Vestnik Yuzhno-Ural'skogo Universiteta. Seriya Matematicheskoe Modelirovanie i Programmirovanie
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive
Submit a manuscript

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Vestnik YuUrGU. Ser. Mat. Model. Progr.:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Vestnik Yuzhno-Ural'skogo Universiteta. Seriya Matematicheskoe Modelirovanie i Programmirovanie, 2016, Volume 9, Issue 3, Pages 105–118
DOI: https://doi.org/10.14529/mmp160309
(Mi vyuru333)
 

Programming & Computer Software

Coefficients identification in fractional diffusion models by the method of time integral characteristics

S. Yu. Lukashchuk

Ufa State Aviation Technical University, Ufa, Russian Federation
References:
Abstract: Inverse problems of identification of the fractional diffusivity and the order of fractional differentiation are considered for linear fractional anomalous diffusion equations with the Riemann–Liouville and Caputo fractional derivatives. As an additional information about the anomalous diffusion process, the concentration functions are assumed to be known at several arbitrary inner points of calculation domain. Numerically-analytical algorithms are constructed for identification of two required parameters of the fractional diffusion equations by approximately known initial data. These algorithms are based on the method of time integral characteristics and use the Laplace transform in time. The Laplace variable can be considered as a regularization parameter in these algorithms. It is shown that the inverse problems under consideration are reduced to the identification problem for a new single parameter which is formed by the fractional diffusivity, the order of fractional differentiation and the Laplace variable. Estimations of the upper error bound for this parameter are derived. A technique of optimal Laplace variable determination based on minimization of these estimations is described. The proposed algorithms are implemented in the AD-TIC package for the Maple software. A brief discussion of this package is also presented.
Keywords: anomalous diffusion; fractional derivatives; inverse coefficient problem; identification algorithm; software package.
Funding agency Grant number
Ministry of Education and Science of the Russian Federation 11.G34.31.0042
This work was supported by the grant of the Ministry of Education and Science of the Russian Federation (contract No. 11.G34.31.0042 with Ufa State Aviation Technical University and leading scientist Professor N.H. Ibragimov).
Received: 13.10.2015
Bibliographic databases:
Document Type: Article
UDC: 517.9
MSC: 65M32
Language: English
Citation: S. Yu. Lukashchuk, “Coefficients identification in fractional diffusion models by the method of time integral characteristics”, Vestnik YuUrGU. Ser. Mat. Model. Progr., 9:3 (2016), 105–118
Citation in format AMSBIB
\Bibitem{Luk16}
\by S.~Yu.~Lukashchuk
\paper Coefficients identification in fractional diffusion models by the method of time integral characteristics
\jour Vestnik YuUrGU. Ser. Mat. Model. Progr.
\yr 2016
\vol 9
\issue 3
\pages 105--118
\mathnet{http://mi.mathnet.ru/vyuru333}
\crossref{https://doi.org/10.14529/mmp160309}
\isi{https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=Publons&SrcAuth=Publons_CEL&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=000390881400009}
\elib{https://elibrary.ru/item.asp?id=25717239}
Linking options:
  • https://www.mathnet.ru/eng/vyuru333
  • https://www.mathnet.ru/eng/vyuru/v9/i3/p105
  • Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Statistics & downloads:
    Abstract page:233
    Full-text PDF :75
    References:38
     
      Contact us:
     Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2024