Automatic method for estimation of the Earth's magnetic field state

V. Geppener, O. Mandrikova, E. Zhizhikina
{"title":"Automatic method for estimation of the Earth's magnetic field state","authors":"V. Geppener, O. Mandrikova, E. Zhizhikina","doi":"10.1109/SCM.2015.7190473","DOIUrl":null,"url":null,"abstract":"This paper describes a method developed by the authors for estimating the state of the Earth's magnetic field. The method is based on the combination of wavelet transform with radial basis neural networks. The method includes decomposing of recorded geomagnetic field variations on different scale components, estimating their disturbance degree and forming conclusion about the state of the field. For approbation of the method, we used geomagnetic data from the \"Paratunka\" station (Paratunka, Kamchatka region, data registration is carried out by IKIR FEB RAS). The analysis of the spectral-temporal characteristics of geomagnetic field variations during periods of moderate and strong magnetic storms was performed. Weak perturbations were detected in the geomagnetic field before the storms. Obtained results confirmed the effectiveness of the proposed method.","PeriodicalId":106868,"journal":{"name":"2015 XVIII International Conference on Soft Computing and Measurements (SCM)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 XVIII International Conference on Soft Computing and Measurements (SCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCM.2015.7190473","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

This paper describes a method developed by the authors for estimating the state of the Earth's magnetic field. The method is based on the combination of wavelet transform with radial basis neural networks. The method includes decomposing of recorded geomagnetic field variations on different scale components, estimating their disturbance degree and forming conclusion about the state of the field. For approbation of the method, we used geomagnetic data from the "Paratunka" station (Paratunka, Kamchatka region, data registration is carried out by IKIR FEB RAS). The analysis of the spectral-temporal characteristics of geomagnetic field variations during periods of moderate and strong magnetic storms was performed. Weak perturbations were detected in the geomagnetic field before the storms. Obtained results confirmed the effectiveness of the proposed method.
估计地球磁场状态的自动方法
本文介绍了作者提出的一种估算地球磁场状态的方法。该方法将小波变换与径向基神经网络相结合。该方法将记录的地磁场变化在不同尺度分量上进行分解,估计其扰动程度,得出地磁场状态的结论。为了验证该方法,我们使用了“Paratunka”站的地磁数据(堪察加半岛Paratunka地区,数据注册由IKIR FEB RAS进行)。分析了中、强磁暴期间地磁场变化的谱时特征。在风暴之前,在地磁场中检测到微弱的扰动。实验结果证实了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信