Application of Genetic Algorithms for Periodicity Recognition and Finite Sequences Sorting

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Zhassuzak M., AKHMET M., Amirgaliyev Y., Buribayev Z.

Algorithms, vol.17, no.3, 2024 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 17 Issue: 3
  • Publication Date: 2024
  • Doi Number: 10.3390/a17030101
  • Journal Name: Algorithms
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, Academic Search Premier, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, zbMATH, Directory of Open Access Journals, Civil Engineering Abstracts
  • Keywords: chaos theory, genetic algorithm, logistic mapping, periodic sequences, unpredictable sequence, unpredictable strings
  • Middle East Technical University Affiliated: Yes

Abstract

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.