Formalization and algorithm of the problem of forecasting decisions made in self-government bodies
Khikmat Rakhimboev JumanazarovichFaculty of Computer Engineering, Urgench branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Urgench, UzbekistanKhalmuratov Omonboy UtamuratovichFaculty of Computer Engineering, Urgench branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Urgench, UzbekistanDavletboev Sardorbek Zokirjon UgliFaculty of Computer Engineering, Urgench branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Urgench, Uzbekistan
2021 International Conference on Information Science and Communications Technologies (ICISCT)conference2021en
ABI
Abstract
This article examines the forecasting of previously adopted or proposed decisions in self-government bodies for a new governing body. For this, machine learning is applied based on a combination of gradient descent and stochastic gradient descent algorithms. As a priori data, generalized assessments of the direction of activity of self-government bodies and the corresponding decisions made or proposed by the experts are used.
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