Перегляд за Автор "Bidyuk, P."

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    Adaptive forecasting and financial risk estimation
    (КПІ ім. Ігоря Сікорського, 2020) Danilov, V.; Gozhyj, O.; Kalinina, I.; Belas, A.; Bidyuk, P.; Jirov, O.
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    Empirical investigation of the theory of production function, with the data of alloy production in Ukraine
    (Політехніка, 2014) Matsuki, Y.; Bidyuk, P.; Kozyrev, V.; Мацукі, Йошіо; Бідюк, Петро Іванович; Козирєв, В.; Мацуки, Йошио; Бидюк, Петр Иванович; Козырев, В.
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    Energy security cost as an externality — increased gas import price and economy of Ukraine
    (Політехніка, 2012) Matsuki, Y.; Bidyuk, P.; Kalnytskyi, G.; Gavrish, E.; Мацукі, Й.; Бідюк, Петро Іванович; Кальницький, Г. В.; Гавриш, Є. І.; Мацуки, Й.; Бидюк, Петр Иванович; Кальницкий, Г. В.; Гавриш, Е. И.
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    Superconducting gravimeters based on advanced nanomaterials and quantum neural network
    (КПІ ім. Ігоря Сікорського, 2022) Yatsenko, V.; Kruchinin, S.; Bidyuk, P.
    The paper is focused on a new concept of a cryogenic-optical sensor intended for use in the space industry, geodynamics, and fundamental experiments. The basis of the sensor is a magnetic suspension with a levitating test body, a highprecision optical recorder of mechanical coordinates of the levitating body, and a signal-processing system. A Michelson-type interferometer with a laser diode and a single-mode optical fiber was used to measure the test body's displacements. The coordination of the laser diode coherence length and the difference in the interferometer optical lengths of the arms made it possible to eliminate coherent noise caused by interference from spurious reflections. The minimum recorded shift of the test body was 0.1 nm. The design of the sensor and the mathematical model of the superconducting suspension dynamics are presented. The results of experimental studies of a magnetic suspension together with an optical interferometric displacement sensor having a subnanometer sensitivity are shown.
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    The algorithm for predicting the cryptocurrency rate taking into account the influence of posts of a group of famous people in social networks
    (КПІ ім. Ігоря Сікорського, 2023) Bidyuk, P.; Gavrilenko, O.; Myagkyi, M.
    Abstract. This article presents an algorithm for predicting the rate of a selected cryptocurrency, taking into account the posts of a group of famous people in a par ticular social network. The celebrities chosen as experts, i.e., famous personalities whose posts on social networks were studied, are either familiar with the financial industry, particularly the cryptocurrency market, or some cryptocurrency. The data set used was the actual rates of the cryptocurrency in question for the selected period and the statistics of expert posts in the selected social network. The study used methods such as the full probability formula and the Bayesian formula. It was found that posts by famous people on social media differently affected cryptocurrency rates. The “main” expert was identified, and his posts were used to forecast the se lected cryptocurrency’s rate.