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dc.contributor.authorШебанін, В’ячеслав Сергійович-
dc.contributor.authorShebanin, Vyacheslav-
dc.contributor.authorKondratenko, Yuriy P.-
dc.contributor.authorАтаманюк, Ігор Петрович-
dc.contributor.authorAtamanyuk, Igor-
dc.date.accessioned2024-01-18T08:56:42Z-
dc.date.available2024-01-18T08:56:42Z-
dc.date.issued2018-
dc.identifier.citationShebanin, V.S., Kondratenko, Y.P., Atamanyuk, I.P. (2018). The Method of Optimal Nonlinear Extrapolation of Vector Random Sequences on the Basis of Polynomial Degree Canonical Expansion. In: Gil-Lafuente, A., Merigó, J., Dass, B., Verma, R. (eds) Applied Mathematics and Computational Intelligence. FIM 2015. Advances in Intelligent Systems and Computing, vol 730. Springer, Cham. https://doi.org/10.1007/978-3-319-75792-6_2uk_UA
dc.identifier.urihttps://dspace.mnau.edu.ua/jspui/handle/123456789/16837-
dc.descriptionПовний текст статті доступний з сайту видавця за посиланням: https://link.springer.com/chapter/10.1007/978-3-319-75792-6_2#citeasuk_UA
dc.description.abstractThe given work is dedicated to the solving of important scientific and technical problem of forming of the method of the optimal (in mean-square sense) extrapolation of the realizations of vector random sequences for the accidental quantity of the known values used for prognosis and for various order of nonlinear stochastic relations. Prognostic model is synthesized on the basis of polynomial degree canonical expansion of vector random sequence. The formula for the determination of the mean-square error of the extrapolation which allows us to estimate the accuracy of the solving of the prognostication problem with the help of the introduced method is obtained. The block diagrams of the algorithms of the determination of the parameters of the introduced method are also presented in the work. Taking into account the recurrent character of the processes of the estimation of the future values of the investigated sequence the method is quite simple in calculating respect. The introduced method of extrapolation as well as the vector canonical expansion assumed as its basis doesn’t put any essential limitations on the class of prognosticated random sequences (linearity, Markovian property, stationarity, scalarity, monotony etc.).uk_UA
dc.language.isoenuk_UA
dc.subjectExtrapolationuk_UA
dc.subjectOptimal nonlinearuk_UA
dc.subjectPolynomial canonical expansionuk_UA
dc.subjectVector random sequencesuk_UA
dc.subjectEstimationuk_UA
dc.subjectMean square erroruk_UA
dc.subjectPolynomialsuk_UA
dc.subjectStochastic systemsuk_UA
dc.subjectBlock diagramsuk_UA
dc.subjectMarkovianuk_UA
dc.subjectMean squareuk_UA
dc.subjectOptimal nonlinearuk_UA
dc.subjectPolynomial degreeuk_UA
dc.subjectPrognostic modeluk_UA
dc.subjectVectorsuk_UA
dc.titleThe method of optimal nonlinear extrapolation of vector random sequences on the basis of polynomial degree canonical expansionuk_UA
dc.typeArticleuk_UA
Розташовується у зібраннях:Публікації науково-педагогічних працівників МНАУ у БД Scopus
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