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
Materias:	artificial intellect business processes instrumental approach regressive model method of support vectors machine-aided training Economics as a science HB71-74
Acceso en línea:	https://doaj.org/article/7546c1c1118a4319b8922595bea86d19
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id	oai: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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Methods of Machine-Aided Training in Small Business: Content and Management

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