Research article

Continuous dependence and stability for a class of fractional partial differential equations with multiple parameters

  • Published: 28 November 2025
  • MSC : 35R11, 35B30

  • In this paper, we studied the continuous dependence and stability of solutions for a class of fractional partial differential equations with multiple spatially varying coefficient parameters. The nonlocal operator was defined by a symmetric kernel, yielding a self-adjoint structure essential to the analysis. Using variational methods and the Minty–Browder theorem, we established the existence and uniqueness of weak solutions in the energy space $ X_0 $ for each admissible parameter vector $ w $. We extended single-parameter stability to a multi-parameter framework by proving that the solution operator $ S_f $ is continuous with respect to $ w $ in the product space $ \prod_i L^{q_i}(\Omega) $. Moreover, we derived an explicit global Lipschitz estimate for $ S_f $ and showed its Gâteaux differentiability under mild regularity assumptions on $ f(x, u, w) $. Numerical simulations confirmed continuity, Lipschitz stability, and differentiability of $ S_f $ with respect to all parameters. These results provided rigorous guarantees for inverse problems and uncertainty quantification in multi-parameter fractional PDE models.

    Citation: Jia Zheng, Xiuling Li, Yanni Pang, Hongying Wang, Tongchao Wang, Jiaxuan Sun. Continuous dependence and stability for a class of fractional partial differential equations with multiple parameters[J]. AIMS Mathematics, 2025, 10(11): 27837-27861. doi: 10.3934/math.20251223

    Related Papers:

  • In this paper, we studied the continuous dependence and stability of solutions for a class of fractional partial differential equations with multiple spatially varying coefficient parameters. The nonlocal operator was defined by a symmetric kernel, yielding a self-adjoint structure essential to the analysis. Using variational methods and the Minty–Browder theorem, we established the existence and uniqueness of weak solutions in the energy space $ X_0 $ for each admissible parameter vector $ w $. We extended single-parameter stability to a multi-parameter framework by proving that the solution operator $ S_f $ is continuous with respect to $ w $ in the product space $ \prod_i L^{q_i}(\Omega) $. Moreover, we derived an explicit global Lipschitz estimate for $ S_f $ and showed its Gâteaux differentiability under mild regularity assumptions on $ f(x, u, w) $. Numerical simulations confirmed continuity, Lipschitz stability, and differentiability of $ S_f $ with respect to all parameters. These results provided rigorous guarantees for inverse problems and uncertainty quantification in multi-parameter fractional PDE models.



    加载中


    [1] A. Annadurai, V. Sureshkumar, D. Jaganathan, S. Dhanasekaran, Enhancing medical image quality using fractional order denoising integrated with transfer learning, Fractal Fract., 8 (2024), 511. https://doi.org/10.3390/fractalfract8090511 doi: 10.3390/fractalfract8090511
    [2] Y. Sire, E. Valdinoci, Fractional Laplacian phase transitions with boundary reactions: A geometric inequality and a symmetry result, J. Funct. Anal., 256 (2009), 1842–1864. https://doi.org/10.1016/j.jfa.2009.01.020 doi: 10.1016/j.jfa.2009.01.020
    [3] R. Cont, P. Tankov, Financial modelling with jump processes, Boca Raton: Chapman & Hall/CRC, 2004. https://doi.org/10.1201/9780203485217
    [4] R. F. Zhang, S. Bilige, Bilinear neural network method to obtain the exact analytical solutions of nonlinear partial differential equations and its application to p-gBKP equation, Nonlinear Dynam., 95 (2019), 3041–3048. https://doi.org/10.1007/s11071-018-04739-z doi: 10.1007/s11071-018-04739-z
    [5] W. Li, J. Sun, Y. Pang, On the study of solutions for a class of third-order semilinear nonhomogeneous delay differential equations, Mathematics, 13 (2025), 1926. https://www.mdpi.com/3351396
    [6] X. R. Xie, R. F. Zhang, Neural network-based symbolic calculation approach for solving the Korteweg–de Vries equation, Chaos Soliton. Fract., 194 (2025), 116232. https://doi.org/10.1016/j.chaos.2025.116232 doi: 10.1016/j.chaos.2025.116232
    [7] S. Liu, G. Dong, H. Bi, B. Wu, On the solutions to variable-order fractional $p$-Laplacian evolution equation with $L^1$-data, Discrete Cont. Dyn.-B, 30 (2025), 4832–4857. https://doi.org/10.3934/dcdsb.2025086 doi: 10.3934/dcdsb.2025086
    [8] M. K. Hamdani, L. Mbarki, M. Allaoui, A new class of multiple nonlocal problems with two parameters and variable-order fractional $p(\cdot)$-Laplacian, Commun. Anal. Mech., 15 (2023), 551–574. https://doi.org/10.3934/cam.2023027 doi: 10.3934/cam.2023027
    [9] S. Biagi, S. Dipierro, E. Valdinoci, E. Vecchi, Semilinear elliptic equations involving mixed local and nonlocal operators, P. Roy. Soc. Edinb. A, 151 (2021), 1611–1641. https://doi.org/10.1017/prm.2020.75 doi: 10.1017/prm.2020.75
    [10] M. d. M. González, R. Monneau, Slow motion of particle systems as a limit of a reaction–diffusion equation with half-Laplacian in dimension one, Discrete Cont. Dyn. Syst., 32 (2012), 1255–1286. https://doi.org/10.3934/dcds.2012.32.1255 doi: 10.3934/dcds.2012.32.1255
    [11] F. Colasuonno, B. Noris, E. Sovrano, Continuous dependence for $p$-Laplace equations with varying operators, Discrete Cont. Dyn.-S, 18 (2025), 1561–1573. https://doi.org/10.3934/dcdss.2024121 doi: 10.3934/dcdss.2024121
    [12] I. M. Batiha, A. A. Abubaker, I. H. Jebril, S. B. Aish, High-performance adaptive step size schemes for nonlinear (variable-order) fractional differential equations, Math. Comput. Simulat., 214 (2025), 43–62. https://doi.org/10.1016/j.matcom.2024.10.012 doi: 10.1016/j.matcom.2024.10.012
    [13] H. Gao, M. K. Ng, Uncertainty quantification of physics-informed neural networks using Wasserstein generative adversarial networks, J. Comput. Phys., 468 (2022), 111510. https://doi.org/10.1016/j.jcp.2022.111510 doi: 10.1016/j.jcp.2022.111510
    [14] X. Fu, M. Ng, Z. Zhang, Physics-informed kernel function neural networks for parametric partial differential equations, J. Comput. Phys., 506 (2024), 112951. https://doi.org/10.1016/j.jcp.2024.112951 doi: 10.1016/j.jcp.2024.112951
    [15] G. Rigas, C. G. Giannetti, D. Lucas, M. A. Scarselli, Adaptive training of physics-informed Kolmogorov–Arnold networks for multi-fidelity modeling, J. Comput. Phys., 503 (2024), 112938. https://doi.org/10.1016/j.jcp.2024.112938 doi: 10.1016/j.jcp.2024.112938
    [16] T. Tripura, S. Chakraborty, Wavelet neural operator for solving parametric partial differential equations in computational mechanics problems, Comput. Method. Appl. M., 404 (2023), 115783. https://doi.org/10.1016/j.cma.2022.115783 doi: 10.1016/j.cma.2022.115783
    [17] R. Stegliński, Existence of a unique solution to a fractional partial differential equation and its continuous dependence on parameters, Entropy, 23 (2021), 851. https://doi.org/10.3390/e23070851 doi: 10.3390/e23070851
    [18] R. Courant, D. Hilbert, Methods of mathematical physics: Partial differential equations, New York: Interscience, 2 (1962). https://doi.org/10.1002/9783527617234
    [19] A. Kirsch, An introduction to the mathematical theory of inverse problems, 2 Eds., New York: Springer, 2011. https://doi.org/10.1007/978-1-4419-8474-6
    [20] M. Galewski, Basic monotonicity methods with some applications, Compact Textbooks in Mathematics, Birkhäuser/Springer, Cham, 2021. https://doi.org/10.1007/978-3-030-75308-5
    [21] E. Zeidler, Nonlinear functional analysis and its applications Ⅱ/A: Linear monotone operators, New York: Springer, 1990. https://doi.org/10.1007/978-1-4612-0985-0
    [22] E. Zeidler, Nonlinear functional analysis and its applications Ⅱ/B: Nonlinear monotone operators, New York: Springer, 1990. https://doi.org/10.1007/978-1-4612-0981-2
    [23] D. Motreanu, V. V. Motreanu, N. S. Papageorgiou, Topological and variational methods with applications to nonlinear boundary value problems, New York: Springer, 2014. https://doi.org/10.1007/978-1-4614-9323-5
    [24] C. Bucur, E. Valdinoci, Nonlocal diffusion and applications, Lecture Notes of the Unione Matematica Italiana, Springer, Cham, 20 (2016). https://doi.org/10.1007/978-3-319-28739-3
  • Reader Comments
  • © 2025 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(342) PDF downloads(24) Cited by(0)

Article outline

Figures and Tables

Figures(3)  /  Tables(1)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog