RUS  ENG
Full version
JOURNALS // Informatics and Automation // Archive

Tr. SPIIRAN, 2019 Issue 18, volume 2, Pages 390–415 (Mi trspy1050)

This article is cited in 2 papers

Artificial Intelligence, Knowledge and Data Engineering

Conception of geomagnetic data integrated space

A. V. Vorobev, G. R. Vorobeva, N. I. Yusupova

Ufa State Aviation Technical University (USATU)

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.

Keywords: geomagnetic data, magnetic observatories, time series, big data, integrated information space, parallel computing.

UDC: 004.95

Received: 14.01.2019

DOI: 10.15622/sp.18.2.390-415



Bibliographic databases:


© Steklov Math. Inst. of RAS, 2024