In this article, the homotopy analysis method (HAM) is applied to solve the fractional cable equation by the Riemann-Liouville fractional partial derivative. This method includes an auxiliary parameter h which provides a convenient way of adjusting and controlling the convergence region of the series solution. In this study, approximate solutions of the fractional cable equation are obtained by HAM. We also give a convergence theorem for this equation. A suitable value for the auxiliary parameter h is determined and results obtained are presented by tables and figures.
Keywords:cable equation; fractional differential equations; fractional cable equation; homotopy analysis method
Fractional calculus has a very long history. However, this field lagged behind classic analysis. In fact, the basis of fractional calculus depended on classic analysis. Especially, in recent years fractional differential equations were used in fluid mechanics, viscoelasticity, biology, pharmacy, physics, chemistry and biochemistry, hydrology, medicine, finance, and engineering. The fractional-order models are more useful than integer-order models in many cases. Structures having fractional order are more useful in the studies that have been done by developing technology.
However, the analytic solutions of most fractional differential equations generally cannot be obtained. Thus, fractional differential equations have been solved by many approximate methods. Examples are the homotopy perturbation method [1,2], the method of separating variables , the iteration method , the decomposition method , and the homotopy analysis method .
In this study, we will consider the cable equation that has been used in modeling the ion electro diffusion at the neurons. The cable equation occurred due to anomalous diffusion and this equation is one of the most fundamental equations for modeling neuronal dynamics . The cable equation can be derived from the Nernst-Planck equation for electrodiffusion in smooth homogeneous cylinders . In recent years, studies were conducted on various biological and physical systems. In this equation, the diffusion rate of species cannot be characterized by the single parameter of the diffusion constant . The anomalous diffusion is characterized by a scaling parameter γ as well as the diffusion constant D and the mean square displacement of diffusing species scales as a nonlinear power law in time, i.e., [7-9]. Henry et al. derived a fractional cable equation from the fractional Nernst-Planck equations to model anomalous electrodiffusion of ions in spiny dentrites . They subsequently found a fractional cable equation by treating the neuron and its membrane as two separate materials governed by separate fractional Nernst-Planck equations. As a result, the fractional cable equation includes two Riemann-Liouville fractional derivatives.
Consider the following fractional cable equation:
where , and are constants, and is the Riemann-Liouville fractional partial derivative of order .
In the literature, there are few treatments of approximate solutions of the fractional cable equation in terms of (1.1). Equation (1.1) has been solved by implicit numerical methods (INM) , the implicit compact difference scheme (ICFDS) , and explicit numerical methods .
Here, we will use the HAM, which is an approximate solution to solve this equation. The HAM method was developed in 1992 by Liao in . This method has been successfully applied by many authors [13-17]. The HAM contains the auxiliary parameter h which provides us with a simple way to adjust and control the convergence region of solution series for large or small values of x and t.
2 Preliminaries and notations
We give some basic definitions and properties of the fractional calculus theory, which are used further in this paper.
where . This integral is convergent for all complex .
3 Homotopy analysis method
We consider the following differential equation:
where is the embedding parameter, is a non-zero auxiliary parameter, is an auxiliary function, L is an auxiliary linear operator, is an initial guess of , and is an unknown function. It is important that one has great freedom to choose auxiliary things in the HAM. Obviously, when and , we have
According to (3.6), the governing equation can be deduced from the zeroth-order deformation equation (3.2). Define the vector
It should be emphasized that for is governed by the nonlinear equation (3.7) with the linear boundary conditions that come from the original problem, which can easily be solved by symbolic computation software such as Maple and Mathematica.
4 Numerical applications and comparison
Consider the following initial and boundary problem of the fractional cable equation:
where . The exact solution of (4.1)-(4.3) is .
We choose the linear operator
Therefore we establish the zeroth-order deformation equation
So we obtain the mth-order deformation equation
Rearrangement of (4.12) gives the mth-order deformation equation
Therefore, some of the symbolically computed components are found as
and so on.
Theorem 4.1 (Convergence Theorem)
Proof If the series
converges, then we can write
and we have
Using definition (4.13), we get
From (4.9), we have
We get the following tables and figures by using a series solution obtained with HAM of (4.1).
In this paper, we have achieved approximate solutions of the fractional cable equation that involve two Riemann-Liouville fractional derivatives by means of the homotopy analysis method. We tried to find an approximate solution of this equation by HAM, which is a semi-analytical method. It is not possible to find the analytical solutions of fractional partial differential equations in most cases. In addition, there is an approximate solution of the fractional cable equation that we have considered just with the finite difference method. The HAM results were given by Tables 1-4 and Figures 1-5.
Table 1. Absolute errors obtained when,, and
Table 2. Comparison of the HPM, HAM, exact solution (ES) and absolute errors results ofwhen,, andfor 5th-order approximation
Table 3. Comparison of the HPM, HAM, exact solution (ES) and absolute errors results ofwhen,, andfor 10th-order approximation
Table 4. Comparison of the HPM, HAM, exact solution (ES) and absolute errors results ofwhen,,, andfor 10th-order approximation
Figure 1. Thehcurves of 5th-order and 10th-order approximate solutions obtained by the HAM for, respectively.
Figure 2. The 10th-order approximate solution ofwith different values ofhforand.
Figure 3. The 10th-order approximate solution ofwith different values ofhfor,and.
Figure 4. Comparison of the HPM, HAM and Exact solution for 5th-order approximate when,and.
Figure 5. Comparison of the HPM, HAM and Exact solution for 10th-order approximate when,and.
The range of convergence control parameter h was determined by taking a different number of terms of the series solution in Figure 1. We showed that convergent results can be obtained by selecting the appropriate values of x and t of the convergence parameter .
An approximate solution that was obtained for different values of the parameter h, the fractional-order derivatives , of the analytical solution and some comparisons for some values of t were presented in Figures 2-3.
A comparison between HPM, HAM, and the analytical solution, when for some values of the auxiliary parameter and partial-order derivatives , was made in Figures 4-5. As can be seen from the figures, HAM and the analytical solution coincided and the HPM solution diverged from the analytical solution.
The absolute errors that were obtained by the implicit numerical method , implicit compact finite difference method , and HAM can be seen in Table 1. In this table and . As can be seen from this table when the convergent control parameter h takes a value close to zero, this method gave better results than the other two methods.
A comparison between HPM, HAM, and the analytical solution for , and some values of the auxiliary parameter were presented in Tables 2-4. As can be seen from the tables, the HPM solution diverged from the analytical solution but the HAM solution approached the analytical solution.
Although convergent results for almost every value of the independent variables and convergent control parameter h have been obtained in HAM; the approximate solution diverged at some small and large values of independent variables in HPM. Namely, it is possible to find results that converge rapidly to the analytical solution by HAM.
The authors declare that they have no competing interests.
All authors contributed equally to the writing of this paper. All authors read and approved the final manuscript.
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