Numerical analysis of fractional human liver model in fuzzy environment

被引:13
作者
Ahmad, Shabir [1 ]
Ullah, Aman [1 ]
Akgul, Ali [2 ]
Abdeljawad, Thabet [3 ,4 ,5 ]
机构
[1] Univ Malakand, Dept Math, Dir L, Khyber Pakhtunk, Pakistan
[2] Siirt Univ, Art & Sci Fac, Dept Math, Siirt, Turkey
[3] Prince Sultan Univ, Dept Math & Sci, POB 66833, Riyadh 11586, Saudi Arabia
[4] China Med Univ, Dept Med Res, Taichung 40402, Taiwan
[5] Asia Univ, Dept Comp Sci & Informat Engn, Taichung, Taiwan
来源
JOURNAL OF TAIBAH UNIVERSITY FOR SCIENCE | 2021年 / 15卷 / 01期
关键词
Human liver model; fuzzy fractional derivative; uncertainty; fuzzy Laplace transform; H-differentiability; DIFFERENTIAL-EQUATIONS;
D O I
10.1080/16583655.2021.2006894
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Many papers have shown that fractional derivatives are preferable to other operators when the data or information is exact, but this is not the case in practice because we live in an uncertain environment. Fuzzy operators are the best option for modelling in this situation. In this paper, we use the fuzzy fractional Caputo's derivative to generalize the fractional-order human liver model. We consider both types of H-differentiability (type 1 and type 2). We establish a general procedure of solution under the concept of H-differentiability through fuzzy Laplace transform. We implement the proposed scheme to derive the numerical results of the model. We present the archived theoretical solution via two- and three-dimensional graphs at different values of fractional orders and specific fuzzy triangular initial conditions. We present the evolution of the proposed model for some values of phi(0) is an element of[0, 1] to see the effect of uncertainty on the secretion of Bromsulphthalein in the blood and liver.
引用
收藏
页码:840 / 851
页数:12
相关论文
共 32 条
[1]   Liver Anatomy [J].
Abdel-Misih, Sherif R. Z. ;
Bloomston, Mark .
SURGICAL CLINICS OF NORTH AMERICA, 2010, 90 (04) :643-+
[2]   On the concept of solution for fractional differential equations with uncertainty [J].
Agarwal, Ravi P. ;
Lakshmikantham, V. ;
Nieto, Juan J. .
NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS, 2010, 72 (06) :2859-2862
[3]   Fuzzy fractional-order model of the novel coronavirus [J].
Ahmad, S. ;
Ullah, A. ;
Shah, K. ;
Salahshour, S. ;
Ahmadian, A. ;
Ciano, T. .
ADVANCES IN DIFFERENCE EQUATIONS, 2020, 2020 (01)
[4]   Semi-analytical solutions of the 3rd order fuzzy dispersive partial differential equations under fractional operators [J].
Ahmad, Shabir ;
Ullah, Aman ;
Akgul, Ali ;
Abdeljawad, Thabet .
ALEXANDRIA ENGINEERING JOURNAL, 2021, 60 (06) :5861-5878
[5]   A study of fractional order Ambartsumian equation involving exponential decay kernel [J].
Ahmad, Shabir ;
Ullah, Aman ;
Akgul, Ali ;
De la Sen, Manuel .
AIMS MATHEMATICS, 2021, 6 (09) :9981-9997
[6]   Computational analysis of fuzzy fractional order non-dimensional Fisher equation [J].
Ahmad, Shabir ;
Ullah, Aman ;
Ullah, Abd ;
Akgul, Ali ;
Abdeljawad, Thabet .
PHYSICA SCRIPTA, 2021, 96 (08)
[7]   An Operational Matrix Based on Legendre Polynomials for Solving Fuzzy Fractional-Order Differential Equations [J].
Ahmadian, Ali ;
Suleiman, Mohamed ;
Salahshour, Soheil .
ABSTRACT AND APPLIED ANALYSIS, 2013,
[8]   A Jacobi operational matrix for solving a fuzzy linear fractional differential equation [J].
Ahmadian, Ali ;
Suleiman, Mohamed ;
Salahshour, Soheil ;
Baleanu, Dumitru .
ADVANCES IN DIFFERENCE EQUATIONS, 2013,
[9]   Explicit solutions of fractional differential equations with uncertainty [J].
Allahviranloo, T. ;
Salahshour, S. ;
Abbasbandy, S. .
SOFT COMPUTING, 2012, 16 (02) :297-302
[10]   Fuzzy Laplace transforms [J].
Allahviranloo, Tofigh ;
Ahmadi, M. Barkhordari .
SOFT COMPUTING, 2010, 14 (03) :235-243