Нейро-нечіткі технології моделювання в економіці

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Browsing Нейро-нечіткі технології моделювання в економіці by Author "Turlakova, Svitlana"

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    Artificial intelligence tools for managing the behavior of economic agents at micro level
    (Київський національний економічний університет імені Вадима Гетьмана, 2023) Turlakova, Svitlana; Lohvinenko,Bohdan
    In modern business conditions, effective management of employee behavior is becoming a critical factor in ensuring competitive advantages and development of enterprises. AI tools, which are rapidly developing, provide new opportunities for managing the behavior of economic agents at the micro level and increasing the productivity of companies. To make the most effective use of AI in the outlined processes, there is a need to conduct research into the areas and possibilities of their application and impact on enterprise personnel. The methodology and mathematical model developed in the article, based on the use of theories of fuzzy sets, neural networks and Lefebvre reflexive control, allow to study the potential and prospects for using AI tools (on an example of SAP SuccessFactors) in managing the behavior of economic agents at the micro level, in particular in predicting the efficiency of employees at enterprise. It was concluded that the SAP SuccessFactors can evaluate the effectiveness of various personnel groups differently. This may occur due to insufficient adaptation of the models to the specifics of work and personal characteristics of employees of different productivity levels. Therefore, when using AI tools in the management of personnel behavior, it is important to consider such features and make individual settings for different groups of employee performance. This is a key aspect to avoid wrong management decisions that can affect the economic efficiency of the enterprise.
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    Modeling the values of reflexive characteristics of agents within the management of herd behavior at the enterprises
    (Київський національний економічний університет імені Вадима Гетьмана, 2022) Turlakova, Svitlana
    The central place at the formation of agent behavior at enterprises is the study of decision-making procedures and factors that mediate their choice. To determine the values of the reflexive characteristics of agents in the framework of management of herd behavior at enterprises a new approach is proposed based on questionnaire methods, the apparatus of the theory of fuzzy sets and neural network modeling. The determination of the values of reflexive characteristics of agents is carried out by the formation of fuzzy sets in the framework of the theory of L. Zadeh based on the results of a questionnaire of agents in selected areas. The agents are distributed by the Kohonen map into groups in order to numerically determine the values of their reflexive characteristics based on formed fuzzy sets. An important applied value in interpreting the results of the Kohonen SOM clustering is the ability to obtain representatives of specific clusters and average values of their characteristics, which are determined by the parameters of the network neurons and represent cluster centers. As a result of the clustering of input data vectors by directions of determining the values of the reflexive characteristics of agents, typical values of the required parameters are obtained for agents-representatives of clusters. The values of the reflexive characteristics of agents can be used to evaluate the results of decision-making by agents using the functions of reflexive choice to ensure effective management of manifestations of herd behavior at enterprises. The proposed modeling methodology will allow to identify the prerequisites for the manifestation of herd behavior at enterprises and the potential circle of agents for the formation of adequate managing actions in the process of ensuring effective management of herd behavior and achieving the goals of the enterprise.