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

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

Boris Pospelov, Yuliya Danchenko, Ilgar Firdovsi Dadashov, Stanislav Skliarov, Stella Gornostal, Oleksandr Cherkashyn

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 small-size 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.


Keywords


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

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References


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Vasyukov, A., Loboichenko, V., Bushtec, S. (2016). Identification of bottled natural waters by using direct conductometry Ecology. Environment and Conservation, 22 (3), 1171–1176.

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.

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.

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

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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

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Kantz, H., Schreiber, T. (2003). Nonlinear time series analysis. Cambridge University Press. doi: https://doi.org/10.1017/cbo9780511755798

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

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.

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

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

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Bendat, J. S., Piersol, A. G. (2010). Random data: analysis and measurement procedures. John Wiley & Sons. doi: https://doi.org/10.1002/9781118032428

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

Singh, P. (2016). Time-frequency analysis via the fourier representation. HAL, 1–7. Available at: https://hal.archives-ouvertes.fr/hal-01303330

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

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

Stankovic, L., Dakovic, M., Thayaparan, T. (2014). Time-frequency signal analysis. Kindle edition, Amazon, 655.

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

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

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

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

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

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

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

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

Mandelbrot, B. (2002). Fraktalnaya geometriya prirodyi. Moscow.

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

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


GOST Style Citations


Vasiliev M. I., Movchan I. O., Koval O. M. Diminishing of ecological risk via optimization of fire-extinguishing system projects in timber-yards // Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2014. Issue 5. P. 106–113.

Vasyukov A., Loboichenko V., Bushtec S. Identification of bottled natural waters by using direct conductometry Ecology // Environment and Conservation. 2016. Vol. 22, Issue 3. P. 1171–1176.

The usage of high speed impulse liquid jets for putting out gas blowouts / Semko A. N., Beskrovnaya M. V., Vinogradov S. A., Hritsina I. N., Yagudina N. I. // Journal of Theoretical and Applied Mechanics. 2014. Vol. 52, Issue 3. P. 655–664.

Mathematical model of the efficiency of diesel particulate matter filter / Kondratenko O. M., Vambol S. O., Strokov O. P., Avramenko A. M. // Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2015. Issue 6. P. 55–61.

Loboichenko V. M., Vasyukov A. E., Tishakova T. S. Investigations of Mineralization of Water Bodies on the Example of River Waters of Ukraine // Asian Journal of Water, Environment and Pollution. 2017. Vol. 14, Issue 4. P. 37–41. doi: https://doi.org/10.3233/ajw-170035 

Ol’shanskii V. P. 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. 2004. Vol. 77, Issue 1. P. 242–246. doi: https://doi.org/10.1023/b:joep.0000020747.49072.8b 

Pascual M., Ellner S. P. Linking Ecological Patterns to Environmental Forcing via Nonlinear Time Series Models // Ecology. 2000. Vol. 81, Issue 10. P. 2767. doi: https://doi.org/10.2307/177340 

Parrott L. Analysis of simulated long-term ecosystem dynamics using visual recurrence analysis // Ecological Complexity. 2004. Vol. 1, Issue 2. P. 111–125. doi: https://doi.org/10.1016/j.ecocom.2004.01.002 

Proulx R. Ecological complexity for unifying ecological theory across scales: A field ecologist's perspective // Ecological Complexity. 2007. Vol. 4, Issue 3. P. 85–92. doi: https://doi.org/10.1016/j.ecocom.2007.03.003 

Kantz H., Schreiber T. Nonlinear time series analysis. Cambridge University Press, 2003. doi: https://doi.org/10.1017/cbo9780511755798 

Eckmann J.-P., Kamphorst S. O., Ruelle D. Recurrence Plots of Dynamical Systems // Europhysics Letters (EPL). 1987. Vol. 4, Issue 9. P. 973–977. doi: https://doi.org/10.1209/0295-5075/4/9/004 

Webber Jr. C. L., Zbilut J. P. Recurrence quantification analysis of nonlinear dynamical systems. Tutorials in contemporary nonlinear methods for the behavioral sciences. 2005. P. 26.

Studying the recurrent diagrams of carbon monoxide concentration at early ignitions in premises / Pospelov B., Andronov V., Rybka E., Meleshchenko R., Borodych P. // Eastern-European Journal of Enterprise Technologies. 2018. Vol. 3, Issue 3 (93). P. 34–40. doi: https://doi.org/10.15587/1729-4061.2018.133127 

Poulsen A., Jomaas G. Experimental Study on the Burning Behavior of Pool Fires in Rooms with Different Wall Linings // Fire Technology. 2011. Vol. 48, Issue 2. P. 419–439. doi: https://doi.org/10.1007/s10694-011-0230-0 

Analysis of correlation dimensionality of the state of a gas medium at early ignition of materials / Pospelov B., Andronov V., Rybka E., Meleshchenko R., Gornostal S. // Eastern-European Journal of Enterprise Technologies. 2018. Vol. 5, Issue 10 (95). P. 25–30. doi: https://doi.org/10.15587/1729-4061.2018.142995

Zhang D., Xue W. Effect of heat radiation on combustion heat release rate of larch // Journal of West China Forestry Science. 2010. Issue 39. P. 148.

Andronov V., Pospelov B., Rybka E. Development of a method to improve the performance speed of maximal fire detectors // Eastern-European Journal of Enterprise Technologies. 2017. Vol. 2, Issue 9. P. 32–37. doi: https://doi.org/10.15587/1729-4061.2017.96694 

Design of fire detectors capable of self-adjusting by ignition / Pospelov B., Andronov V., Rybka E., Skliarov S. // Eastern-European Journal of Enterprise Technologies. 2017. Vol. 4, Issue 9 (88). P. 53–59. doi: https://doi.org/10.15587/1729-4061.2017.108448 

Research into dynamics of setting the threshold and a probability of ignition detection by self­adjusting fire detectors / Pospelov B., Andronov V., Rybka E., Skliarov S. // Eastern-European Journal of Enterprise Technologies. 2017. Vol. 5, Issue 9 (89). P. 43–48. doi: https://doi.org/10.15587/1729-4061.2017.110092 

Results of experimental research into correlations between hazardous factors of ignition of materials in premises / Pospelov B., Rybka E., Meleshchenko R., Gornostal S., Shcherbak S. // Eastern-European Journal of Enterprise Technologies. 2017. Vol. 6, Issue 10 (90). P. 50–56. doi: https://doi.org/10.15587/1729-4061.2017.117789 

Bendat J. S., Piersol A. G. Random data: analysis and measurement procedures. John Wiley & Sons, 2010. doi: https://doi.org/10.1002/9781118032428 

Techniques to Obtain Good Resolution and Concentrated Time-Frequency Distributions: A Review / Shafi I., Ahmad J., Shah S. I., Kashif F. M. // EURASIP Journal on Advances in Signal Processing. 2009. Vol. 2009, Issue 1. doi: https://doi.org/10.1155/2009/673539 

Singh P. Time-frequency analysis via the fourier representation // HAL. 2016. P. 1–7. URL: https://hal.archives-ouvertes.fr/hal-01303330

Experimental study of the fluctuations of gas medium parameters as early signs of fire / Pospelov B., Andronov V., Rybka E., Popov V., Romin A. // Eastern-European Journal of Enterprise Technologies. 2018. Vol. 1, Issue 10 (91). P. 50–55. doi: https://doi.org/10.15587/1729-4061.2018.122419 

Pretrel H., Querre P., Forestier M. Experimental Study of Burning Rate Behaviour in Confined and Ventilated Fire Compartments // Fire Safety Science. 2005. Vol. 8. P. 1217–1228. doi: https://doi.org/10.3801/iafss.fss.8-1217 

Stankovic L., Dakovic M., Thayaparan T. Time-frequency signal analysis. Kindle edition, Amazon, 2014. 655 p.

Avargel Y., Cohen I. Modeling and Identification of Nonlinear Systems in the Short-Time Fourier Transform Domain // IEEE Transactions on Signal Processing. 2010. Vol. 58, Issue 1. P. 291–304. doi: https://doi.org/10.1109/tsp.2009.2028978 

Giv H. H. Directional short-time Fourier transform // Journal of Mathematical Analysis and Applications. 2013. Vol. 399, Issue 1. P. 100–107. doi: https://doi.org/10.1016/j.jmaa.2012.09.053 

Development of the method of frequency­temporal representation of fluctuations of gaseous medium parameters at fire / Pospelov B., Andronov V., Rybka E., Popov V., Semkiv O. // Eastern-European Journal of Enterprise Technologies. 2018. Vol. 2, Issue 10 (92). P. 44–49. doi: https://doi.org/10.15587/1729-4061.2018.125926 

Grassberger P., Procaccia I. Measuring the strangeness of strange attractors // Physica D: Nonlinear Phenomena. 1983. Vol. 9, Issue 1-2. P. 189–208. doi: https://doi.org/10.1016/0167-2789(83)90298-1 

Determining Lyapunov exponents from a time series / Wolf A., Swift J. B., Swinney H. L., Vastano J. A. // Physica D: Nonlinear Phenomena. 1985. Vol. 16, Issue 3. P. 285–317. doi: https://doi.org/10.1016/0167-2789(85)90011-9 

Marwan N., Kurths J., Saparin P. Generalised recurrence plot analysis for spatial data // Physics Letters A. 2007. Vol. 360, Issue 4-5. P. 545–551. doi: https://doi.org/10.1016/j.physleta.2006.08.058 

Fractal dimension estimations of drainage network in the Carpathian–Pannonian system / Dombrádi E., Timár G., Bada G., Cloetingh S., Horváth F. // Global and Planetary Change. 2007. Vol. 58, Issue 1-4. P. 197–213. doi: https://doi.org/10.1016/j.gloplacha.2007.02.011 

Cardiac magnetic field map topology quantified by Kullback-Leibler entropy identifies patients with hypertrophic cardiomyopathy / Schirdewan A., Gapelyuk A., Fischer R., Koch L., Schütt H., Zacharzowsky U. et. al. // Chaos: An Interdisciplinary Journal of Nonlinear Science. 2007. Vol. 17, Issue 1. P. 015118. doi: https://doi.org/10.1063/1.2432059 

Mandelbrot B. Fraktalnaya geometriya prirodyi. Moscow, 2002.

Andronov V., Pospelov B., Rybka E. Development of a method to improve the performance speed of maximal fire detectors // Eastern-European Journal of Enterprise Technologies. 2017. Vol. 2, Issue 9 (86). P. 32–37. doi: https://doi.org/10.15587/1729-4061.2017.96694 

Geometry from a Time Series / Packard N. H., Crutchfield J. P., Farmer J. D., Shaw R. S. // Physical Review Letters. 1980. Vol. 45, Issue 9. P. 712–716. doi: https://doi.org/10.1103/physrevlett.45.712 







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

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ISSN (print) 1729-3774, ISSN (on-line) 1729-4061