Skip to main content
SpringerLink
Log in
SpringerLink
Log in

Formal Modeling of Decision-Making Processes Under Transboundary Emergency Conditions

  • Chapter
  • First Online:
Data-Centric Business and Applications

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 42))

Abstract

This paper is dedicated to the problems of modeling of decision making processes in the case of emergency occurrence. In particular, the transboundary emergencies are considered which impose constraints on the data used for decision making as well as on the process itself. The transboundary character of emergencies implies that the sources of data for environmental monitoring may be unavailable and the data gathered from the available sources, which are spatially distributed and belong to different state rescue services, may be incomplete, inaccurate or duplicate. The given study represents three types of problems related to emergency situations management: prevention of emergencies; immediate reaction on emergence that has just occurred; elimination of emergency consequences. The formal problem statement of these problems forms the basis for decision support system design. The effective management solution in an emergency situation is represented in the form of a sequence of actions that need to be taken under conditions of limited resources available for the elimination of emergency consequences. The paper represents the rules that allow the transformation of conditions of the formal decision-making problem statement into knowledge used by the environment monitoring system.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Yannikov I, Ponomareva D (2017) Modern systems for monitoring and forecasting emergencies. In: Innovative technologies in engineering: a collection of works of the VIII international scientific and practical conference 2017, pp 209–213

    Google Scholar 

  2. Sanginova O, Bondarenko S, Andriyuk V (2017) Computer-integrated system of monitoring and forecasting the quality of water bodies. Mater V Int Water Forum Water Res Climate 2:146–149

    Google Scholar 

  3. Wang H, Xu Z, Pedrycz W (2017) An overview on the roles of fuzzy set techniques in big data processing: trends, challenges and opportunities. Knowl-Based Syst 118:15–30

    Article  Google Scholar 

  4. Zhukov A, Leonov P (2018) Problems of data collection for the application of the data mining methods in analyzing threshold levels of indicators of economic security. KnE Soc Sci Humanit 3(2):369–374

    Google Scholar 

  5. Power DJ, Sharda R, Burstein F (2015) Decision support systems. John Wiley & Sons, Ltd

    Google Scholar 

  6. Kryvinska N (2012) Building consistent formal specification for the service enterprise agility foundation. J Serv Sci Res 4(2):235–269 Springer, The Society of Service Science

    Article  Google Scholar 

  7. Henrique dos Santos P, Neves SM, Sant’Anna DO, Henrique de Oliveira C, Carvalho HD (2018) The analytic hierarchy process supporting decision making for sustainable development: an overview of applications. J Cleaner Prod. https://doi.org/10.1016/j.jclepro.2018.11.270

  8. King C, Thomas DSG (2014) Monitoring environmental change and degradation in the irrigated oases of the Northern Sahara. J Arid Environ 103:36–45

    Article  Google Scholar 

  9. Thu HN, Wehn U (2016) Data sharing in international transboundary contexts: the Vietnamese perspective on data sharing in the Lower Mekong Basin. J Hydrol 536:351–364

    Article  Google Scholar 

  10. Chettri N et al (2015) Long term environmental and socio-ecological monitoring in transboundary landscapes. International Centre for Integrated Mountain Development (ICIMOD), Kathmandu, Nepal

    Google Scholar 

  11. Mulema SA, García AC (2019) Monitoring of an aquatic environment in aquaculture using a MEWMA chart. Aquaculture. https://doi.org/10.1016/j.aquaculture.2019.01.019

    Article  Google Scholar 

  12. Kaczor S, Kryvinska N (2013) It is all about services—fundamentals, drivers, and business models. Serv Sci Res 5(2):125–154 Springer, The Society of Service Science

    Article  Google Scholar 

  13. Kryvinska N, Gregus M (2014) SOA and its business value in requirements, features, practices and methodologies. Comenius University, Bratislava

    Google Scholar 

  14. Razumov VV, Razumova NV, Alekseev OA (2017) Information requirements for terrestrial and space monitoring of precursors of natural and technogenic catastrophes on the border territories of Russia. Modern problems of remote sensing of the Earth from space 14(7):52–61

    Google Scholar 

  15. Transon J et al (2018) Survey of hyperspectral earth observation applications from space in the sentinel-2 context. Remote Sens 10(2):157

    Article  Google Scholar 

  16. Frohn RC, Lopez RD (2017) Remote sensing for landscape ecology: new metric indicators: monitoring, modeling, and assessment of ecosystems. CRC Press

    Google Scholar 

  17. Bilitewski U, Turner A (2014) Biosensors in environmental monitoring. CRC Press

    Google Scholar 

  18. Plutalova TG (2017) Monitoring of transboundary territories. Water and ecological problems of Siberia and Central Asia, pp 80

    Google Scholar 

  19. Shabanov VV, Markin VN (2015) Conducting monitoring of water bodies in modern conditions. Publishing house of RGAU-MAHA

    Google Scholar 

  20. Tkachenko V, Cherednichenko O, Godlevskyi M (2018) The concept of device meta-model for real-time communication in the transboundary environment monitoring system. In: Problems of infocommunications. science and technology: PIC S & T. Proceedings of the IEEE. Kharkiv, Ukraine

    Google Scholar 

  21. Furems E (2008) Knowledge-based multi-attribute classification problems structuring. computational intelligence in decision and control. World Scientific Publisher, Singapore, pp 465–470

    Google Scholar 

  22. Molnar E, Molnar R, Kryvinska N, Gregus M (2014) Web intelligence in practice. J Serv Sci Res 6(1):149–172 Springer, The Society of Service Science

    Article  Google Scholar 

  23. Tkachenko V, Cherednichenko O (2018) Information technologies of decision support in transboundary emergencies. aviation in the XXI century—safety in aviation and space technology. In: Proceeding of the eighth world congress. NAU, Kyiv, pp 94–98. Homepage. http://conference.nau.edu.ua/index.php/Congress/Congress2018/schedConf/presentations

  24. Kirichenko L, Radivilova T, Zinkevich I (2017) Forecasting weakly correlated time series in tasks of electronic commerce. In: Proceedings of 2017 12th international scientific and technical conference on computer sciences and information technologies (CSIT), Lviv, pp 309–312. https://doi.org/10.1109/stc-csit.2017.8098793

  25. Kirichenko L, Radivilova T, Zinkevich I (2018) Comparative analysis of conversion series forecasting in e-commerce tasks. In: Shakhovska N, Stepashko V (eds) Advances in intelligent systems and computing II. CSIT 2017. Advances in intelligent systems and computing, vol 689. Springer, Cham, pp 230–242. https://doi.org/10.1007/978-3-319-70581-1_16

  26. Gregus M, Kryvinska N (2015) Service orientation of enterprises—aspects, dimensions, technologies. Comenius University, Bratislava

    Google Scholar 

  27. Dobrynin I, Radivilova T, Maltseva N, Ageyev D (2018) Use of approaches to the methodology of factor analysis of information risks for the quantitative assessment of information risks based on the formation of cause-and-effect links. In: Proceedings of the 2018 international scientific-practical conference problems of infocommunications. Science and technology (PIC S & T), Kharkiv, Ukraine, pp 229–232. https://doi.org/10.1109/infocommst.2018.8632022

  28. Kirichenko L, Bulakh V, Radivilova T (2017) Fractal time series analysis of social network activities. In: Proceedings of the 2017 4th international scientific-practical conference problems of infocommunications. Science and technology (PIC S & T), Kharkov, Ukraine, pp 456–459. https://doi.org/10.1109/infocommst.2017.8246438

  29. Ageyev D (2010) NGN network planning according to criterion of provider’s maximum profit. In: Proceeding of the IEEE international conference on modern problems of radio engineering, telecommunications and computer science (TCSET-2010), pp 256–256

    Google Scholar 

  30. Ageyev D, Al-Ansari A, Qasim N (2015) Multi-Period LTE RAN and services planning for operator profit maximization. In: Proceeding of the IEEE the experience of designing and application of CAD systems in microelectronics, pp 25–27. https://doi.org/10.1109/cadsm.2015.7230786

  31. Bede B (2013) Mathematics of fuzzy sets and fuzzy logic. Springer, Berlin

    Book  Google Scholar 

  32. Kirichenko L, Radivilova T, Tkachenko A (2019) Comparative analysis of noisy time series clustering. In: Proceedings of the 3rd international conference on computational linguistics and intelligent systems (COLINS-2019), vol I. Kharkiv, Ukraine, Apr 18–19, pp 184-196

    Google Scholar 

  33. Ageyev D, Wehbe F (2013) Parametric synthesis of enterprise infocommunication systems using a multi-layer graph model. In: Proceeding of the IEEE 23rd international crimean conference microwave & telecommunication technology, pp 507–508

    Google Scholar 

  34. Al-Dulaimi A, Al-Dulaimi M, Ageyev D (2016) Realization of resource blocks allocation in LTE Downlink in the form of nonlinear optimization. In: Proceeding of the IEEE 13th international conference on modern problems of radio engineering, telecommunications and computer science (TCSET), pp 646–648. https://doi.org/10.1109/tcset.2016.7452140

  35. Liubartseva S, Coppini G, Pinardi N, De Dominicis M, Lecci R, Turrisi G et al (2016) Decision support system for emergency management of oil spill accidents in the Mediterranean Sea. Nat Hazards Earth Syst Sci 16(8):2009–2020

    Article  Google Scholar 

  36. Janža M (2014) A decision support system for emergency response to groundwater resource pollution in an urban area (Ljubljana, Slovenia). Environ Earth Sci 73(7):3763–3774

    Article  Google Scholar 

  37. Qi C, Fang J, Sun L (2018) Implementation of emergency logistics distribution decision support system based on GIS. Cluster Comput. https://doi.org/10.1007/s10586-018-1983-8

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Kharkiv Politechnic Institute, National Technical University, Kharkiv, Ukraine

    Olga Cherednichenko, Olha Yanholenko & Maryna Vovk

  2. Research Center of the Armed Forces of Ukraine “State Oceanarium”, Odesa, Ukraine

    Vasyl Tkachenko

Authors
  1. Olga Cherednichenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Olha Yanholenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Maryna Vovk
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Vasyl Tkachenko
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Olga Cherednichenko .

Editor information

Editors and Affiliations

  1. Department of Infocommunication Engineering, Faculty of Infocommunication, Kharkiv National University of Radio Electronics, Kharkiv, Ukraine

    Dmytro Ageyev

  2. Department of Infocommunication Engineering, Faculty of Infocommunication, Kharkiv National University of Radio Electronics, Kharkiv, Ukraine

    Tamara Radivilova

  3. Department of e-Business, Faculty of Business, Economics and Statistics, University of Vienna, Vienna, Austria

    Natalia Kryvinska

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Cherednichenko, O., Yanholenko, O., Vovk, M., Tkachenko, V. (2020). Formal Modeling of Decision-Making Processes Under Transboundary Emergency Conditions. In: Ageyev, D., Radivilova, T., Kryvinska, N. (eds) Data-Centric Business and Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 42. Springer, Cham. https://doi.org/10.1007/978-3-030-35649-1_7

Download citation

Publish with us

Policies and ethics

Search

Navigation