模拟总电子含量的极值:以塞尔维亚为例

Pub Date : 2017-12-31 DOI:10.15233/GFZ.2017.34.12
M. T. Drakul, Mileva Samardžić Petrović, S. Grekulović, O. Odalović, D. Blagojević
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引用次数: 0

摘要

本文致力于模拟塞尔维亚境内的极端TEC(总电子含量)值。对于极端TEC值,我们考虑了2013年、2014年和2015年11年太阳活动周期中冬夏至和秋春分日的最大值。平均TEC值在10至12 UT(世界时)之间进行处理。作为所有处理的基础数据,我们使用了位于塞尔维亚境内的三个常设站获得的GNSS(全球导航卫星系统)观测数据。这些数据,我们接受为实际的,即作为一个“真实的TEC值”。本研究的主要目的是研究使用两种机器学习技术的可能性:神经网络和支持向量机。为了强调应用技术的质量,所有结果都与使用国际参考电离层全球模式获得的TEC值进行了充分的比较。此外,我们还分别分析了整个时间和时空方法的技术质量。
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Modelling extreme values of the total electron content: Case study of Serbia
This paper is dedicated to modeling extreme TEC (Total Electron Content) values at the territory of Serbia. For the extreme TEC values, we consider the maximum values from the peak of the 11-year cycle of solar activity in the years 2013, 2014 and 2015 for the days of the winter and summer solstice and autumnal and vernal equinox. The average TEC values between 10 and 12 UT (Universal Time) were treated. As the basic data for all processing, we used GNSS (Global Navigation Satellite System) observation obtained by three permanent stations located in the territory of Serbia. Those data, we accept as actual, i.e. as a “true TEC values”. The main objectives of this research were to examine the possibility to use two machine learning techniques: neural networks and support vector machine. In order to emphasize the quality of applied techniques, all results are adequately compared to the TEC values obtained by using International Reference Ionosphere global model. In addition, we separately analyzed the quality of techniques throughout temporal and spatial-temporal approach.
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