Analysis of detection of ecological hazard based on computing the measures of current recurrence of ecosystem states

Authors

DOI:

https://doi.org/10.15587/1729-4061.2018.147508

Keywords:

ecosystem, hazardous ecological state, recurrence plot, measure of recurrence, current recurrence in window

Abstract

Analysis of the early detection of an environmental hazard in ecosystems was performed. New measures of the current recurrence of states that allow their use for the early detection of an environmental hazard in ecosystems were proposed. Calculations of the measures under consideration are based on the distribution of the known measure of global recurrence for the case of the calculation of measures of current recurrence in moving square windows. In this case, one of the measures under consideration is based on the implementation of a moving square window along the main diagonal of the recurrent plot of state. Another measure is based on the use of a moving window of the specified size along the horizontal (vertical) axis of recurrence plots. The latter made it possible to obtain a constructive current measure for calculation of recurrence to identify dangerous states in ecosystems based on the temporal localization of zero recurrence of states at minimum sizes of a moving window. In accordance with the proposed measures of current recurrence, the possibilities of using the measures for the early identification of an environmental hazard for gas medium with the ignition center of combustible material, such as alcohol, were analyzed. It was shown that the window measure of current recurrence at a horizontal moving small­size window is the most suitable of the considered measures. It was found that for such a measure, window sizes must be in the range from 5×5 to 15×15 counts. In this case, the values of region ε of neighborhood for the considered states must be selected in the range from 0.01 to 0.15. It was determined theoretically and experimentally that the specified measure of current recurrence of states with a horizontally moving window can be considered as a structural current measure of recurrence to ensure a reliable early detection of hazardous states in different ecosystems

Author Biographies

Boris Pospelov, National University of Civil Defence of Ukraine Chernyshevska str., 94, Kharkiv, Ukraine, 61023

Doctor of Technical Sciences, Professor

Research Center

Yuliya Danchenko, Kharkiv National University of Civil Engineering and Architecture Sumska str., 40, Kharkiv, Ukraine, 61002

PhD, Associate Professor

Department of General Chemistry

Ilgar Firdovsi Dadashov, Academy of the ministry of Emergency Situations of Azerbaijanian Republic Elman Gasimov str., 8, Hovsan settlement, Baku, Azerbaijan, AZ1089

PhD

Department of the special disciplines and safety of vital functions

Stanislav Skliarov, National University of Civil Defence of Ukraine Chernyshevska str., 94, Kharkiv, Ukraine, 61023

PhD

Research Center

Stella Gornostal, National University of Civil Defence of Ukraine Chernyshevska str., 94, Kharkiv, Ukraine, 61023

PhD

Department of Fire Prevention in Settlements

Oleksandr Cherkashyn, National University of Civil Defence of Ukraine Chernyshevska str., 94, Kharkiv, Ukraine, 61023

PhD

Department of fire and rescue training

References

  1. Vasiliev, M. I., Movchan, I. O., Koval, O. M. (2014). Diminishing of ecological risk via optimization of fire-extinguishing system projects in timber-yards. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, 5, 106–113.
  2. Vasyukov, A., Loboichenko, V., Bushtec, S. (2016). Identification of bottled natural waters by using direct conductometry Ecology. Environment and Conservation, 22 (3), 1171–1176.
  3. Semko, A. N., Beskrovnaya, M. V., Vinogradov, S. A., Hritsina, I. N., Yagudina, N. I. (2014). The usage of high speed impulse liquid jets for putting out gas blowouts. Journal of Theoretical and Applied Mechanics, 52 (3), 655–664.
  4. Kondratenko, O. M., Vambol, S. O., Strokov, O. P., Avramenko, A. M. (2015). Mathematical model of the efficiency of diesel particulate matter filter. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, 6, 55–61.
  5. Loboichenko, V. M., Vasyukov, A. E., Tishakova, T. S. (2017). Investigations of Mineralization of Water Bodies on the Example of River Waters of Ukraine. Asian Journal of Water, Environment and Pollution, 14 (4), 37–41. doi: https://doi.org/10.3233/ajw-170035
  6. Ol’shanskii, V. P. (2004). Identification of the Parameters of a Nested Cylindrical Heat Source under Stationary Self-Heating of a Raw Material Mass of the Same Form. Journal of Engineering Physics and Thermophysics, 77 (1), 242–246. doi: https://doi.org/10.1023/b:joep.0000020747.49072.8b
  7. Pascual, M., Ellner, S. P. (2000). Linking Ecological Patterns to Environmental Forcing via Nonlinear Time Series Models. Ecology, 81 (10), 2767. doi: https://doi.org/10.2307/177340
  8. Parrott, L. (2004). Analysis of simulated long-term ecosystem dynamics using visual recurrence analysis. Ecological Complexity, 1 (2), 111–125. doi: https://doi.org/10.1016/j.ecocom.2004.01.002
  9. Proulx, R. (2007). Ecological complexity for unifying ecological theory across scales: A field ecologist's perspective. Ecological Complexity, 4 (3), 85–92. doi: https://doi.org/10.1016/j.ecocom.2007.03.003
  10. Kantz, H., Schreiber, T. (2003). Nonlinear time series analysis. Cambridge University Press. doi: https://doi.org/10.1017/cbo9780511755798
  11. Eckmann, J.-P., Kamphorst, S. O., Ruelle, D. (1987). Recurrence Plots of Dynamical Systems. Europhysics Letters (EPL), 4 (9), 973–977. doi: https://doi.org/10.1209/0295-5075/4/9/004
  12. Webber, Jr. C. L., Zbilut, J. P. (2005). Recurrence quantification analysis of nonlinear dynamical systems. Tutorials in contemporary nonlinear methods for the behavioral sciences, 26.
  13. Pospelov, B., Andronov, V., Rybka, E., Meleshchenko, R., Borodych, P. (2018). Studying the recurrent diagrams of carbon monoxide concentration at early ignitions in premises. Eastern-European Journal of Enterprise Technologies, 3 (9 (93)), 34–40. doi: https://doi.org/10.15587/1729-4061.2018.133127
  14. Poulsen, A., Jomaas, G. (2011). Experimental Study on the Burning Behavior of Pool Fires in Rooms with Different Wall Linings. Fire Technology, 48 (2), 419–439. doi: https://doi.org/10.1007/s10694-011-0230-0
  15. Pospelov, B., Andronov, V., Rybka, E., Meleshchenko, R., Gornostal, S. (2018). Analysis of correlation dimensionality of the state of a gas medium at early ignition of materials. Eastern-European Journal of Enterprise Technologies, 5 (10 (95)), 25–30. doi: https://doi.org/10.15587/1729-4061.2018.142995
  16. Zhang, D., Xue, W. (2010). Effect of heat radiation on combustion heat release rate of larch. Journal of West China Forestry Science, 39, 148.
  17. Andronov, V., Pospelov, B., Rybka, E. (2017). Development of a method to improve the performance speed of maximal fire detectors. Eastern-European Journal of Enterprise Technologies, 2 (9), 32–37. doi: https://doi.org/10.15587/1729-4061.2017.96694
  18. Pospelov, B., Andronov, V., Rybka, E., Skliarov, S. (2017). Design of fire detectors capable of self-adjusting by ignition. Eastern-European Journal of Enterprise Technologies, 4 (9 (88)), 53–59. doi: https://doi.org/10.15587/1729-4061.2017.108448
  19. Pospelov, B., Andronov, V., Rybka, E., Skliarov, S. (2017). Research into dynamics of setting the threshold and a probability of ignition detection by self­adjusting fire detectors. Eastern-European Journal of Enterprise Technologies, 5 (9 (89)), 43–48. doi: https://doi.org/10.15587/1729-4061.2017.110092
  20. Pospelov, B., Rybka, E., Meleshchenko, R., Gornostal, S., Shcherbak, S. (2017). Results of experimental research into correlations between hazardous factors of ignition of materials in premises. Eastern-European Journal of Enterprise Technologies, 6 (10 (90)), 50–56. doi: https://doi.org/10.15587/1729-4061.2017.117789
  21. Bendat, J. S., Piersol, A. G. (2010). Random data: analysis and measurement procedures. John Wiley & Sons. doi: https://doi.org/10.1002/9781118032428
  22. Shafi, I., Ahmad, J., Shah, S. I., Kashif, F. M. (2009). Techniques to Obtain Good Resolution and Concentrated Time-Frequency Distributions: A Review. EURASIP Journal on Advances in Signal Processing, 2009 (1). doi: https://doi.org/10.1155/2009/673539
  23. Singh, P. (2016). Time-frequency analysis via the fourier representation. HAL, 1–7. Available at: https://hal.archives-ouvertes.fr/hal-01303330
  24. Pospelov, B., Andronov, V., Rybka, E., Popov, V., Romin, A. (2018). Experimental study of the fluctuations of gas medium parameters as early signs of fire. Eastern-European Journal of Enterprise Technologies, 1 (10 (91)), 50–55. doi: https://doi.org/10.15587/1729-4061.2018.122419
  25. Pretrel, H., Querre, P., Forestier, M. (2005). Experimental Study Of Burning Rate Behaviour In Confined And Ventilated Fire Compartments. Fire Safety Science, 8, 1217–1228. doi: https://doi.org/10.3801/iafss.fss.8-1217
  26. Stankovic, L., Dakovic, M., Thayaparan, T. (2014). Time-frequency signal analysis. Kindle edition, Amazon, 655.
  27. Avargel, Y., Cohen, I. (2010). Modeling and Identification of Nonlinear Systems in the Short-Time Fourier Transform Domain. IEEE Transactions on Signal Processing, 58 (1), 291–304. doi: https://doi.org/10.1109/tsp.2009.2028978
  28. Giv, H. H. (2013). Directional short-time Fourier transform. Journal of Mathematical Analysis and Applications, 399 (1), 100–107. doi: https://doi.org/10.1016/j.jmaa.2012.09.053
  29. Pospelov, B., Andronov, V., Rybka, E., Popov, V., Semkiv, O. (2018). Development of the method of frequency­temporal representation of fluctuations of gaseous medium parameters at fire. Eastern-European Journal of Enterprise Technologies, 2 (10 (92)), 44–49. doi: https://doi.org/10.15587/1729-4061.2018.125926
  30. Grassberger, P., Procaccia, I. (1983). Measuring the strangeness of strange attractors. Physica D: Nonlinear Phenomena, 9 (1-2), 189–208. doi: https://doi.org/10.1016/0167-2789(83)90298-1
  31. Wolf, A., Swift, J. B., Swinney, H. L., Vastano, J. A. (1985). Determining Lyapunov exponents from a time series. Physica D: Nonlinear Phenomena, 16 (3), 285–317. doi: https://doi.org/10.1016/0167-2789(85)90011-9
  32. Marwan, N., Kurths, J., Saparin, P. (2007). Generalised recurrence plot analysis for spatial data. Physics Letters A, 360 (4-5), 545–551. doi: https://doi.org/10.1016/j.physleta.2006.08.058
  33. Dombrádi, E., Timár, G., Bada, G., Cloetingh, S., Horváth, F. (2007). Fractal dimension estimations of drainage network in the Carpathian–Pannonian system. Global and Planetary Change, 58 (1-4), 197–213. doi: https://doi.org/10.1016/j.gloplacha.2007.02.011
  34. Schirdewan, A., Gapelyuk, A., Fischer, R., Koch, L., Schütt, H., Zacharzowsky, U. et. al. (2007). Cardiac magnetic field map topology quantified by Kullback-Leibler entropy identifies patients with hypertrophic cardiomyopathy. Chaos: An Interdisciplinary Journal of Nonlinear Science, 17 (1), 015118. doi: https://doi.org/10.1063/1.2432059
  35. Mandelbrot, B. (2002). Fraktalnaya geometriya prirodyi. Moscow.
  36. Andronov, V., Pospelov, B., Rybka, E. (2017). Development of a method to improve the performance speed of maximal fire detectors. Eastern-European Journal of Enterprise Technologies, 2 (9 (86)), 32–37. doi: https://doi.org/10.15587/1729-4061.2017.96694
  37. Packard, N. H., Crutchfield, J. P., Farmer, J. D., Shaw, R. S. (1980). Geometry from a Time Series. Physical Review Letters, 45 (9), 712–716. doi: https://doi.org/10.1103/physrevlett.45.712

Downloads

Published

2018-11-16

How to Cite

Pospelov, B., Danchenko, Y., Dadashov, I. F., Skliarov, S., Gornostal, S., & Cherkashyn, O. (2018). Analysis of detection of ecological hazard based on computing the measures of current recurrence of ecosystem states. Eastern-European Journal of Enterprise Technologies, 6(10 (96), 6–13. https://doi.org/10.15587/1729-4061.2018.147508

Issue

Vol. 6 No. 10 (96) (2018): Ecology

Section

Ecology

License

Copyright (c) 2018 Boris Pospelov, Yuliya Danchenko, Ilgar Firdovsi Dadashov, Stanislav Skliarov, Stella Gornostal, Oleksandr Cherkashyn

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.