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Feasibility study of using artificial intelligence to explore the process of zebra migration

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  • Chen, Shan
  • Ding, Yuanzhao

Abstract

It is essential to comprehend and forecast animal migratory paths. Only with this knowledge will scientists be able to help conserve animals and better safeguard their habitats. Using the zebra migration as an example, this research simulates and interprets the evolution of zebra migration patterns using a revolutionary genetic algorithm method. With this technique, we discover that only when the zebra population size is quite large and the mutation rate is moderate does migratory route evolution go more smoothly. Future efforts to conserve animals will be greatly impacted by this paper's demonstration of the viability of employing a genetic algorithm to comprehend and enhance animal migration pathways.

Suggested Citation

  • Chen, Shan & Ding, Yuanzhao, 2026. "Feasibility study of using artificial intelligence to explore the process of zebra migration," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 242(C), pages 74-83.
    • Handle: RePEc:eee:matcom:v:242:y:2026:i:c:p:74-83
    DOI: 10.1016/j.matcom.2025.11.018
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    References listed on IDEAS

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    1. J Berger & M Barkaoui, 2003. "A new hybrid genetic algorithm for the capacitated vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(12), pages 1254-1262, December.
    2. Ayesha Sohail, 2023. "Genetic Algorithms in the Fields of Artificial Intelligence and Data Sciences," Annals of Data Science, Springer, vol. 10(4), pages 1007-1018, August.
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