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An efficient computational approach for time-fractional Rosenau–Hyman equation

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Abstract

In this work, we concentrate on the analysis of the time-fractional Rosenau–Hyman equation occurring in the formation of patterns in liquid drops via q-homotopy analysis transform technique and reduced differential transform approach. The q-homotopy analysis transform algorithm can provide rapid convergent series by choosing the appropriate values of auxiliary parameters ħ and n at large domain. The reduced differential transform technique gives wider applicability due to reduction in computations and makes the calculation much simpler and easier. The proposed techniques are realistic and free from any assumption and perturbation for solving the time-fractional Rosenau–Hyman equation.

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Acknowledgements

The authors are highly grateful to the referees for their invaluable suggestions and comments for the improvement of this article.

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Authors and Affiliations

  1. Department of Mathematics, JECRC University, Jaipur, Rajasthan, 303905, India

    Jagdev Singh & Devendra Kumar

  2. Department of Mathematics, Arya Institute of Engineering and Technology, Riico Kukas, Jaipur, Rajasthan, 303101, India

    Ram Swroop

  3. Department of Mathematics, National Institute of Technology, Jamshedpur, Jharkhand, 831014, India

    Sunil Kumar

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  1. Jagdev Singh
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  4. Sunil Kumar
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Correspondence to Jagdev Singh.

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Singh, J., Kumar, D., Swroop, R. et al. An efficient computational approach for time-fractional Rosenau–Hyman equation. Neural Comput & Applic 30, 3063–3070 (2018). https://doi.org/10.1007/s00521-017-2909-8

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  • DOI: https://doi.org/10.1007/s00521-017-2909-8

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