Model order reduction of tumor growth model
Volume 16, Issue 4, pp 222--232
http://dx.doi.org/10.22436/jnsa.016.04.03
Publication Date: October 26, 2023
Submission Date: July 31, 2023
Revision Date: August 16, 2023
Accteptance Date: September 23, 2023
Authors
G. Mulayim
- Department of Mathematics, Faculty of Science and Arts, Adiyaman University, Adiyaman, Turkey.
Abstract
In this paper, reduced order models (ROMs) for the tumor growth model, which is a nonlinear cross-diffusion system are presented. Linear-quadratic ordinary differential equations are obtained by applying the finite difference method to the tumor growth model for spatial discretization. The structure of the ROMs is the same as the structure of the full order model. Proper orthogonal decomposition method with tensorial form is sufficient to compute the reduced solutions efficiently and fast. The results of ROM are presented for one- and two-dimensional cases. Finally, the entropy structure for the reduced solutions, which are in decay form are presented.
Share and Cite
ISRP Style
G. Mulayim, Model order reduction of tumor growth model, Journal of Nonlinear Sciences and Applications, 16 (2023), no. 4, 222--232
AMA Style
Mulayim G., Model order reduction of tumor growth model. J. Nonlinear Sci. Appl. (2023); 16(4):222--232
Chicago/Turabian Style
Mulayim, G.. "Model order reduction of tumor growth model." Journal of Nonlinear Sciences and Applications, 16, no. 4 (2023): 222--232
Keywords
- Tumor growth model
- finite differences
- entropy
- proper orthogonal decomposition
- tensor algebra
MSC
- 37N25
- 35K57
- 35K61
- 65M06
- 65L05
- 34C20
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