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Please use this identifier to cite or link to this item: http://dspace.bsu.edu.ru/handle/123456789/13772
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dc.contributor.authorLisetskii, F. N.-
dc.contributor.authorPichura, V. I.-
dc.contributor.authorPavlyuk, Y. V.-
dc.contributor.authorMarinina, O. A.-
dc.date.accessioned2015-12-29T12:03:32Z-
dc.date.available2015-12-29T12:03:32Z-
dc.date.issued2015-
dc.identifier.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.ru
dc.identifier.urihttp://dspace.bsu.edu.ru/handle/123456789/13772-
dc.description.abstractThe 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 basinru
dc.language.isoenru
dc.subjectearth Sciencesru
dc.subjecthydrologyru
dc.subjectneuron networksru
dc.subjectBox-Jenkins methodru
dc.subjectWinters methodru
dc.subjectriver runoffru
dc.subjectmodelingru
dc.subjectforecastingru
dc.titleComparative assessment of methods for forecasting river runoff with different conditions of organizationru
dc.typeArticleru
dc.identifier.citationpublicationResearch Journal of Pharmaceutical, Biological and Chemical Sciencesru
dc.identifier.citationnumber4ru
dc.identifier.citationvolume6ru
dc.identifier.citationfirstpage56ru
dc.identifier.citationendpage60ru
dc.description.refereedyesru
dc.description.institutionБелгородский государственный университетru
Appears in Collections:Статьи из периодических изданий и сборников (на иностранных языках) = Articles from periodicals and collections (in foreign languages)

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