Environmental Problems. – 2016. – Vol. 1, No. 2

Permanent URI for this collectionhttps://ena.lpnu.ua/handle/ntb/35890

Науковий журнал

Засновник і видавець Національний університет «Львівська політехніка». Виходить двічі на рік з 2016 року.

Environmental problems = Екологічні проблеми : [науковий журнал] / Lviv Polytechnic National University ; [editor-in-chief M. Malovanyy]. – Lviv : Publishing House of Lviv Polytechnic National University, 2016. – Volume 1, number 2. – 168 p. : il.

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    Analysis and forecast of the environmental radioactivity dynamics based on the methods of chaos theory: general conceptions
    (Publishing House of Lviv Polytechnic National University, 2016) Glushkov, Alexander; Safranov, Timur; Khetselius, Olga; Ignatenko, Anna; Buyadzhi, Vasily; Svinarenko, Andrey
    For the first time, we present a completely new technique of analysis, processing and forecasting of any time series of the environmental radioactivity dynamics, which schematically is as follows: a) general qualitative analysis of a dynamical problem, typical environmental radioactivity dynamics (including a qualitative analysis from the viewpoint of ordinary differential equations, the “Arnold-analysis”); b) checking for the presence of chaotic (stochastic) features and regimes (the Gottwald-Melbourne’s test; the correlation dimension method); c) reducing the phase space (the choice of time delay, the definition of the embedding space by the correlation dimension methods and false nearest neighbours algorithms); d) determination of the dynamic invariants of a chaotic system (computation of the global Lyapunov dimension la; determination of the Kaplan-Yorke dimension dL and average limits of predictability Prmax on the basis of the advanced algorithms; e) a nonlinear prediction (forecasting) of any dynamical system evolution. The last block really includes new (in the theory of environmental radioactivity dynamics and environmental protection) methods and algorithms of nonlinear prediction such as methods of predicted trajectories, stochastic propagators and neural networks modeling, renormanalysis with blocks of polynomial approximations, wavelet-expansions etc.