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Please use this identifier to cite or link to this item: http://dspace.bsu.edu.ru/handle/123456789/13772
Title: Comparative assessment of methods for forecasting river runoff with different conditions of organization
Authors: Lisetskii, F. N.
Pichura, V. I.
Pavlyuk, Y. V.
Marinina, O. A.
Keywords: earth Sciences
hydrology
neuron networks
Box-Jenkins method
Winters method
river runoff
modeling
forecasting
Issue Date: 2015
Citation:  Comparative assessment of methods for forecasting river runoff with different conditions of organization / F. N. Lisetskii et al. // Research Journal of Pharmaceutical, Biological and Chemical Sciences. - 2015. - Vol.6, N4.-Р. 56-60. - Refer.: p. 60.
Abstract: The article presents the results of comparative analysis of application of traditional statistical methods and non linear multilayer neural networks for processing multi year data of the river runoff with the aim of its forecasting. The obtained in the work optimal parameters for learning predictive neural networks are recommended ed for learning transformation and forecast of river runoff in the situation of permenant anthropogenic influence on basin
URI: http://dspace.bsu.edu.ru/handle/123456789/13772
Appears in Collections:Статьи из периодических изданий и сборников (на иностранных языках) = Articles from periodicals and collections (in foreign languages)

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