from sunspots. For this reason, new measures based on solar magnetic field observations are proposed and a solar flare forecasting model supported with an artificial neural network is introduced. This model is equivalent to a person with a long period of solar flare forecasting experience.


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    Title :

    Solar flare forecasting model supported with artificial neural network techniques


    Contributors:
    Wang, H.N. (author) / Cui, Y.M. (author) / Li, R. (author) / Zhang, L.Y. (author) / Han, H. (author)

    Published in:

    Advances in Space Research ; 42 , 9 ; 1464-1468


    Publication date :

    2007-06-29


    Size :

    5 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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