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Постійне посилання зібранняhttps://repository.lntu.edu.ua/handle/123456789/309
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Item type:Наукова стаття, The system of dynamic optimization pricing by machine learning(Greece, 2024) Konotopchyk, Artem; Melnyk, Kateryna; Lavrenchuk, Svitlana; Khrystynets, Nataliia; Melnyk, Pavlo; Melnyk, Pavlo; Bortnyk, KaterynaBased on the real retail data collected over eight months, a number of models are developed to determine the most efficient machine learning algorithm. It is found that the KNeighbors Regressor model demonstrates the best performance for a small number of transactions, achieving a low MSE of 0.00091 and a high R2 of 0.72 in the validation set. For a large number of transactions, Random Forest Regressor and Decision Tree Regressor show the best ability to capture complex relationships and handle nonlinearties in the data, thanks to the ensemble learning technique. Whereas the Linear Regressor and Support Vector Regressor models demonstrated large deviations from the real price on the test data. The results of the study demonstrate the relevance of rtificial intelligence algorithms in dynamic pricing trategies, showing the ability to quickly process huge amounts of data, taking into account numerous factors and changes in market demand.Item type:Наукова стаття, Simulation of two-stage temperature regulation system.(Lutsk: LNТU, 2023) Pekh, Petro; Khrystynets, Nataliia; Gubysh, Roman; Shulgach, VolodymyrThe article presents the results of the development of the PID controller setting technology using Matlab Simulink tools and the study of the operation process of a closed two-cascade temperature control system based on such controllers. The structural diagrams of the model and the simulation results of the two-cascade system are given.