Correlation between sunspots and interplanetary shocks measured by ACE during 1998-2014 and some estimations for the 22nd solar cycle and the years between 2015 and 2018 with artificial neural network using the Cavus 2013 model

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dc.authoridCavus, Huseyin/0000-0003-4224-7039
dc.authoridCoban, Gani Caglar/0000-0003-0185-190X
dc.contributor.authorCavus, Huseyin
dc.contributor.authorAraz, Gokhan
dc.contributor.authorCoban, Gani Caglar
dc.contributor.authorRaheem, Abd-ur
dc.contributor.authorKarafistan, Aysel I.
dc.date.accessioned2025-01-27T20:31:58Z
dc.date.available2025-01-27T20:31:58Z
dc.date.issued2020
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractThe Advanced Composition Explorer (ACE) spacecraft has measured 235 solar-based interplanetary (IP) shock waves between the years of 1998-2014. These were composed of 203 fast forward (FF), 6 slow forward (SF), 21 fast reverse (FR) and 5 slow reverse (SR) type shocks. These data can be obtained from the Interplanetary Shock Database of Harvard-Smithsonian Centre for Astrophysics. The Solar Section of American Association of Variable Star Observers (AAVSO) is an organization that counts the number of the sunspots. The effects of interplanetary shock waves on some physical parameters can be computed using a hydrodynamical model. There should be some correlations between these effects and the sunspot variations. The major objective of this paper is twofold. The first one is to search these correlations with sunspots given in the database of AAVSO. As expected, high correlations between physical parameters and sunspots have been obtained and these are presented in tables below. The second objective is to make an estimation of these parameters for the 22nd solar cycle and the years between 2015 and 2018 using an artificial neural network. Predictions have been made for these years where no shock data is present using artificial intelligence. The correlations were observed to increase further when these prediction results were included. (C) 2019 COSPAR. Published by Elsevier Ltd. All rights reserved.
dc.description.sponsorshipTUBITAK [117F336]
dc.description.sponsorshipThis paper was supported by TUBITAK 117F336 project. Data files can be obtained from https://www.drop-box.com/sh/156tvnjf0zwrhny/AACsvH2fvTRi9mFG_Yo UwprFa?d1=0.
dc.identifier.doi10.1016/j.asr.2019.09.056
dc.identifier.endpage1047
dc.identifier.issn0273-1177
dc.identifier.issn1879-1948
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85074886170
dc.identifier.scopusqualityQ1
dc.identifier.startpage1035
dc.identifier.urihttps://doi.org/10.1016/j.asr.2019.09.056
dc.identifier.urihttps://hdl.handle.net/20.500.12428/23317
dc.identifier.volume65
dc.identifier.wosWOS:000514016200012
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Sci Ltd
dc.relation.ispartofAdvances in Space Research
dc.relation.publicationcategoryinfo:eu-repo/semantics/openAccess
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20250125
dc.subjectInterplanetary shocks
dc.subjectSolar activity
dc.subjectSunspots
dc.subjectArtificial Neural Network
dc.subjectEstimation
dc.titleCorrelation between sunspots and interplanetary shocks measured by ACE during 1998-2014 and some estimations for the 22nd solar cycle and the years between 2015 and 2018 with artificial neural network using the Cavus 2013 model
dc.typeArticle

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