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| Titel |
A logistic regression model for predicting the occurrence of intense geomagnetic storms |
| VerfasserIn |
N. Srivastava |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
0992-7689
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| Digitales Dokument |
URL |
| Erschienen |
In: Annales Geophysicae ; 23, no. 9 ; Nr. 23, no. 9 (2005-11-22), S.2969-2974 |
| Datensatznummer |
250015366
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| Publikation (Nr.) |
 copernicus.org/angeo-23-2969-2005.pdf |
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| Zusammenfassung |
| A logistic regression model is
implemented for predicting the occurrence of intense/super-intense
geomagnetic storms. A binary dependent variable, indicating the
occurrence of intense/super-intense geomagnetic storms, is
regressed against a series of independent model variables that
define a number of solar and interplanetary properties of
geo-effective CMEs. The model parameters (regression coefficients)
are estimated from a training data set which was extracted from a dataset
of 64 geo-effective CMEs observed during 1996-2002. The trained
model is validated by predicting the occurrence of geomagnetic
storms from a validation dataset, also extracted from the same
data set of 64 geo-effective CMEs, recorded during 1996-2002, but
not used for training the model. The model predicts 78% of the
geomagnetic storms from the validation data set. In addition, the
model predicts 85% of the geomagnetic storms from the training
data set. These results indicate that logistic regression models
can be effectively used for predicting the occurrence of intense
geomagnetic storms from a set of solar and interplanetary factors. |
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