Methods of Machine-Aided Training in Small Business: Content and Management

The article provides key characteristics of standard methods of machine-aided training used by companies in operative business processes. Within the frames of home orientation to the innovation business development, digital economy and infrastructure for data storage the human factor becomes essenti...

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Autores principales: S. A. Tishchenko, M. A. Shakhmuradian
Formato: article
Lenguaje:RU
Publicado: Plekhanov Russian University of Economics 2019
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Acceso en línea:https://doaj.org/article/7546c1c1118a4319b8922595bea86d19
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spelling oai:doaj.org-article:7546c1c1118a4319b8922595bea86d192021-11-15T05:20:49ZMethods of Machine-Aided Training in Small Business: Content and Management2413-28292587-925110.21686/2413-2829-2019-6-83-95https://doaj.org/article/7546c1c1118a4319b8922595bea86d192019-12-01T00:00:00Zhttps://vest.rea.ru/jour/article/view/791https://doaj.org/toc/2413-2829https://doaj.org/toc/2587-9251The article provides key characteristics of standard methods of machine-aided training used by companies in operative business processes. Within the frames of home orientation to the innovation business development, digital economy and infrastructure for data storage the human factor becomes essential. The use of methods of artificial intellect by employees of small enterprises faces obstacles that imply personnel ignorance concerning strategic functionality of available today algorithms of business processes. Small commercial enterprises encounter the problem that they do not know the key instrumental principles of functioning and use of machine-aided training algorithms. At the same time business processes of the enterprise could be seriously improved through implementing algorithms of machine-aided training. The authors conducted a formal and analytical review of potential means for small business optimization. They described types of algorithms and models of machine-aided training, such as multiple regressive model, logistic regression, etc., as well as instrumental problems of their use by enterprise analysts and developers. Recommendations were prepared aimed at use of these models in order to raise the efficiency of small commercial enterprises.S. A. TishchenkoM. A. ShakhmuradianPlekhanov Russian University of Economicsarticleartificial intellectbusiness processesinstrumental approachregressive modelmethod of support vectorsmachine-aided trainingEconomics as a scienceHB71-74RUВестник Российского экономического университета имени Г. В. Плеханова, Vol 0, Iss 6, Pp 83-95 (2019)
institution DOAJ
collection DOAJ
language RU
topic artificial intellect
business processes
instrumental approach
regressive model
method of support vectors
machine-aided training
Economics as a science
HB71-74
spellingShingle artificial intellect
business processes
instrumental approach
regressive model
method of support vectors
machine-aided training
Economics as a science
HB71-74
S. A. Tishchenko
M. A. Shakhmuradian
Methods of Machine-Aided Training in Small Business: Content and Management
description The article provides key characteristics of standard methods of machine-aided training used by companies in operative business processes. Within the frames of home orientation to the innovation business development, digital economy and infrastructure for data storage the human factor becomes essential. The use of methods of artificial intellect by employees of small enterprises faces obstacles that imply personnel ignorance concerning strategic functionality of available today algorithms of business processes. Small commercial enterprises encounter the problem that they do not know the key instrumental principles of functioning and use of machine-aided training algorithms. At the same time business processes of the enterprise could be seriously improved through implementing algorithms of machine-aided training. The authors conducted a formal and analytical review of potential means for small business optimization. They described types of algorithms and models of machine-aided training, such as multiple regressive model, logistic regression, etc., as well as instrumental problems of their use by enterprise analysts and developers. Recommendations were prepared aimed at use of these models in order to raise the efficiency of small commercial enterprises.
format article
author S. A. Tishchenko
M. A. Shakhmuradian
author_facet S. A. Tishchenko
M. A. Shakhmuradian
author_sort S. A. Tishchenko
title Methods of Machine-Aided Training in Small Business: Content and Management
title_short Methods of Machine-Aided Training in Small Business: Content and Management
title_full Methods of Machine-Aided Training in Small Business: Content and Management
title_fullStr Methods of Machine-Aided Training in Small Business: Content and Management
title_full_unstemmed Methods of Machine-Aided Training in Small Business: Content and Management
title_sort methods of machine-aided training in small business: content and management
publisher Plekhanov Russian University of Economics
publishDate 2019
url https://doaj.org/article/7546c1c1118a4319b8922595bea86d19
work_keys_str_mv AT satishchenko methodsofmachineaidedtraininginsmallbusinesscontentandmanagement
AT mashakhmuradian methodsofmachineaidedtraininginsmallbusinesscontentandmanagement
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