Research article

Algorithms and applications of the new modified decomposition method to solve initial-boundary value problems for fractional partial differential equations

  • Received: 13 January 2025 Revised: 25 February 2025 Accepted: 04 March 2025 Published: 17 March 2025
  • MSC : 35A25, 35C05, 35G16, 35R11

  • This study aims to efficiently solve the class of initial-boundary problems for fractional partial differential equations by expanding the modified Adomian decomposition method. Three new algorithms are proposed, two for handling various fractional initial-boundary problems via the $ x $-differential operator, and one for using the $ t $-differential operator. The proposed methods are designed to increase computational efficiency and ensure greater accuracy in the solutions. The effectiveness of the techniques is reviewed by applying them to a variety of cases, demonstrating their ability to address a broad range of fractional calculus problems. The results emphasize the flexibility and adaptability of the developed algorithms as reliable methods.

    Citation: Mariam Al-Mazmumy, Mona Alsulami, Norah AL-Yazidi. Algorithms and applications of the new modified decomposition method to solve initial-boundary value problems for fractional partial differential equations[J]. AIMS Mathematics, 2025, 10(3): 5806-5829. doi: 10.3934/math.2025267

    Related Papers:

  • This study aims to efficiently solve the class of initial-boundary problems for fractional partial differential equations by expanding the modified Adomian decomposition method. Three new algorithms are proposed, two for handling various fractional initial-boundary problems via the $ x $-differential operator, and one for using the $ t $-differential operator. The proposed methods are designed to increase computational efficiency and ensure greater accuracy in the solutions. The effectiveness of the techniques is reviewed by applying them to a variety of cases, demonstrating their ability to address a broad range of fractional calculus problems. The results emphasize the flexibility and adaptability of the developed algorithms as reliable methods.



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