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id: 27733
Title: Diagnostics of the State of Safety-Oriented Enterprise Management System Using Neural Networks
Authors: Havlovska N., Koptieva H., Babchynska O., Rudnichenko Y., Lopatovskyi V., Prytys V.
Keywords: managerial decision, economic security, risk, benefit, neural network
Date of publication: 2022-08-03 12:38:37
Last changes: 2022-08-03 12:38:37
Year of publication: 2022
Summary: Enterprise management is based on the need to make and justify management decisions that contribute to its development. It is almost impossible to determine the risk of a particular managerial decision, and excessive risk in the implementation of individual projects can lead to loss of business. Therefore, management faces the need to find a balance between benefits and risks, at which, on the one hand, it will be possible to develop a company and, on the other hand, adhere to postulates of safetyoriented management. Since management decisions cannot be foreseen for all possible situations and combinations of risk-benefit ratios, a universal model is proposed. It implies a golden ratio, depending on the limited number of current conditions, that would satisfy an enterprise management the standpoint of sufficient justification on a decision. The article proposes a probabilistic neural network architecture and Matlab parameters of a probabilistic neural network for diagnosing the states of a safety-oriented control system. The proposed model in the form of a probabilistic neural network generates a response to input data on previous month under estimation, and forms an optimal state for a next month.
Publication type: Стаття Scopus
Publication: TEM Journal. 2022. Vol. 11. Iss. 1. P. 13-23
In the collections: Статті/ Видання інших установ/
Published by: Адміністратор
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