Maryna Antonevych
Faculty of Information Technology, Taras Shevchenko National University of Kyiv, Ukraine
Anna Didyk
Faculty of Information Technology, Taras Shevchenko National University of Kyiv, Ukraine
Nataliia Tmienova
Faculty of Information Technology, Taras Shevchenko National University of Kyiv, Ukraine
Vitaliy Snytyuk
Faculty of Information Technology, Taras Shevchenko National University of Kyiv, Ukraine
Анотація
DOI: https://doi.org/10.17721/AIT.2021.1.03
This paper is devoted to the problem of optimization of a function in -dimensional space, which, in general case, is polyextreme and undifferentiated. The new method of deformed stars in n-dimensional space was proposed. It is built on the ideas and principles of the evolutionary paradigm. Method of deformed stars is based on the assumption of using potential solutions groups. There by it allows to increase the rate of the accuracy and the convergence of the achieved result. Populations of potential solutions are used to optimize the multivariable function. In contrast to the classical method of deformed stars, we obtained a method that solves problems in
-dimensional space, where the population of solutions consists of 3-, 4-, and 5-point groups. The advantages of the developed method over genetic algorithm, differential evolution and evolutionary strategy as the most typical evolutionary algorithms are shown. Also, experiments were performed to investigate the best configuration of method of deformed stars parameters.
Keywords – enterprise, technology, optimization, method, experiment.
Інформація про авторів
Maryna Antonevych. Student Faculty of Information Technology, Taras Shevchenko National University of Kyiv. Scientific interests: data science, evolutionary algorithms, machine learning, deep learning, computer vision, data mining.
Anna Didyk. Student Faculty of Information Technology, Taras Shevchenko National University of Kyiv. Scientific interests: data science, evolutionary algorithms, web-development, web-design, machine learning, deep learning.
Nataliia Tmienova. Candidate of Physical and Mathematical Sciences (PhD), Associate Professor, Deputy Dean of Academic Studies. Higher Education: Taras Shevchenko University of Kyiv, Master in Social Informatics, Teacher of Mathematics and Informatics. Defended Thesis: PhD: 01.05.04 — System analysis and theory of optimal decisions, “The limit theorems for controlled systems”. Scientific interests: natural language processing, e-learning technologies, queuing systems research, random processes research.
Vitaliy Snytyuk. Doctor of Technical Science, Professor, Dean of the Faculty of Information Technology. Higher education: Taras Shevchenko State University of Kyiv, Mathematician, Lecturer.Defended Theses: PhD 05.13.12 – Systems of automation of design works, “Methods to reduce uncertainty on the initial stages of systems design with variable structure”. Doctoral 05.13.06 – Information technology, “Evolutionary technologies of decision making under uncertainty”. Scientific interests: decision making under uncertainty, computational intelligence, evolutionary modelling.
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Опубліковано
2021-11-04
Як цитувати
Antonevych, A. Didyk, N. Tmienova, V. Snytyuk, “Choosing the best parameters for method of deformed stars in n-dimensional space” Advanced Information Technology, vol.1, pp. 24–28, 2021
Номер
Сучасні інформаційні технології № 1 (1), 2021
Розділ
Штучний та обчислювальний інтелект