Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Igor B. Kolmakov"'
Autor:
Valeriy I. Antipov, Igor B. Kolmakov
Publikováno v:
Вестник Российского экономического университета имени Г. В. Плеханова, Vol 0, Iss 2, Pp 130-139 (2017)
Russian economy is in a deep crisis now caused by reduction in aggregate demand, which depends on many reasons, the main is plunging customer demand provoked by high inflation rate. Due to this academics and industrialists propose different steps aim
Externí odkaz:
https://doaj.org/article/eb04a2f7be87447aa03f08d3a4e994e0
Publikováno v:
Вестник Российского экономического университета имени Г. В. Плеханова, Vol 0, Iss 5, Pp 160-172 (2017)
On the basis of authors' programs and methodological approaches the automated system of calculating short-term forecast of the parameters in the field of research and innovation was developed. The article for the first time raised and solved the task
Externí odkaz:
https://doaj.org/article/071b7cfcc6f0493f98e90fe6e5f29b42
Autor:
Olga V. Kitova, Igor B. Kolmakov, Matvey V. Domozhakov, Yaroslava V. Krivosheeva, Il'ya A. Pen'kov
Publikováno v:
Вестник Российского экономического университета имени Г. В. Плеханова, Vol 0, Iss 2, Pp 147-161 (2017)
The article deals with general methodology and architecture of the system of hybrid models for forecasting economic indices, its putting into effect in the form of integrated information system illustrated by rates in the field of research and innova
Externí odkaz:
https://doaj.org/article/1f8964403e42400097d1e7966de2af6b
Publikováno v:
Вестник Российского экономического университета имени Г. В. Плеханова, Vol 0, Iss 6, Pp 86-95 (2017)
The article shows specific features of short-term forecast models, which were realized on the basis of the solution trees method applied to regression task. The authors provide the description of key characteristics of the trees solution method using
Externí odkaz:
https://doaj.org/article/ed8077c7ca8e4be790a9abfb5e3fa2b0
Publikováno v:
Статистика и экономика, Vol 0, Iss 4, Pp 27-30 (2016)
Possibilities of applying intelligent machine learning technique based on support vectors for predicting investment measures are considered in the article. The base features of support vector method over traditional econometric techniques for improvi
Externí odkaz:
https://doaj.org/article/a0a43334d788432ba171a195fe8da4a4