Received 22.12.2021
Revised 04.05.2022
Accepted 14.06.2022
Retrieved from Iss. 111, 2022
Pages 126 -132
Abstract
It is offered forecast the natural time series (hydrological time series) by methods the deterministic chaotic dynamic. At analysis of the time series reveal the hidden regularities at raw data’s. Hereinafter revealled regularities use for realization of the forecast of input data. Hydrological time series either as chaotical time series possible forecast only at determined number step onward. For hydrological time series exists the limit of forecasting (forecasting horizon). The identical prediction possible unless come behind of the forecasting horizon. The aim of the work there is design of the procedure the investigations of the natural time series on possibility of the forecasting. As raw data’s were used the mean day data of consuption for the large flat river of the Ukraine (length is 4*365 points). For forecasting of the natural time series it was used designed an autors modification of the method of Local Approximation. The forecasting horizon of time series was defined by means of factor the linear correlation (on how much points onward (maximum) possible forecast the time series for conservation of the factor the correlation within the range of 0.7 … 1.0). The explored dependency of the forecasting horizon from parameter DIM (Dimensionality Reconstrusted the phase space). The results of the research say for essential determinism of time series (hydrological) – the time series is forecasted on 15 … 22 points onward. Software was designed for investigations of the natural time series (hydrological and hydrochemistry) for forecasting (to find forecasting horizon). The called on investigation has shown that the method of Local Approximation more efficient than classical methods the forecast (for classical methods the adequate forecast possible only on 1 … 2 points onward).
Keywords:
hydrological time series, forecasting water consuption, method Local Approximation forecast horizonLukashin Y.P. Adaptivnyye metody kratkosrochnogo prognozirovaniya vremennykh ryadov: ucheb. posobiye. M.: Finansy i statistika, 2003. 416 s.
Jayawardena A.W., Lai F. Chaos in hydrological time series. Extreme Hydrological Events: Precipitation, Floods and Droughis. Proceedings of the Yokohama Symposium, July 1993. IAHS, Publ. №213. 1993. P. 59-66.
Koutsoyiannis D. On the guest for chaotic attractors in hydrological processes. Hydrological Sciences, 51(6). Dec. 2006. P. 1065-1091.
Sivakumar B., Berndtsson R., Olsson J., Jinno K., Kawamura A. Dynamics of monthly rainfall-runoff process at the Gota basin: A search for chaos. Hydrology and Earth System Sciences, 4(3). 2000. P. 407-417.
Jayawardena A.W., Li W.K., Xu P. Neighbourhood selection for local modelling and prediction of hydrological time series. Journal of Hydrology, 258. 2002. P. 40-57.
Khan S., Ganguly A.R., Saigal S. Detection and predictive modeling of chaos in finite hydrological time series. Nonlinear Processes in Geophysics, 12. 2005. P. 41-53.
Malinetskiy G.G., Potapov A.B. Sovremennyye problemy nelineynoy dinamiki. M.: Editorial URSS, 2000. 336 s.
Jayawardena A.W. Runoff forecasting using a local approximation method. Destructive Water: Water-Caused Natural Disasters, their Abatement and Control. Proceedings of the Conference held at Anaheim, California, June 1996. IAHS, Publ. №239. 1997. P. 167-171.
Yushkina O.A. Analiz i prognoz vremennoy izmenchivosti rechnogo stoka metodami nelineynoy dinamiki: avtoref. diss. … kand. geograf. nauk. Irkutsk, 2009. 20 s.
Artemenko V.A., Petrovych V.V. Prohnozuvannya nerehulyarnykh chasovykh ryadiv metodom lokalnoyi aproksymatsiyi. Avtomobilni dorohy i dorozhnye budivnytstvo. Kyiv, 2012. Vyp. 86. S. 176-195.
Artemenko V.A., Petrovych V.V. Neparametrychnyy pokaznyk variabelʹnosti hydroekolohichnykh chasovykh ryadiv. Avtomobilni dorohy i dorozhnye budivnytstvo. Kyiv, 2021. Vyp. 109. S. 103-108.
Artemenko V.A., Petrovych V.V. Povysheniye kachestva prognozirovaniya hydrologicheskikh vremennykh ryadov. Avtomobilni dorohy i dorozhnye budivnytstvo. Kyiv, 2014. Vyp. 92. S. 114-127.