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Application of Genetic Algorithms for Periodicity Recognition and Finite Sequences Sorting
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Date
2024-03-01
Author
Zhassuzak, Mukhtar
Akhmet, Marat
Amirgaliyev, Yedilkhan
Buribayev, Zholdas
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Unpredictable strings are sequences of data with complex and erratic behavior, which makes them an object of interest in various scientific fields. Unpredictable strings related to chaos theory was investigated using a genetic algorithm. This paper presents a new genetic algorithm for converting large binary sequences into their periodic form. The MakePeriod method is also presented, which is aimed at optimizing the search for such periodic sequences, which significantly reduces the number of generations to achieve the result of the problem under consideration. The analysis of the deviation of a nonperiodic sequence from its considered periodic transformation was carried out, and methods of crossover and mutation were investigated. The proposed algorithm and its associated conclusions can be applied to processing large sequences and different values of the period, and also emphasize the importance of choosing the right methods of crossover and mutation when applying genetic algorithms to this task.
Subject Keywords
chaos theory
,
genetic algorithm
,
logistic mapping
,
periodic sequences
,
unpredictable sequence
,
unpredictable strings
URI
https://hdl.handle.net/11511/109376
Journal
Algorithms
DOI
https://doi.org/10.3390/a17030101
Collections
Department of Mathematics, Article
Citation Formats
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BibTeX
M. Zhassuzak, M. Akhmet, Y. Amirgaliyev, and Z. Buribayev, “Application of Genetic Algorithms for Periodicity Recognition and Finite Sequences Sorting,”
Algorithms
, vol. 17, no. 3, pp. 0–0, 2024, Accessed: 00, 2024. [Online]. Available: https://hdl.handle.net/11511/109376.