IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i11p3082-d562304.html
   My bibliography  Save this article

Inverse Problem for a Two-Dimensional Anomalous Diffusion Equation with a Fractional Derivative of the Riemann–Liouville Type

Author

Listed:
  • Rafał Brociek

    (Department of Mathematics Applications and Methods for Artificial Intelligence, Faculty of Applied Mathematics, Silesian University of Technology, 44-100 Gliwice, Poland)

  • Agata Wajda

    (Department of Technologies and Installations for Waste Management, Faculty of Energy and Environmental Engineering, Silesian University of Technology, 44-100 Gliwice, Poland)

  • Damian Słota

    (Department of Mathematics Applications and Methods for Artificial Intelligence, Faculty of Applied Mathematics, Silesian University of Technology, 44-100 Gliwice, Poland)

Abstract

The article presents a method for solving the inverse problem of a two-dimensional anomalous diffusion equation with a Riemann–Liouville fractional-order derivative. In the first part of the present study, the authors present a numerical solution of the direct problem. For this purpose, a differential scheme was developed based on the alternating direction implicit method. The presented method was accompanied by examples illustrating its accuracy. The second part of the study concerned the inverse problem of recreating the model parameters, including the orders of the fractional derivative, in the anomalous diffusion equation. Equations of this type can be used to describe, inter alia, the heat conductivity in porous materials. The ant colony optimization algorithm was used to solve this problem. The authors investigated the impact of the distribution of measurement points, the use of different mesh sizes, and the input data errors on the obtained results.

Suggested Citation

  • Rafał Brociek & Agata Wajda & Damian Słota, 2021. "Inverse Problem for a Two-Dimensional Anomalous Diffusion Equation with a Fractional Derivative of the Riemann–Liouville Type," Energies, MDPI, vol. 14(11), pages 1-17, May.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:11:p:3082-:d:562304
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/11/3082/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/11/3082/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Socha, Krzysztof & Dorigo, Marco, 2008. "Ant colony optimization for continuous domains," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1155-1173, March.
    2. Songshu Liu & Lixin Feng, 2020. "An Inverse Problem for a Two-Dimensional Time-Fractional Sideways Heat Equation," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-13, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Amjad Hudaib & Mohammad Khanafseh & Ola Surakhi, 2018. "An Improved Version of K-medoid Algorithm using CRO," Modern Applied Science, Canadian Center of Science and Education, vol. 12(2), pages 116-116, February.
    2. Liao, Tianjun & Stützle, Thomas & Montes de Oca, Marco A. & Dorigo, Marco, 2014. "A unified ant colony optimization algorithm for continuous optimization," European Journal of Operational Research, Elsevier, vol. 234(3), pages 597-609.
    3. Ali Sardar Shahraki & Mohim Tash & Tommaso Caloiero & Ommolbanin Bazrafshan, 2024. "Optimal Allocation of Water Resources Using Agro-Economic Development and Colony Optimization Algorithm," Sustainability, MDPI, vol. 16(13), pages 1-18, July.
    4. Luo, Qifang & Yang, Xiao & Zhou, Yongquan, 2019. "Nature-inspired approach: An enhanced moth swarm algorithm for global optimization," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 159(C), pages 57-92.
    5. Qiang Yang & Xu Guo & Xu-Dong Gao & Dong-Dong Xu & Zhen-Yu Lu, 2022. "Differential Elite Learning Particle Swarm Optimization for Global Numerical Optimization," Mathematics, MDPI, vol. 10(8), pages 1-32, April.
    6. Yousaf, Muhammad Zain & Koondhar, Mohsin Ali & Zaki, Zaki A. & Ahmed, Emad M. & Alaas, Zuhair Muhammed & Mahariq, Ibrahim & Guerrero, Josep M., 2025. "Improved MPPT of solar PV Systems under different Environmental conditions utilizes a Novel Hybrid PSO," Renewable Energy, Elsevier, vol. 244(C).
    7. Hakan Yılmazer & Selma Ayşe Özel, 2024. "Diverse but Relevant Recommendations with Continuous Ant Colony Optimization," Mathematics, MDPI, vol. 12(16), pages 1-26, August.
    8. Hong, Wei-Chiang, 2010. "Application of chaotic ant swarm optimization in electric load forecasting," Energy Policy, Elsevier, vol. 38(10), pages 5830-5839, October.
    9. Gao, Wei-feng & Huang, Ling-ling & Liu, San-yang & Chan, Felix T.S. & Dai, Cai & Shan, Xian, 2015. "Artificial bee colony algorithm with multiple search strategies," Applied Mathematics and Computation, Elsevier, vol. 271(C), pages 269-287.
    10. Ana Maria A. C. Rocha & M. Fernanda P. Costa & Edite M. G. P. Fernandes, 2017. "On a smoothed penalty-based algorithm for global optimization," Journal of Global Optimization, Springer, vol. 69(3), pages 561-585, November.
    11. Li, Yuanmao & Liu, Guixiong & Deng, Wei & Li, Zuyu, 2024. "Comparative study on parameter identification of an electrochemical model for lithium-ion batteries via meta-heuristic methods," Applied Energy, Elsevier, vol. 367(C).
    12. Behzad Ataie-Ashtiani & Hamed Ketabchi, 2011. "Elitist Continuous Ant Colony Optimization Algorithm for Optimal Management of Coastal Aquifers," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(1), pages 165-190, January.
    13. Md. Hossain & A. El-shafie, 2013. "Intelligent Systems in Optimizing Reservoir Operation Policy: A Review," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(9), pages 3387-3407, July.
    14. Warren Liao, T. & Chang, P.C., 2010. "Impacts of forecast, inventory policy, and lead time on supply chain inventory--A numerical study," International Journal of Production Economics, Elsevier, vol. 128(2), pages 527-537, December.
    15. Yonggang Chen & Yu Qiao & Xiangtuan Xiong, 2022. "Regularization Error Analysis for a Sideways Problem of the 2D Nonhomogeneous Time-Fractional Diffusion Equation," Mathematics, MDPI, vol. 10(10), pages 1-14, May.
    16. Broderick Crawford & Ricardo Soto & Gino Astorga & José García & Carlos Castro & Fernando Paredes, 2017. "Putting Continuous Metaheuristics to Work in Binary Search Spaces," Complexity, Hindawi, vol. 2017, pages 1-19, May.
    17. Asghar Mahdavi & Mohammad Shiri, 2015. "An augmented Lagrangian ant colony based method for constrained optimization," Computational Optimization and Applications, Springer, vol. 60(1), pages 263-276, January.
    18. Stefano Bromuri, 2019. "Dynamic heuristic acceleration of linearly approximated SARSA( $$\lambda $$ λ ): using ant colony optimization to learn heuristics dynamically," Journal of Heuristics, Springer, vol. 25(6), pages 901-932, December.
    19. Ahmad Wedyan & Jacqueline Whalley & Ajit Narayanan, 2017. "Hydrological Cycle Algorithm for Continuous Optimization Problems," Journal of Optimization, Hindawi, vol. 2017, pages 1-25, December.
    20. Peter Korošec & Jurij Šilc, 2013. "The continuous differential ant-stigmergy algorithm for numerical optimization," Computational Optimization and Applications, Springer, vol. 56(2), pages 481-502, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:11:p:3082-:d:562304. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.