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dc.contributor.authorBogomolova, A.en
dc.contributor.authorBalk, I.en
dc.contributor.authorIvachenko, N.en
dc.contributor.authorTerlyga, A.en
dc.date.accessioned2019-07-22T06:46:29Z-
dc.date.available2019-07-22T06:46:29Z-
dc.date.issued2018-
dc.identifier.citationBudget optimization modelling for sustainable development of the university research: The example of Russia / A. Bogomolova, I. Balk, N. Ivachenko et al. // Journal of Physics: Conference Series. — 2018. — Vol. 1117. — Iss. 1. — 12012.en
dc.identifier.issn1742-6588-
dc.identifier.otherhttps://iopscience.iop.org/article/10.1088/1742-6596/1117/1/012012/pdfpdf
dc.identifier.other1good_DOI
dc.identifier.other2ca24d5a-6f68-479d-bb6a-d0faa616817cpure_uuid
dc.identifier.otherhttp://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85058334572m
dc.identifier.urihttp://elar.urfu.ru/handle/10995/75487-
dc.description.abstractRussian universities have undergone many changes in recent years, including increased attention to innovative development and transformation of the main function of universities. In addition to education function, universities now should cooperate with the market and create the infrastructure for the successful development of R&D. One of the main resources for this is financing, but it is often in deficiency. Moreover, sudden economic shocks add instability to the situation. This problem is acute for research projects which often last for several years and react sharply to sudden changes in the key resources. This article proposes an optimization model for the management of universities' own funds to ensure sustainable and predictable R&D funding. The model uses mathematical and machine learning methods. The model is applied to statistical data from Russian universities, as well as to one particular Russian university. © Published under licence by IOP Publishing Ltd.en
dc.description.sponsorshipThe main parameter of our interest is Ri– total R&D Funding, which consists of Ci – R&D funding from external sources (industry, federal and others) and Ui – university own funds including Ui*– resources used in current periods and U’i– deferred resources for future periods. The latter forms a state variable Ii – investments. So, deferred resources can grow at β – return on investments rate: Ii+1 = Ii*(1+β) + U’i.en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherInstitute of Physics Publishingen
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.sourceJournal of Physics: Conference Seriesen
dc.subjectBUDGET CONTROLen
dc.subjectLEARNING SYSTEMSen
dc.subjectOPTIMIZATIONen
dc.subjectKEY RESOURCESen
dc.subjectMACHINE LEARNING METHODSen
dc.subjectMODEL USEen
dc.subjectOPTIMIZATION MODELINGen
dc.subjectOPTIMIZATION MODELLINGen
dc.subjectSTATISTICAL DATASen
dc.subjectSUDDEN CHANGEen
dc.subjectUNIVERSITY RESEARCHen
dc.subjectBIG DATAen
dc.titleBudget optimization modelling for sustainable development of the university research: The example of Russiaen
dc.typeConference Paperen
dc.typeinfo:eu-repo/semantics/conferenceObjecten
dc.typeinfo:eu-repo/semantics/publishedVersionen
dc.conference.name2018 3rd Big Data Conference, BDC 2018en
dc.conference.date14 September 2018-
dc.identifier.rsi38640536-
dc.identifier.doi10.1088/1742-6596/1117/1/012012-
dc.identifier.scopus85058334572-
local.affiliationLomonosov Moscow State University, GSP-1, Leninskie Gory, Moscow, 119991, Russian Federationen
local.affiliationGlobal Innovation Labs LLC, 258 Harvard Str #352, Brookline, MA 02446, United Statesen
local.affiliationUral Federal University after the First President of Russia B.N. Eltsin, 61 Komsomolskaya st., Ekaterinburg, Russian Federationen
local.contributor.employeeТерлыга Александра Федоровнаru
local.issue1-
local.volume1117-
dc.identifier.wos000495570900012-
local.identifier.pure8415094-
local.description.order12012-
local.identifier.eid2-s2.0-85058334572-
local.identifier.wosWOS:000495570900012-
Располагается в коллекциях:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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