dc.contributor.author | Eroğlu, Emre | |
dc.date.accessioned | 2021-12-12T17:02:22Z | |
dc.date.available | 2021-12-12T17:02:22Z | |
dc.date.issued | 2021 | |
dc.identifier.issn | 1866-7511 | |
dc.identifier.issn | 1866-7538 | |
dc.identifier.uri | https://doi.org/10.1007/s12517-021-08816-3 | |
dc.identifier.uri | https://hdl.handle.net/20.500.11857/3443 | |
dc.description.abstract | This essay investigates the first four moderate geomagnetic activities (the 04 January storm, the 07 January storm, the 17 February storm, and the 24 February storm) of 2015 in the 24th solar cycle. The essay attempts to understand these storms with the aid of zonal geomagnetic indices. It predicts the zonal geomagnetic indices (Dst, ap, AE) of the storms by an artificial neural network model. The phenomena that occurred in January and February are discussed by taking into account the solar wind parameters (B-z, E, P, N, v, T) and the zonal geomagnetic indices obtained from NASA. In the study, after glancing at the general appearance of the year 2015, which is exhibited with too small errors, binary correlations of the variables are indicated by the covariance matrix and the hierarchical cluster of the variables is presented by at dendrogram. The artificial neural network model is governed by the physical principles in the paper. The model uses the solar wind parameters as inputs and the zonal geomagnetic indices as outputs. The causality principle forms the models by cause-effect association. The back propagation algorithm is specified as Levenberg-Marquardt (trainlm), and 35 neural numbers are utilized in the artificial neural network. The neural network model predicts the Dst, ap, and AE indices of January and February geomagnetic storms with an accuracy that deserves discussion. The R correlation coefficients of the Dst, ap, and AE indices reach up to 98.9%. In addition to reliable accuracy, the parameters affecting the R correlation coefficients agree with the literature. Estimating the geomagnetic activities may support interplanetary works. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Springer Heidelberg | en_US |
dc.relation.ispartof | Arabian Journal of Geosciences | en_US |
dc.identifier.doi | 10.1007/s12517-021-08816-3 | |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Solar wind parameters (SWp) | en_US |
dc.subject | Zonal geomagnetic indices (ZGi) | en_US |
dc.subject | Artificial neural network (ANN) | en_US |
dc.title | Analysis of the first four moderate geomagnetic storms of the year 2015 | en_US |
dc.type | article | |
dc.department | Fakülteler, Fen-Edebiyat Fakültesi, Matematik Bölümü | |
dc.identifier.volume | 14 | en_US |
dc.identifier.issue | 23 | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.identifier.wos | WOS:000720727100013 | en_US |
dc.institutionauthor | Eroğlu, Emre | |