ANALYSIS OF THE TERRESTRIAL POLE COORDINATES USING REGRESSION DYNAMIC MODELING
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| Publicado en: | International Multidisciplinary Scientific GeoConference : SGEM vol. 18, no. 2.2 (2018), p. 73 |
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| Autor Principal: | |
| Outros autores: | , , , |
| Publicado: |
Surveying Geology & Mining Ecology Management (SGEM)
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| Acceso en liña: | Citation/Abstract Full Text Full Text - PDF |
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| 001 | 2185857199 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1314-2704 | ||
| 024 | 7 | |a 10.5593/sgem2018/2.2/S08.010 |2 doi | |
| 035 | |a 2185857199 | ||
| 045 | 0 | |b d20180101 | |
| 084 | |a 176728 |2 nlm | ||
| 100 | 1 | |a Andreev, Alexey |u Kazan Federal University, Kazan, Russia | |
| 245 | 1 | |a ANALYSIS OF THE TERRESTRIAL POLE COORDINATES USING REGRESSION DYNAMIC MODELING | |
| 260 | |b Surveying Geology & Mining Ecology Management (SGEM) |c 2018 | ||
| 513 | |a Conference Proceedings | ||
| 520 | 3 | |a For processing observations of the terrestrial pole dynamics, the regression dynamic modeling (RDM) approach was used. With the RDM software package the models describing the dynamics of the terrestrial polar coordinates were built. This approach provides accurate combined models of observations which describe to some extent causal and deterministic communication and provide forecast of characteristics. A comparison of observations and predicted values of the terrestrial polar coordinates obtained with the RDM approach and by other researchers is performed. To solve the problem, the expansion of the RDM automated systems was made. The basic version is supplemented by new software modules for the developed technique and geophysical observations features. The RDM software package intended for processing geophysical characteristics contains the modules as follows: 1) A spectral window to transform uneven observations to even ones; 2) Cross-spectral analysis to identify common significant harmonics of two observations; 3) Kalman Filter to eliminate noise from the residues of a model; 4) Fractal analysis to verify the series on trendstability; 5) Set of wavelets; 6) Processing scenarios to build the best on the "external" standard deviation model of (SD) model of Time series (TS) automatically. | |
| 651 | 4 | |a North Pole | |
| 653 | |a Research | ||
| 653 | |a Analysis | ||
| 653 | |a Software packages | ||
| 653 | |a Fractal analysis | ||
| 653 | |a Modelling | ||
| 653 | |a Communication | ||
| 653 | |a Software | ||
| 653 | |a Polar coordinates | ||
| 653 | |a Researchers | ||
| 653 | |a Spectral analysis | ||
| 653 | |a Modules | ||
| 653 | |a Time series | ||
| 653 | |a Dynamic models | ||
| 653 | |a Terrestrial environments | ||
| 653 | |a Wavelet analysis | ||
| 653 | |a Fractal models | ||
| 653 | |a Kalman filters | ||
| 653 | |a Dynamics | ||
| 653 | |a Computer programs | ||
| 653 | |a Physics | ||
| 653 | |a Hypotheses | ||
| 653 | |a Geophysics | ||
| 653 | |a Stochastic models | ||
| 653 | |a Regression analysis | ||
| 653 | |a Computer software | ||
| 653 | |a Economic | ||
| 653 | |a Environmental | ||
| 700 | 1 | |a Nefedyev, Yury |u Kazan Federal University, Kazan, Russia | |
| 700 | 1 | |a Mubarakshina, Regina |u Kazan Federal University, Kazan, Russia | |
| 700 | 1 | |a Demina, Natalya |u Kazan Federal University, Kazan, Russia | |
| 700 | 1 | |a Demin, Sergey |u Kazan Federal University, Kazan, Russia | |
| 773 | 0 | |t International Multidisciplinary Scientific GeoConference : SGEM |g vol. 18, no. 2.2 (2018), p. 73 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2185857199/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/2185857199/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2185857199/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |