Analysis of time series by the example of registration of variations in the gravitational field

Authors

  • R.Z. Burtiev Institute of Geology and Seismology of the Academy of Sciences of Moldova, Moldova, Republic of
  • Yu.V. Semenova Subbotin Institute of Geophysics of the National Academy of Sciences of Ukraine, Ukraine
  • V.T. Kiriyak Technical University of Moldova, Moldova, Republic of
  • E.V. Sidorenko Technical University of Moldova, Moldova, Republic of
  • S.V. Troyan Institute of Geology and Seismology of the Academy of Sciences of Moldova, Moldova, Republic of
  • V.Yu. Kardanets Institute of Geology and Seismology of the Academy of Sciences of Moldova, Moldova, Republic of
  • D.I. Nuka Technical University of Moldova, Moldova, Republic of

DOI:

https://doi.org/10.24028/gzh.v43i4.239960

Abstract

In this work, a time series model is used to study the structure of gravimetric data series to identify patterns in the change in the levels of the series and build its model in order to predict and study the relationships between the levels of gravimetric data. Observations of the activity of geophysical processes showed that the periods of variations in geophysical processes are scattered chaotically on the time axis. According to their schedule, it is impossible to definitely speak about the regularity in the duration of the periods of variations, and in the alternation of periods of seismic calm with a period of high seismic activity. The impetus for this study was the desire to analyze the structure of a number of formal methods to search for statistical patterns in the variations of geophysical parameters over time. Time series models were used to study the dynamics of geophysical events. Forecasting was carried out using the SPSS 20 package and EXCEL 2016. The accuracy of the forecast is indicated by the comparison of the forecast series with the actual data. The predicted values of the gravimetric data are within the confidence intervals. If you start forecasting too early, the forecast may differ from the forecast based on all statistical data. If the data shows seasonal trends, it is recommended to start forecasting from the date before the last point of the statistical data. Spatial and time series models can be used to study the dynamics of geophysical events. A spatial model describes a set of geophysical parameters at a given point in time. A time series is a series of regular observations of a certain parameter at successive points in time or at intervals of time. In this work, the time series model is used: to identify the statistical relationship between the frequency and depth of occurrence of earthquakes, as well as to identify the statistical dependence of these data on gravimetric variations; determination of patterns in the change in the levels of the series and the construction of its model in order to predict and study the relationships between geophysical phenomena.

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Published

2021-10-05

How to Cite

Burtiev, R. ., Semenova, Y. ., Kiriyak, V. ., Sidorenko, E., Troyan, S. ., Kardanets, V., & Nuka, . D. (2021). Analysis of time series by the example of registration of variations in the gravitational field. Geofizicheskiy Zhurnal, 43(4), 76–90. https://doi.org/10.24028/gzh.v43i4.239960

Issue

Vol. 43 No. 4 (2021)

Section

Articles

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