Issue №: 6 (46)
The magazine deals with the problems of the agricultural sector of the economy in the context of integration and processes of globalization. Attention is paid to the issues of development of digital economy, rural territories, technologies of enterprise management and organization of accounting, problems of legal support of economic processes, market tendencies of development of various branches of economy. Particular attention is paid to green tourism as a promising segment of the national economy.
DEVELOPMENT OF A METHODOLOGY FOR FORMALIZING THE INVESTMENT DECISION-MAKING PROCESS BASED ON THE HOPFIELD NEURAL NETWORK
RUZAKOVA Olga – Candidate of Science (Economics), assistant professor of the Department of
Computer Science and Economic Cybernetics, Vinnytsia National Agrarian University (21008,
Vinnytsya, 3, Solnyschaya St., e-mail: olgarkv81@gmail.com phone 0975025672).
KIPORENKO Svitlana – Assistant of the Department of Computer Science and Economic
Cybernetics, Vinnitsa National Agrarian University (21008, Vinnitsa, 3, Solnechnaya St., e-mail:
kiporis@i.ua phone 0970343045).
The article presents a methodological approach to assessing the investment attractiveness of an enterprise based on the Hopfield neural network mathematical apparatus. An extended set of evaluation parameters of the investment process has been compiled. An algorithm for formalizing the decision-making process regarding the investment attractiveness of the enterprise based on the mathematical apparatus of neural networks has been developed. The proposed approach allows taking into account the constantly changing sets of quantitative and qualitative parameters, identifying the appropriate level of investment attractiveness of the enterprise with minimal money and time expenses – one of the standards of the Hopfield network, which is most similar to the one that characterizes the activity of the enterprise. Developed complex formalization of the investment process allows you to make investment decisions in the context of incompleteness and heterogeneity of information, based on the methodological tools of neural networks.
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