Forecasting chaotic processes in hydroecological systems on the basis of attractors conception and neural networks approach: Application

Authors: O.Yu.Khetselius

Year: 2014

Issue: 15

Pages: 16-21


It is proposed a new approach to non-linear modeling and forecasting chaotic processes in hydroecological systems, which is based on the conception of compact geometrical attractor and neural networks (artificial intellect) algorithms. As an illustrative example of using the method, the dynamics of the nitrates concentrations in the Small Carpathians river’s watersheds in the Earthen Slovakia during 1969-1996 years is predicted.

Tags: attractor conception; chaotic processes; forecasting; hydroecological systems; neural networks algorithm


  1. Hastings A.M., Hom С., Ellner S, Turchin P., Godfray Y. Chaos in ecology: is Mother Nature a strange attractor? // Ann. Rev. Ecol. Syst.-1993.-Vol.24.-P.1-33.
  2. Abarbanel H.D.I., Brown R., Sidorowich J.J., Tsimring L.Sh. The analysis of observed chaotic data in physical systems // Rev. Mod. Phys.-1993.-Vol.65.- P.1331-1392.
  3. Schreiber T. Interdisciplinary application of nonlinear time series methods// Phys. Rep. -1999.-Vol..08(1).-P.1-64.
  4. May R.M. Necessity and chance: determinisctic chaos in ecology and evolution// Bull. Amer. Math. Soc.-1995.-Vol.32.-P.291-308.
  5. Kennel M., Brown R., Abarbanel H. Determining embedding dimension for phase-space reconstruction using a geometrical construction// Phys. Rev.A.-1992.-Vol.45.-P.3403-3411.
  6. Turcotte D.L. Fractals and chaos in geology and geophysics. – Cambridge: Cambridge University Press.-1997.
  7. Mañé R. On the dimensions of the compact invariant sets of certain non-linear maps// Lecture Notes in Mathematics (Berlin, Springer).-1981.-Vol.898.-P.230-242.
  8. Grassberger P., Procaccia I. Measuring the strangeness of strange attractors// Physica D. – 1983. – Vol. 9. – P. 189-208.
  9. Bunyakova Yu.Ya., Glushkov A.V., Analysis and forecast of the impact of anthropogenic factors on air basein of an industrial city.-Odessa: Ecology, 2010.-256p.
  10. Glushkov A.V., Khokhlov V.N., Prepelitsa G.P., Tsenenko I.A. Temporal variability of the atmosphere ozone content: Effect of North-Atlantic oscillation// Optics of atmosphere and ocean.-2004.-Vol.14,N7.-P. 219-223
  11. Glushkov A.V., Svinarenko A.A., Loboda A.V. Theory of neural networks on basis of photon echo and its program realization.- Odessa, TEC, 2004.-280P.
  12. Glushkov A.V.,Loboda N.S.,Khokhlov V.N.Using meteorological data for reconstruction of annual runoff series over ungauged area: Empirical orthogonal functions approach to Moldova- Southwest Ukraine region//Atmospheric Research (Elsevier).-2005.-Vol.77.-P.100-113.
  13. Glushkov A.V., Loboda N.S., Khokhlov V.N., Lovett L. Using non-decimated wavelet decomposition to analyse time variations of North Atlantic Oscillation, eddy kinetic energy, and Ukrainian precipitation // Journal of Hydrology (Elsevier).-2006.-Vol. 322. N1-4.-P.14-24.
  14. Khokhlov V.N., Glushkov A.V., Loboda N.S., Bunyakova Yu.Ya. Short-range forecast of atmospheric pollutants using non-linear prediction method// Atmospheric Environment (Elsevier).-2008.-Vol.42.-P. 7284–7292.
  15. Glushkov A.V., Khetselius O.Yu., Brusentseva S.V., Zaichko P.A., Ternovsky V.B. Adv. in Neural Networks, Fuzzy Systems and Artificial Intelligence, Series: Recent Adv. in Com-puter Engineering, ed. by J.Balicki (WSEAS, Gdansk).-2014.-Vol.21.- P.69-75.
  16. Glushkov A.V., Svinarenko A.A., Buyadzhi V.V., Zaichko P.A., Ternovsky V.B. Neural Networks, Fuzzy Systems and Artificial Intelligence, Series: Recent Adv. in Computer Engineering, ed. by J.Balicki (WSEAS, Gdansk).-2014.-Vol.21.- P.143-150.
  17. Glushkov A.V., Khetselius O.Yu., Bunyakova Yu.Ya., Grushevsky O.N., Solyanikova E.P. Studying and forecasting the atmospheric and hydroecological systems dynamics by using chaos theory methods// Dynamical Systems Theory Eds. J. Awrejcewicz, M. Kazmierczak, P. Olejnik, J, Mrozowski (Lodz, Polland).-2013.-Vol.T1.-P.249-258.
  18. Khetselius O.Yu. Forecasting evolutionary dynamics of chaotic systems using advanced non-linear prediction method// Dynamical Systems Applications, Eds. J. Awrejcewicz, M. Kazmierczak, P. Olejnik, J, Mrozowski (Lodz, Polland).-2013.-Vol.T2.-P.145-152
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