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Numerical simulation of Burger’s equation using a particle swarm optimization

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Abstract

The process of optimization implies maximizing the advantages of a mathematical function or system while minimizing its shortcomings. Optimizing the parameters associated with a mathematical model has a critical role to play in finding the solution in many aspects. Among the nature-inspired algorithms, particle swarm optimization (PSO) is one such algorithm that offers the potential for global optimization. In this paper, a novel approach is proposed to optimize the solution of the Burger’s equation by implementing the particle swarm optimization along the exponential B-spline basis function with the differential quadrature method (PSO-EDQ). The unknown parameter of exponential basis functions plays an important role in the error calculation. The manuscript is focused on the application of PSO in minimizing the error and thus obtaining the value of the optimal parameter. The numerical results are presented as figures and tables along with comparison with the current studies.

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Authors and Affiliations

  1. Department of Mathematics, Lovely Professional University, Phagwara, Punjab, India

    Geeta Arora

  2. Jaypee Institute of Information Technology, Noida, India

    Pinkey Chauhan

  3. Department of Mathematics, Hamedan Branch, Islamic Azad University, Hamedan, Iran

    Homan Emadifar & Masoumeh Khademi

Authors
  1. Geeta Arora
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  2. Pinkey Chauhan
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  3. Homan Emadifar
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  4. Masoumeh Khademi
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All authors contributed equally to this article. All authors read and approved the final manuscript.

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Correspondence to Homan Emadifar.

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Arora, G., Chauhan, P., Emadifar, H. et al. Numerical simulation of Burger’s equation using a particle swarm optimization. Int. j. inf. tecnol. 15, 2551–2558 (2023). https://doi.org/10.1007/s41870-023-01309-4

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  • DOI: https://doi.org/10.1007/s41870-023-01309-4

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