1. SISN
  2. All Volumes and Issues
  3. Volume 13, 2023
  4. Database development for intellectual system for research of space weather parameters

Database development for intellectual system for research of space weather parameters

SISN.
2023;
Volume 13
: pp. 329 - 337
https://doi.org/10.23939/sisn2023.13.329
Authors:
  1. Danylo Ivantyshyn
  2. Yevhen Burov
1
Lviv Polytechnic National University, Ukraine
2
Lviv Polytechnic National University, Information Systems and Networks Department

An analysis of the helio- and geo-activity subject area has been carried out, which become a ground for the main essences of space weather indices, their attributes and connections between them were determined. An ER-diagram was constructed and a logical scheme of the database of the intelligent system for the research of space weather parameters was developed. The scientific novelty of the obtained results relies on the development of a database model of an intelligent system for the research of space weather parameters. The practical significance of the obtained results lies in the possibilities of filling the database on manifestations of solar activity, their processing, analysis and establishment of connections between indicators of helio- and geoactivity.

intelligent system database
database modeling
solar activity
solar-terrestrial connections
  1. Buzulukova N., Tsurutani B. (2022). Space Weather: From solar origins to risks and hazards evolving in time. Front. Astron. Space Sci., Vol. 9, 1017103. DOI: 10.3389/fspas.2022.1017103.
  2. Hapgood M., Liu H., Lugaz N. (2022). SpaceX-Sailing close to the space weather? Space Weather, Vol. 20, e2022SW003074.    https://doi.org/10.1029/2022SW003074.
  3. Fang T.-W., Kubaryk A., Goldstein D., et al. (2022). Space weather environment during the SpaceX Starlink satellite loss in February. Space Weather, Vol. 20, e2022SW003193. https://doi.org/10.1029/ 2022SW003193.
  4. The Sun and Space Weather (Astrophysics and Space Science Library) (Second Edition) by A. Hanslmeier, 2008, 326 p.
  5. Plainaki C., Antonucci M., Bemporad A. et al. (2020). Current state and perspectives of Space Weather science in Italy. J. Space Weather Space Clim., Vol. 10, 6.
  6. Veretenenko S. (2022). Stratospheric Polar Vortex as an Important Link between the Lower Atmosphere Circulation and Solar Activity. Atmosphere, Vol. 13(7), 1132. https://doi.org/10.3390/atmos13071132.
  7. Schrijver C., Kauristie K., Aylward A. D., et al. (2015). Understanding space weather to shield society: A global road map for 2015–2025 commissioned by COSPAR and ILWS. Adv. Space Res., Vol. 55, 2745–2807. https://doi.org/10.1016/j.asr.2015.03.023.
  8. Singh A. K., Bhargawa A., Siingh D., Singh R. P. (2021). Physics of Space Weather Phenomena: A Review. Geosciences, Vol. 11(7), 286. https://doi.org/10.3390/geosciences11070286.
  9. Kutiev І., Tsagouri І., Perrone L., et al. (2013). Solar activity impact on the Earth’s upper atmosphere. J. Space Weather Space Clim., Vol. 3, A06. https://doi.org/10.1051/swsc/2013028.
  10. Tsagouri I. (2022). SpaceWeather Effects on the Earth’s Upper Atmosphere: Short Report on Ionospheric Storm Effects at Middle Latitudes. Atmosphere, Vol. 13(2), 346. https://doi.org/10.3390/atmos13020346.
  11. Astafyeva E., Zakharenkova I., Huba J. D., et al. (2017). Global ionospheric and thermospheric effects of the June 2015 geomagnetic disturbances: Multi-instrumental observations and modeling. J. Geophys. Res.: Space Phys., Vol. 122,  11716–11742. https://doi.org/10.1002/2017JA024174.
  12. Bhaskar A., Vichare G. (2019). Forecasting of SYMH and ASYH indices for geomagnetic storms of solar cycle 24 including St. Patricks day, 2015 storm using NARX neural network. J. Space Weather Space Clim., Vol. 9, A12.    https://doi.org/10.1051/swsc/2019007.
  13. Wanliss, J. A., Showalter K. M. (2006). High-resolution global storm index: Dstversus SYM-H. J. Geophys Res., Vol. 111(2), A02202. https://doi.org/10.1029/2005JA011034.
  14. Park W., Lee J, Kim K-C Lee J, et al. (2021). Operational Dst index prediction model based on combination of artificial neural network and empirical model. J. Space Weather Space Clim., Vol. 11, 38. https://doi.org/10.1051/swsc/2021021.
  15. Carley E. P., Baldovin C., Benthem P., et al. (2020). Radio observatories and instrumentation used in space weather science and operations. J. Space Weather Space Clim., Vol. 10, 7. https://doi.org/10.1051/ swsc/2020007.
  16. Pasichnyk V. V., Reznichenko V. A. (2006). Organization of databases and knowledge. K.:  BHV Publishing Group, 384 p.