Conception of Geomagnetic Data Integrated Space

Q3 Mathematics SPIIRAS Proceedings Pub Date : 2019-04-12 DOI:10.15622/SP.18.2.390-415
A. Vorobev, G. Vorobeva, N. Yusupova
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引用次数: 0

Abstract

. As is known, today the problem of geomagnetic field and its variations parameters monitoring is solved mainly by a network of magnetic observatories and variational stations, but a significant obstacle in the processing and analysis of the data thus obtained, along with their spatial anisotropy, are omissions or reliable inconsistency with the established format. Heterogeneity and anomalousness of the data excludes (significantly complicates) the possibility of their automatic integration and the application of frequency analysis tools to them. Known solutions for the integration of heterogeneous geomagnetic data are mainly based on the consolidation model and only partially solve the problem. The resulting data sets, as a rule, do not meet the requirements for real-time information systems, may include outliers, and omissions in the time series of geomagnetic data are eliminated by excluding missing or anomalous values from the final sample, which can obviously lead to both to the loss of relevant information, violation of the discretization step, and to heterogeneity of the time series. The paper proposes an approach to creating an integrated space of geomagnetic data based on a combination of consolidation and federalization models, including preliminary processing of the original time series with an optionally available procedure for their recovery and verification, focused on the use of cloud computing technologies and hierarchical format and processing speed of large amounts of data and, as a result, providing users with better and more homogeneous data.
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地磁数据集成空间的概念
。众所周知,目前地磁场及其变化参数监测问题主要是通过地磁观测站和变分站网络来解决的,但在对这些数据进行处理和分析的过程中,一个重要的障碍是数据的遗漏或与既定格式的可靠不一致,以及数据在空间上的各向异性。数据的异质性和异常性排除了(显著复杂化)它们的自动集成和频率分析工具的应用的可能性。已知的非均质地磁数据整合方法主要基于固结模型,只能部分解决问题。得到的数据集通常不满足实时信息系统的要求,可能存在异常值,通过从最终样本中剔除缺失或异常值来消除地磁数据时间序列中的遗漏,这显然会导致相关信息的丢失,违反离散化步骤,并导致时间序列的异质性。本文提出了一种基于整合和联邦化相结合的地磁数据综合空间构建方法,包括对原始时间序列进行初步处理,并可选择恢复和验证程序,重点利用云计算技术和海量数据的分层格式和处理速度,从而为用户提供更好、更均匀的数据。
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来源期刊
SPIIRAS Proceedings
SPIIRAS Proceedings Mathematics-Applied Mathematics
CiteScore
1.90
自引率
0.00%
发文量
0
审稿时长
14 weeks
期刊介绍: The SPIIRAS Proceedings journal publishes scientific, scientific-educational, scientific-popular papers relating to computer science, automation, applied mathematics, interdisciplinary research, as well as information technology, the theoretical foundations of computer science (such as mathematical and related to other scientific disciplines), information security and information protection, decision making and artificial intelligence, mathematical modeling, informatization.
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