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Entrepreneurship and Sustainability Issues Open access
Journal Impact FactorTM (2023) 1.2 Q4
Journal Citation IndicatorTM (2023) 0.33 Q3
Received: 2020-03-18  |  Accepted: 2020-09-01  |  Published: 2020-12-30

Title

Artificial intelligence components and fuzzy regulators in entrepreneurship development


Abstract

The article provides a comparative study of the possibility of entrepreneurship development based on fuzzy signals of business activity and applied elements of artificial intelligence. The principal research methods that determine the logic and practical basis of the application of fuzzy logic in entrepreneurship are highlighted. It has been determined that fuzzy modeling is effective when technological processes are too complex for analysis using generally accepted quantitative methods, or when available sources of information in the business environment are interpreted poorly, inaccurately, and indefinitely. It has been shown experimentally that fuzzy logic gives better results compared to those obtained with generally accepted algorithms for analyzing the quality of doing business. A model of a neuro-fuzzy regulator has been developed and measures for its implementation in the business environment have been proposed. A neural network model in entrepreneurial development has been formed. Studies have shown the possibility of effective use of the principles of artificial intelligence and modeling in solving problems of developing entrepreneurial potential and making business decisions under conditions of uncertainty. This ensures objective and well-grounded decision-making in solving various applied problems of business development and taking into account environmental factors. The applied tasks of supporting the adoption of entrepreneurial decisions in the conditions are formulated; uncertainty; indicating that approaches to decision-making under conditions of uncertainty based on artificial intelligence and fuzzy logic tools are universal and require appropriate careful study and adaptation to a specific applied problem in the business environment.


Keywords

entrepreneurship, neural network, regulators, linguistic rule, genetic algorithm, object of control


JEL classifications

M21 , O16


URI

http://jssidoi.org/jesi/article/711


DOI


Pages

487-499


Funding

This research was supported by the project, which has received funding from the Grant No. 1/0544/19 Formation of the methodological platform to measure and assess the effectiveness and financial status of non-profit organizations in the Slovak Republic

This is an open access issue and all published articles are licensed under a
Creative Commons Attribution 4.0 International License

Authors

Bogachov, Sergii
PO "Institute for Local and Regional Development", Kiev, Ukraine
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Kwilinski, Aleksy
London Academy of Science and Business, London, United Kingdom https://www.london-asb.co.uk
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Miethlich, Boris
Comenius University in Bratislava, Bratislava, Slovakia https://uniba.sk
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Bartosova, Viera
University of Žilina, Žilina, Slovakia https://www.uniza.sk
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Gurnak, Aleksandr
Financial University under the Government of the Russian Federation, Moscow, Russian Federation http://www.fa.ru
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Journal title

Entrepreneurship and Sustainability Issues

Volume

8


Number

2


Issue date

December 2020


Issue DOI


ISSN

ISSN 2345-0282 (online)


Publisher

VšĮ Entrepreneurship and Sustainability Center, Vilnius, Lithuania

Cited

Google Scholar

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References