Abstract
In this manuscript, we discuss fractional fuzzy Goursat problems with Caputo’s
-differentiability. The second-order mixed derivative term in Goursat problems and two types of Caputo’s
-differentiability pose challenges to dealing with Goursat problems. Therefore, in this study, we convert Goursat problems to equivalent systems fuzzy integral equations to deal properly with the mixed derivative term and two types of Caputo’s
-differentiability. In this study, we utilize the concept of metric fixed point theory to discuss the existence of a unique solution of fractional fuzzy Goursat problems. For the useability of established theoretical work, we provide some numerical problems. We also discuss the solutions to numerical problems by conformable double Laplace transform. To show the validity of the solutions we provide 3D plots. We discuss, as an application, why fractional partial fuzzy differential equations are the generalization of usual partial fuzzy differential equations by providing a suitable reason. Moreover, we show the advantages of the proposed fractional transform over the usual Laplace transform.
1. Introduction
The concept of dealing with fuzzyness in real life was initiated in the work of paper []. Classical calculus has been extended to fuzzy and fuzzy fractional calculus for the last two decades. The attention of many mathematicians to modern fuzzy and fuzzy fractional calculus is due to their significant applications, realistic description of physical, optimization, linear programming, banking industry, and biological problems. To optimize path length and energy consumption of robot routing [], we use the fuzzy concept. The use of fuzzy concepts in the data analysis in banking [], medical resources allocation [], decision-making model for the operating system, and human–computer interaction [], etc., show the importance of fuzzy calculus. Also, the uncertainty in physical models is dealt with easily in the fuzzy models [,].
Partial differential equations (PDEs) deal more with real-life problems than ordinary differential equations (DEs) because, during the study of natural phenomena, we often face several variables simultaneously. However, due to uncertainty, PDEs sometimes face difficulty in the study of physical problems. To remove this drawback, the paper [] introduced the fuzzy PDEs (FPDEs). In this direction, many researchers share their contributions, and the fuzzy models on heat [,], advection-diffusion [,], and the Goursat problem [] stem from these.
The generalization of integer order of differential and integral operators to real order generalized classical calculus to fractional calculus. Moreover, integer order differential operators are particular cases of the fractional order. Therefore, researchers show more interest in fractional order differential and integral equations. Salahshour et al. [] extend the gH-differentiability to fuzzy fractional differentiability. In the papers [,,], the existence and solutions of DEs with fuzzy fractional differentiability were discussed. Some fractional order problems are also studied in [,,,,] and the references cited therein.
The Goursat problems have a second-order hyperbolic partial differential equation with mixed derivative terms. This problem arises in the wave phenomena with mixed derivatives. The Goursat problems are different from the other second-order partial differential equations like diffusion, advection-diffusion, and reaction-diffusion equations due to the mixed derivative term. The Goursat problems have important applications in different fields. Therefore, different solutions, processes, and applications of Goursat problems were discussed in [,,,]. The existing conditions of Goursat problems with fuzzy boundary conditions were discussed by [].
In this manuscript, we discuss the Goursat problems with fuzzy boundary conditions and Caputo’s gH-differentiability concept. A fuzzy function is Caputo’s gH-differentiable if it is
differentiable or
differentiable. The second-order FPDEs with gH-differentiability pose challenges due to two types of Caputo’s gH-differentiability. The Goursat problems are partial differential equations with the second-order term having mixed derivatives. Keeping these difficulties in mind, we study three aspects of these problems. First of all, we convert the fractional order Goursat problem to equivalent systems of fuzzy fractional integral equations to deal properly with the two types of Caputo’s gH-differentiability in the mixed derivative term. Next, we show that the equivalent systems of fuzzy fractional integral equations satisfy the FPDE and boundary conditions of the Goursat problem. After that, the results for the existence of unique solutions to fractional fuzzy Goursat problems are the goal of this study. In addition to theoretical proofs, in this manuscript, we discuss numerical examples. We discuss the solutions of numerical examples by conformable double Laplace transform. The manuscript also presents 3D fuzzy plots of solutions to illustrate our findings. In the last, we discuss why fractional FPDEs are the globalization of usual PDEs. We also investigate the advantages of fractional transform on the usual Laplace transform.
2. Preliminaries
Here, we revisit specific findings of the fuzzy and fuzzy fractional calculus. The fuzzy set
is a fuzzy number if it satisfies the following properties for all
- is upper semi-continuous;
- is convex, i.e., ,
- is normal, i.e., ;
- Closure of set is compact.
The set of all F-numbers is fuzzy space, denoted by
.
The
-level set is
where
for all
[].
Definition 1
([]). The
is metric define in term of Hausdorff distance
The complete metric space
has the following properties for all
In this manuscript,
and
are open intervals of real numbers
Definition 2
([]). The
is continuous if for
and arbitrarily fixed
hold the condition
Corollary 1
([]). The function
is integrable if it is continuous.
Remark 1
([]). If
is integrable and
then
.
Lemma 1
([]). If
is integrable and
then
- is integrable in interval
Definition 3
([]). Let
then
difference of
is define by
If the
difference
exist then
Definition 4
([,]). The partial gH-differentiability of
with respect to τ exist at the point
if one of the following conditions holds
- The H-difference exist for sufficiently small and the folloing limits exist in
- The H-difference exist for sufficiently small and the following limits exist in
The first one
is referred to
differentiable and second one
to
differentiable.
Lemma 2
([,]). Let
is a continuous function and
with
. Then for
one can have
- If exist on then
- If exist on then
- If exist on then
- If exist on then
Definition 5
([]). Let
be a fuzzy function. If for
the
and
exists on
Then, u is second-order partial
differentiable with respect to x at
and
differentiable with respect to y at
.
Let us denote the partial second-order [k,l-gH]differentiability of u with respect to
at
by
, where
. Similarly, we have
. For
where
one can write
and
.
Lemma 3
([]). Let
is continuous and
and
such that
exist on
, then
- if where
- if where
Lemma 4
([]). Let
is
-differentiable at
and derivative
is continuous at each
then
The space
consist of
such that
then
and
are continuous. Now, according to Lemma 3 one can write
and
Also for
and
and
Lemma 5
([]). Let
be defined in the neighborhood
of point
Assume that
exist in
be continuous on τ(for fixed ω)
be continuous on ω(for fixed τ) and
be continuous at
If for all
the following H-Differences exist close enough to
And for all
the following H-Differences exist close enough to
For
and
small enough that
exist and
Remark 2
([]). Since
exist in
, then
exist for
enough small. The H-Differences
exist and
Using Lemma 5 one can obtain
Similarly
Definition 6
([]). Let
be a function, the integral of fractional order is defined as
Definition 7
([]). Caputo’s derivative of
is defined as
Definition 8
([]). Caputo’s gH-differentiability of fuzzy valued function
is defined as
Lemma 6
([]). Let function
, then for
- If u is differentiable then
- If u is differentiable then
Lemma 7
([]). Let us have the following equation with
- If u is differentiable, then the equivalent integral form is
- If u is differentiable, then the equivalent integral form is
Definition 9
([]). Let Caputo’s fractional derivative of
with
,
and
be defined as
where
where
with
.
Definition 10
([]). The Mittag–Leffler function
of two parametric forms is defined in the series form as follows
where
Integrating (3) term-by-term, we obtain
Definition 11
([]). The conformable Laplace transform(CLT) with respect to τ of
is given as
Lemma 8
([]). θ-th order conformable Laplace transform(CLT) of order
is define as
3. Existence and Uniqueness Results of Fractional Order Fuzzy Goursat Problem
Now, we discuss an existing result for a unique solution of the fractional order fuzzy Goursat problem.
Let us consider the following fractional FDEs of order
Such that
are continuous on the close rectangle
where
and
are also continuous and
. We search for solution
Let
be the solution of Equation (7) such that
exist and
We convert Equation (7) to the following equivalent systems. For this put
,
where
are continuous fuzzy functions. Therefore, we deduce
Using, Lemma 7 and initial condition we have
- 1:
- For , the following system of equations is obtained
- 2:
- For and , the following system of equations is obtained
- 3:
- For and , the following system of equations is obtained
- 4:
- For , the following system of equations is obtained
Conversely, let us suppose the functions
and
are continuous on Y and satisfying one of the system (9)–(12). We have to show that a solution
to the system of integral equations is the solution to the problem (7) and
Using Lemma 6 and Equation (9), we deduce Equation (8) and
Then,
is
differentiable with respect to
Therefore
Now, on the other hand
From above we can obtain
From Equations (8), (9) and (13) and Remark 1 for
we deduce
Now, we show that
is a solution of Problem (7).
By Equation (9),
satisfies the boundary conditions of Problem (7)
Now, we take the case
Using Lemma 7 and Equation (10), we deduce Equation (8) and
Then
is
differentiable with respect to
Therefore
Now, on the other hand
From above we can obtain
From Equations (8), (10) and (14) and Remark 1 for
we deduce
Now, we show that
is a solution of Problem (7).
By Equation (10),
satisfies the boundary conditions of Problem (7).
The case
can be proven by a similar procedure; therefore, we omit details here.
is
differentiable with respect to
Therefore
Now, on the other hand
From above we can get
From Equations (8), (12) and (15) and Remark 1 for
we deduce
Now, we have to show
is a solution to Problem (7).
By Equation (12),
satisfies the boundary conditions of Problem (7).
Hence, the problem (7) is equivalent to one of the systems from (9) to (12) under the given restrictions. Thus, under the provided restrictions, Problem (7) is equivalent to one of the systems of integral equations from (9) to (12). For the existence of the solution to the problem (7) it is sufficient to study these systems of integral equations. Now, we discuss the existence and uniqueness of results for the solution to Problem (7).
Theorem 1.
Let
is
differentiable and
is
differentiable for fix
then Problem (7) has unique solution in
Proof.
Let us define metric
Let
and
is define by
for
We can easily show that
and
are complete metric spaces therefore, we omit their proofs here. The operator
define for
where
by
For
we have
is defined by
Let
and
Now, the upper bounds for coefficients can be found from the definitions of
and properties of metric
and
as follows
Using two-parameter Mittag–Leffler function
as follows
Using series expression of Mittag–Leffler function
as follows
Hence, one can obtain the following
where
Now, for
we have
is defined by
For
we deduce using a similar procedure to the previous case as follows
Hence, it is possible to choose
and
large enough such that
and
Hence
and
has unique solution to problem (7) in
for
For
the existence of a unique solution can be proven by a similar procedure to the previous case. For
, denote mapping by
and
denote mapping by
the contraction constant
can be obtain by analogous procedure to previous case. □
4. Some Numerical Examples
Now, we discuss numerical examples for the useability and authenticity of established results. For the solutions of numerical problems, we apply a conformable double Laplace transform. In this section, we also provide 3D plots of solutions of numerical examples (See Figure 1, Figure 2, Figure 3 and Figure 4).
Figure 1.
3D plots of the solution of Example (1) with
.
Figure 2.
3D plots of the solution of Example (2) with
.
Figure 3.
3D plots of the solution of Example (4) with
.
Figure 4.
3D plots of the solution of Example (5) with
.
Example 1.
We have the following FPDEs with
and
Since γ is a fuzzy number and
and
are
differentiable then for
by Theorem 1 the problem (16) has a unique solution in
where
Apply conformable double Laplace transform.
Using initial conditions one can get
Apply inverse conformable double Laplace transform to obtain the solution
Since
and
are not
differentiable, the rest of the cases do not have solutions.
Example 2.
Let the following FPDEs with
and
Since γ is a fuzzy number and
and
are
differentiable then for
by Theorem 1 the Problem (17) has a unique solution in
where
Apply conformable double Laplace transform
Using initial conditions and rearranging one can get
Apply inverse conformable double Laplace transform and the required solution is obtained as
Since
and
are not
differentiable, the rest of the cases do not have solutions.
Example 3.
We have the following FPDEs with
and
Since γ is a fuzzy number and
and
are
differentiable, then for
by Theorem 1 the problem (19) has a unique solution in
where
Apply conformable double Laplace transform
Using initial conditions and rearranging one can get
Apply inverse conformable double Laplace transform the required solution is obtained as
Example 4.
We have the following FPDEs with
and
Since γ is a fuzzy number and
and
are
differentiable then for
by Theorem 1 the problem (20) has a unique solution in
where
Apply conformable double Laplace transform
Using initial conditions and rearranging one can get
Apply inverse conformable double Laplace transform the required solution is obtained as
Example 5.
We have the following FPDEs with
and
Since γ is a fuzzy number and
and
are
differentiable then for
by Theorem 1 the problem (21) has a unique solution in
where
Apply conformable double Laplace transform
Using initial conditions and rearranging one can get
Apply inverse conformable double Laplace transform the required solution is obtain as
5. Applications of Fractional Fuzzy Goursat Problems
Fractional calculus is the generalization of usual calculus. In this section, we discuss some facts about the generalization of fractional differentiability and fractional transform. Let us consider the following fuzzy partial differential equation
Since
is a fuzzy number and
and
are
differentiable then for
by Theorem 1 the problem (22) has a unique solution in
where
Now, apply conformable double Laplace transform
Using initial conditions and rearranging Equation (23), one can get
By applying the inverse conformable double Laplace transform the required solution is obtain as
Note that the fractional transform discussed in this work, particularly in this problem, is more easy than the usual Laplace transform. Also, fractional differential equations and their solutions are generalizations of usual differential equations because if
then, we obtain the usual form discussed in []. Moreover, the fractional partial differential Equation (22) and their solution produce the partial fractional differential equations and solutions for any value
particularly if
and
then Equation (22) produce the following problem
where solution of Equation (24) is
Caputo’s fractional derivative of order
and first-order usual derivative of
are the following, respectively,
Caputo’s fractional derivative of
and
exist at 0 but the usual derivative does not exist at 0; therefore, the fractional derivative is the generalization of the usual derivative. Concluding the above facts, we claim that this work is more advanced than [].
6. Conclusions and Future Direction
In this manuscript, we discussed fractional order fuzzy Goursat problems with Caputo’s gH-differentiability. The Goursat problems have partial differential equations with second-order mixed derivatives. Also, Caputo’s gH-differentiability has two types,
differentiability and
differentiability. To avoid the difficulties of mixed derivative terms and two types of Caputo’s gH-differentiability, we convert the Goursat problem to four equivalent systems of fuzzy fractional integral equations. The four systems of fuzzy fractional integral equations produced for a Goursat problem due to two types the Caputo’s gH-differentiability. In this study, we discussed that all the equivalent systems of fuzzy fractional integral equations satisfy the FPDEs and boundary conditions of the Goursat problem. After that, we discussed the existence and uniqueness result of fuzzy Goursat problems by using equivalent systems of fuzzy fractional integral equations. In addition to theoretical proofs, we provided numerical examples to show the useability of the theoretical work. We used conformable double Laplace transform for the solutions of numerical examples. In the application, we discussed the generalization of PFDEs and the advantage of fractional differentiability over the usual differentiability. Moreover, we show the advantage of fractional transform over the usual Laplace transform. This manuscript presents 3D fuzzy plots of solutions to illustrate our findings. This type of setting is also interesting for other second-order fractional FPDEs like advection equations, advection-diffusion equations, heat equations, etc. Moreover, this study is also interesting with other types of fuzzy differences and differentiability. The stability analysis of the solutions of Goursat problems and other second-order fractional FPDEs with this type of setting is also interesting for study in the future.
Author Contributions
Conceptualization, N.J.; Validation, T.S.; Formal analysis, C.P. and T.S.; Investigation, C.P.; Writing—original draft, N.J.; Writing—review and editing, M.S.; Visualization, K.A.; Supervision, M.S. and K.A.; Funding acquisition, C.P. and T.S. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by the National Science, Research and Innovation Fund (NSRF), and King Mongkut’s University of Technology North Bangkok with Contract no. KMUTNB-FF-67-B-31.
Data Availability Statement
Data sharing is not applicable to this article as no data sets are generated or analyzed during the current study.
Acknowledgments
The authors would like to thank the Prince Sultan University for the support of this work through TAS LAB.
Conflicts of Interest
The authors declare that they have no competing interests.
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