Articles

Optimization of the management system for mitigating the consequences of water area pollution during the crisis

• 
• 

User Rating:  / 0

PoorBest 

Details

Category: Content №6 2021

Last Updated on 29 December 2021

Published on 30 November -0001

Hits: 5051

Authors:

S.V.Kotenko, orcid.org/0000-0003-2977-095X, Institute of Market Problems and Economic-Ecological Research of the National Academy of Sciences of Ukraine, Odesa, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

N.D.Maslii, orcid.org/0000-0002-3472-5646, Institute of Market Problems and Economic-Ecological Research of the National Academy of Sciences of Ukraine, Odesa, Ukraine; Odessa I.I.Mechnikov National University, Odesa, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

V.A.Kasianova, orcid.org/0000-0002-6302-366X, Private institution of higher education Odessa University of Technology Shah, Odesa, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

M.G.Bezpartochnyi, orcid.org/0000-0003-3765-7594, National Aerospace University named after N.Zhukovsky Kharkiv Aviation Institute, Kharkiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

I.I.Nadtochii, orcid.org/0000-0003-0693-8000, Admiral Makarov National University of Shipbuilding, Kherson Branch, Kherson, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2021, (6): 118 - 123

https://doi.org/10.33271/nvngu/2021-6/118

Abstract:

Purpose. The study is aimed at optimizing and reducing delays in crisis situations in the operation of decision support systems to eliminate the consequences of pollution of water areas.

Methodology. The presented study uses the fundamental provisions of modern science to find the optimal solution in crisis situations. Methods of abstraction and mathematical formalization were used to solve the problem of minimizing the delay time of information packets in providing critical information in conditions of overloading information channels.

Findings. It has been proven that a decrease in the volume of losses is possible in the case of effective management of the elimination of pollution, prompt minimization of its consequences. It has been established that the effectiveness of management to minimize the consequences of an accident is determined by the effectiveness of the information system, and largely depends not only on relevant information, but also on the timeliness of its receipt by the subject of decision-making. A mathematical model and an algorithm for optimizing information flows have been created, which provide minimal delays in obtaining information even under conditions of extreme load of the information system. It has been proven that the task of effective management of an information system can be reduced to minimizing the delay in the provision of critical information. As a result of the study, it was found that for a large information system, which includes more than forty subunits and satellite systems, the use of the proposed approach provides a decrease in the response delay to an information request of time, which does not exceed a minute.

Originality. To prevent delays in the operation of the information management system for the elimination of pollution of water areas, a scientific and applied approach to optimize the information system is proposed, which uses the theory of graphs and Ant Colony Optimization Algorithm and implements effective management of information flow. A mathematical model and an original algorithm have been developed that allow reducing delays in work and providing a resource utilization factor better than the existing analogues.

Practical value. The presented approach will make it possible to increase the efficiency and reliability of information systems for managing technogenic pressure on water areas in crisis situations, reduce the time for providing the necessary information and, thereby, reduce the consequences of pollution and the costs associated with their neutralization. The data obtained in the course of the study are approximated by a polynomial equation, making it possible to evaluate the effectiveness of using the proposed method depending on the number of nodes of the information system and the requirements for limiting the delay time of information.

Keywords: man-caused load, marine environment, management, information system, algorithm

References.

1. Burkinsky, B.V., Ilchenko, S.V., Rubel, O.E., & Kotenko, S.V. (2020). Information and analytical support for the protection of the marine environment from man-made impact, according to the general ed. Burkinsky B.V.; NAS of Ukraine, Inst. market and econ.-ecol. research. Odesa: IPREED NASU.

2. Bezsonov, Ye., Andreev, V., & Smyrnov, V. (2016). Assessment of safety index for water ecological system. Eastern-uropean journal of enterprise technologies, 6/10(84), 24-34. https://doi.org/10.15587/1729-4061.2016.86170.

3. Udod, V., Madzhd, S., & Kulynych, Ya. (2017). Regional features of structural and functional properties of technogenically transformed aquatic ecosystems. Transactions of Kremenchuk M. Ostrohradskyi National University, 3(1), 93-99.

4. Uberman, V., & Vaskovets, L. (2018). Approximation of the system of determination, assessment and regulation of surface water quality to EU law. Sustainable Development state and prospects: proceedings of the international scientific symposium SDEV2018, 63-66. Retrieved from http://ena.lp.edu.ua:8080/handle/ntb/43230.

5. Iduk, U., & Nitonye, S. (2015). Effects and Solutions of Marine Pollution from Ships in Nigerian Waterways. International Journal of Scientific and Engineering Research, 6(9), 81-90.

6. zdemir, ., & Yilmaz, H. E. (2016). Investigation of Marine Pollution Caused by Ship Operations with DEMATEL Method. International Journal on Marine Navigation and Safety of Sea Transportation, 10(2), 315-320. https://doi.org/10.12716/1001.10.02.14.

7. Mokhtari, S., Hosseini, S.M., Danehkar, A., Azad,M.T., Kadlec,J., Jolma, A., & Naimi, B. (2015). Inferring spatial distribution of oil spill risks from proxies: Case study in the north of the Persian Gulf. Ocean & Coastal Management, 116, 504-511. https://doi.org/10.1016/j.ocecoaman.2015.08.017.

8. Nevalainen, M., Helle, I., & Vanhatalo, J. (2017). Preparing for the unprecedented Towards quantitative oil risk assessment in the Arctic marine areas. Marine Pollution Bulletin, 114, 90-101. https://doi.org/10.1016/j.marpolbul.2016.08.064.

9. Byrnes, T.A., & Dunn, R.J.K. (2020). Boating- and Shipping-Related Environmental Impacts and Example Management Measures: A Review. Journal of Marine Science and Engineering, 8(11), 908. https://doi.org/10.3390/jmse8110908.

10. Grasso, R., Cococcioni, M., Mourre, B., Chiggiato, J., & Rixen,M. (2012). A maritime decision support system to assess risk in the presence of environmental uncertainties: the REP10 experiment. Ocean Dynamics, 62, 469-493. https://doi.org/10.1007/s10236-011-0512-6.

11. Moroni, D., Pieri, G., & Tampucci, M. (2019). Environmental Decision Support Systems for Monitoring Small Scale Oil Spills: Existing Solutions, Best Practices and Current Challenges. Journal of Marine Science and Engineering, 7(19), 1-17. https://doi.org/10.3390/jmse7010019.

12. Jolma, A., Lehikoinen, A., Helle, I., & Venesjrvi, R. (2014). Asoftware system for assessing the spatially distributed ecological risk posed by oil shipping. Environmental Modelling & Software, 61, 1-11. https://doi.org/10.1016/j.envsoft.2014.06.023.

13. Zodiatis, G., De Dominicis, M., Perivoliotis, L., Radhakrishnan,H., Georgoudis, E., Sotillo, M., ..., & Clementi, E. (2016). The Mediterranean Decision Support System for Marine Safety dedicated to oil slicks predictions. Deep Sea Research Part II: Topical Studies in Oceanography, 133, 4-20. https://doi.org/10.1016/j.dsr2.2016.07.014.

14. Alves, T.M., Kokinou, E., Zodiatis, G., Radhakrishnan, H., Panagiotakis, C., & Lardner, R. (2016). Multidisciplinary oil spill modeling to protect coastal communities and the environment of the Eastern Mediterranean Sea. Scientific Reports, 6, 36882. https://doi.org/10.1038/srep36882.

15. Kriazhych, O.O., & Kovalenko, O.V. (2015). Some issues of sustainability of information technologies of technogenic safety management. Decision support systems. Theory and practice, 170-173.

16. Ievdin, Ye.O. (2015). Methodology of integration of mathematical models of the environment into decision-making support systems. Decision support systems. Theory and practice, 74-77.

17. Kopeichykov, V.V., & Kovtun, V.A. (2015). Features of assessment of efficiency of distributed networks of situation centers in state administration. Decision support systems. Theory and practice, 135-138. Retrieved from http://conf.atsukr.org.ua/conf_files/conf_dir_24/Kopeychykov_sppr2015.pdf.

18. Sreznevsky, B. (2019). Central Geophysical Observatory. Review of the state of environmental pollution on the territory of Ukraine according to the observations of hydrometeorological organizations in 2019. Retrieved from http://cgo-sreznevskyi.kyiv.ua/index.php?fn=u_zabrud&f=ukraine.

19. DHI (2021). Marine Environment Decision Support. Retrieved from http://www.waterforecast.com/forecastservices/marineenvironmentdecisionsupport.

20. lanas-Sitja, I., Deneubourg, J.-L., Gibon, C., & Sempo, G. (2015). Group personality during collective decision-making: a multi-level approach. Proceedings of the Royal Society B, 282, 20142515, 1-9. https://doi.org/10.1098/rspb.2014.2515.

21. Dayal, U., Wilkinson, K., Simitsis, A., Castellanos, M., & Paz, L. (2012). Optimization of Analytic Data Flows for Next Generation Business Intelligence Applications. In: Nambiar, R., & Poess, M. (Eds.) Topics in Performance Evaluation, Measurement and Characterization. TPCTC 2011. Lecture Notes in Computer Science, 7144, 46-66. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-32627-1_4.

22. Ilchenko, S.V., Kotenko, S.V., & Kasianova, V.A. (2020). Theoretical-applied principles of formation of information and analytical support of protection of the marine environment from vessel pollution, Economic innovation, 22(4(77)), 73-82. https://doi.org/10.31520/ei.2020.22.4(77).73-82.

• < Prev
• Next >