Development of complex methodology of processing heterogeneous data in intelligent decision support systems

Authors

DOI:

https://doi.org/10.15587/1729-4061.2020.208554

Keywords:

decision support system, monitoring object, different types of data, computational complexity, information processing, type of information

Abstract

The complex methodology for processing heterogeneous data in intelligent decision support systems is developed. This method is made to increase the efficiency of processing heterogeneous data in intelligent decision support systems. The complex methodology consists of the following interrelated procedures: heterogeneous data storing model; heterogeneous data synchronization algorithm; heterogeneous data separation algorithm; heterogeneous data indexing algorithm. The model of storing heterogeneous intelligence data, which is the basis of the methodology, differs in the presence of templates of intelligence objects and parameter templates of intelligence objects. Templates allow storing both unstructured heterogeneous intelligence data and structured intelligence data according to a defined pattern, which reduces the time to access the data. In the heterogeneous intelligence data storage model, a heterogeneous intelligence data synchronization algorithm, heterogeneous intelligence data separation algorithm and heterogeneous intelligence data indexing algorithm are developed. The development of the proposed technique is due to the need to increase the efficiency of processing various information types in intelligent decision support systems with acceptable computational complexity. The proposed method allows increasing the efficiency of intelligent decision support systems through integrated processing of data circulating in them. The proposed method allows increasing the efficiency of information processing in decision support systems from 16 to 20 % depending on the amount of information about the monitoring object

Author Biographies

Pavlo Zuiev, General Staff of the Armed Forces of Ukraine Povitroflotsky ave., 6, Kyiv, Ukraine, 03168

PhD, Head Deputy

Ruslan Zhyvotovskyi, Central Scientifically-Research Institute of Arming and Military Equipment of the Armed Forces of Ukraine Povitroflotskyi ave., 28, Kyiv, Ukraine, 03168

PhD, Senior Researcher, Head of Research Department

Research Department of the Development of Anti-Aircraft Missile Systems and Complexes

Oleksii Zvieriev, Central Scientifically-Research Institute of Arming and Military Equipment of the Armed Forces of Ukraine Povitroflotskyi ave., 28, Kyiv, Ukraine, 03168

PhD, Associate Professor, Researcher

Research Department of the Development of Anti-Aircraft Missile Systems and Complexes

Serhiy Hatsenko, Ivan Chernyakhovsky National Defense University of Ukraine Povitrofloski ave., 28, Kyiv, Ukraine, 03049

PhD, Deputy Head of Department

Department of Intelligence

Volodymyr Kuprii, Military Unit A 0135 Povitroflotsky ave., 6, Kyiv, Ukraine, 03168

PhD, Associate Professor, Head Specialist of Department

Oleksandr Nakonechnyi, Institute for Support of Troops (Forces) and Information Technologies Ivan Chernyakhovsky National Defense University of Ukraine Povitrofloski ave., 28, Kyiv, Ukraine, 03049

Adjunct

Mykhailo Adamenko, Ivan Chernyakhovsky National Defense University of Ukraine Povitrofloski ave., 28, Kyiv, Ukraine, 03049

PhD, Head of Laboratory

Research Laboratory

Department of Intelligence

Andrii Shyshatskyi, Central Scientifically-Research Institute of Arming and Military Equipment of the Armed Forces of Ukraine Povitroflotskyi ave., 28, Kyiv, Ukraine, 03168

PhD, Senior Researcher

Research Department of Electronic Warfare Development

Yevhenii Neroznak, Military institute of telecommunications and informatization named after Heroes of Kruty Moskovsky str., 45/1, Kyiv, Ukraine, 01011

Adjunct

Department of Automated Control Systems

Vira Velychko, Military institute of telecommunications and informatization named after Heroes of Kruty Moskovsky str., 45/1, Kyiv, Ukraine, 01011

Lecturer

Department of Automated Control Systems

References

  1. Makridenko, L. A., Volkov, S. N., Hodnenko, V. P. (2010). Kontseptual'nye voprosy sozdaniya i primeneniya malyh kosmicheskih apparatov. Voprosy elektromehaniki, 114, 15–26.
  2. Bashkirov, O. M., Kostina, O. M., Shishats'kiy, A. V. (2015). Development of integrated communication systems and data transfer for the needs of the Armed Forces. Weapons and military equipment, 5 (1), 35–39.
  3. Trotsenko, R. V., Bolotov, M. V. (2014). Data extraction process for heterogeneous sources. Privolzhskiy nauchnyy vestnik, 12-1 (40), 52–54.
  4. Bodyanskiy, E., Strukov, V., Uzlov, D. (2017). Generalized metrics in the problem of analysis of multidimensional data with different scales. Zbirnyk naukovykh prats Kharkivskoho universytetu Povitrianykh Syl, 3, 98–101.
  5. Noh, B., Son, J., Park, H., Chang, S. (2017). In-Depth Analysis of Energy Efficiency Related Factors in Commercial Buildings Using Data Cube and Association Rule Mining. Sustainability, 9 (11), 2119. doi: https://doi.org/10.3390/su9112119
  6. Petras, V., Petrasova, A., Jeziorska, J., Mitasova, H. (2016). Processing UAV and lidar point clouds in Grass GIS. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B7, 945–952. doi: https://doi.org/10.5194/isprs-archives-xli-b7-945-2016
  7. Polovina, S., Radic, B., Ristic, R., Milcanovic, V. (2016). Spatial and temporal analysis of natural resources degradation in the Likodra River watershed. Glasnik Sumarskog Fakulteta, 114, 169–188. doi: https://doi.org/10.2298/gsf1614169p
  8. Poryadin, I., Smirnova, E. (2017). Binary Classification Method of Social Network Users. Science and Education of the Bauman MSTU, 17 (02), 121–137. doi: https://doi.org/10.7463/0217.0000915
  9. Tymchuk, S. (2017). Methods of Complex Data Processing from Technical Means of Monitoring. Path of Science, 3 (3), 4.1–4.9. doi: https://doi.org/10.22178/pos.20-4
  10. Semenov, V. V., Lebedev, I. S. (2019). Processing of signal information in problems of monitoring information security of unmanned autonomous objects. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 19 (3), 492–498. doi: https://doi.org/10.17586/2226-1494-2019-19-3-492-498
  11. Zhou, S., Yin, Z., Wu, Z., Chen, Y., Zhao, N., Yang, Z. (2019). A robust modulation classification method using convolutional neural networks. EURASIP Journal on Advances in Signal Processing, 2019 (1). doi: https://doi.org/10.1186/s13634-019-0616-6
  12. Zhang, D., Ding, W., Zhang, B., Xie, C., Li, H., Liu, C., Han, J. (2018). Automatic Modulation Classification Based on Deep Learning for Unmanned Aerial Vehicles. Sensors, 18 (3), 924. doi: https://doi.org/10.3390/s18030924
  13. Kukulska, A., Salata, T., Cegielska, K., Szylar, M. (2018). Methodology of evaluation and correction of geometric data topology in QGIS software. Acta Scientiarum Polonorum Formatio Circumiectus, 17 (1), 125–138. doi: https://doi.org/10.15576/asp.fc/2018.17.1.125
  14. Rulev, A., Yuferev, V. (2015). Theory of geoinformatic mapping of erosion geomorphological systems. Vestnik Volgogradskogo Gosudarstvennogo Universiteta. Serija 11. Estestvennye Nauki, 4, 62–67. doi: https://doi.org/10.15688/jvolsu11.2015.4.7
  15. Yousefi, M., Kreuzer, O. P., Nykänen, V., Hronsky, J. M. A. (2019). Exploration information systems – A proposal for the future use of GIS in mineral exploration targeting. Ore Geology Reviews, 111, 103005. doi: https://doi.org/10.1016/j.oregeorev.2019.103005
  16. Ashkezari, A. D., Hosseinzadeh, N., Chebli, A., Albadi, M. (2018). Development of an enterprise Geographic Information System (GIS) integrated with smart grid. Sustainable Energy, Grids and Networks, 14, 25–34. doi: https://doi.org/10.1016/j.segan.2018.02.001
  17. Wang, S., Zhong, Y., Wang, E. (2019). An integrated GIS platform architecture for spatiotemporal big data. Future Generation Computer Systems, 94, 160–172. doi: https://doi.org/10.1016/j.future.2018.10.034
  18. Wan-Mohamad, W. N. S., Abdul-Ghani, A. N. (2011). The Use of Geographic Information System (GIS) for Geotechnical Data Processing and Presentation. Procedia Engineering, 20, 397–406. doi: https://doi.org/10.1016/j.proeng.2011.11.182
  19. Pedro, J., Silva, C., Pinheiro, M. D. (2019). Integrating GIS spatial dimension into BREEAM communities sustainability assessment to support urban planning policies, Lisbon case study. Land Use Policy, 83, 424–434. doi: https://doi.org/10.1016/j.landusepol.2019.02.003
  20. Mokhtara, C., Negrou, B., Settou, N., Gouareh, A., Settou, B. (2019). Pathways to plus-energy buildings in Algeria: design optimization method based on GIS and multi-criteria decision-making. Energy Procedia, 162, 171–180. doi: https://doi.org/10.1016/j.egypro.2019.04.019
  21. Kalantaievska, S., Pievtsov, H., Kuvshynov, O., Shyshatskyi, A., Yarosh, S., Gatsenko, S. et. al. (2018). Method of integral estimation of channel state in the multiantenna radio communication systems. Eastern-European Journal of Enterprise Technologies, 5 (9 (95)), 60–76. doi: https://doi.org/10.15587/1729-4061.2018.144085
  22. Karin, S. A. (2012). Integration in the single information space of heterogeneous geospatial data. Informatsionno-upravlyayushchie sistemy, 2, 89–94.
  23. Karin, S. A. (2014). Developing a domain-specific ontology in spatial data processing systems. Informatsionno-upravlyayushchie sistemy, 4, 78–84.
  24. Belousov, S. M. (2006). Matematicheskaya model' mnogopotochnoy sistemy massovogo obsluzhivaniya, upravlyaemoy planirovshchikom resursov. Vestnik Novosibirskogo gosudarstvennogo universiteta. Ser.: Informatsionnye tehnologii, 4 (1), 14–26.
  25. Karin, C. A., Dudin, E. A. (2014). Podhody k sozdaniyu raspredelennoy sistemy sbora, hraneniya i obrabotki geoprostranstvennyh dannyh. Informatsiya i kosmos, 3, 46–51.
  26. Koshlan, A., Salnikova, O., Chekhovska, M., Zhyvotovskyi, R., Prokopenko, Y., Hurskyi, T. et. al. (2019). Development of an algorithm for complex processing of geospatial data in the special-purpose geoinformation system in conditions of diversity and uncertainty of data. Eastern-European Journal of Enterprise Technologies, 5 (9 (101)), 35–45. doi: https://doi.org/10.15587/1729-4061.2019.180197
  27. Kuchuk, N., Mohammed, A. S., Shyshatskyi, A., Nalapko, O. (2019). The method of improving the efficiency of routes selection in networks of connection with the possibility of self-organization. International Journal of Advanced Trends in Computer Science and Engineering, 8 (1.2), 1–6. Available at: http://www.warse.org/IJATCSE/static/pdf/file/ijatcse01812sl2019.pdf

Downloads

Published

2020-08-31

How to Cite

Zuiev, P., Zhyvotovskyi, R., Zvieriev, O., Hatsenko, S., Kuprii, V., Nakonechnyi, O., Adamenko, M., Shyshatskyi, A., Neroznak, Y., & Velychko, V. (2020). Development of complex methodology of processing heterogeneous data in intelligent decision support systems. Eastern-European Journal of Enterprise Technologies, 4(9 (106), 14–23. https://doi.org/10.15587/1729-4061.2020.208554

Issue

Vol. 4 No. 9 (106) (2020): Information and controlling system

Section

Information and controlling system

License

Copyright (c) 2020 Pavlo Zuiev, Ruslan Zhyvotovskyi, Oleksii Zvieriev, Serhiy Hatsenko, Volodymyr Kuprii, Oleksandr Nakonechnyi, Mykhailo Adamenko, Andrii Shyshatskyi, Yevhenii Neroznak, Vira Velychko

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.

A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.