Research article

Optimal investment and reinsurance for the insurer and reinsurer with the joint exponential utility under the CEV model

  • This paper considers the problem of optimal investment-reinsurance for the insurer and reinsurer under the constant elasticity of variance (CEV) model. It is assumed that the net claims process is approximated by a diffusion process, both the insurer and reinsurer can invest in risk-free assets and risky assets. We use the variance premium principle to calculate the premiums of the insurer and reinsurer, and the reinsurance proportion is constrained by the net profit condition. Our objective is to maximize the joint exponential utility of the insurer and reinsurer's terminal wealth for a fixed time. By solving the HJB equation, we obtain the explicit expressions of the optimal investment-reinsurance strategy and value function. We find that the optimal reinsurance strategy can be divided into many cases and is related to the risk aversion coefficient of the insurer and reinsurer, but independent of the price of risky assets. Furthermore, we give the proof of the verification theorem. Finally, we demonstrate a numerical analysis to explain the results.

    Citation: Ling Chen, Xiang Hu, Mi Chen. Optimal investment and reinsurance for the insurer and reinsurer with the joint exponential utility under the CEV model[J]. AIMS Mathematics, 2023, 8(7): 15383-15410. doi: 10.3934/math.2023786

    Related Papers:

    [1] Yousef Jawarneh, Humaira Yasmin, Abdul Hamid Ganie, M. Mossa Al-Sawalha, Amjid Ali . Unification of Adomian decomposition method and ZZ transformation for exploring the dynamics of fractional Kersten-Krasil'shchik coupled KdV-mKdV systems. AIMS Mathematics, 2024, 9(1): 371-390. doi: 10.3934/math.2024021
    [2] Saima Rashid, Rehana Ashraf, Fahd Jarad . Strong interaction of Jafari decomposition method with nonlinear fractional-order partial differential equations arising in plasma via the singular and nonsingular kernels. AIMS Mathematics, 2022, 7(5): 7936-7963. doi: 10.3934/math.2022444
    [3] Khalid Khan, Amir Ali, Manuel De la Sen, Muhammad Irfan . Localized modes in time-fractional modified coupled Korteweg-de Vries equation with singular and non-singular kernels. AIMS Mathematics, 2022, 7(2): 1580-1602. doi: 10.3934/math.2022092
    [4] M. Mossa Al-Sawalha, Osama Y. Ababneh, Rasool Shah, Amjad khan, Kamsing Nonlaopon . Numerical analysis of fractional-order Whitham-Broer-Kaup equations with non-singular kernel operators. AIMS Mathematics, 2023, 8(1): 2308-2336. doi: 10.3934/math.2023120
    [5] Muath Awadalla, Abdul Hamid Ganie, Dowlath Fathima, Adnan Khan, Jihan Alahmadi . A mathematical fractional model of waves on Shallow water surfaces: The Korteweg-de Vries equation. AIMS Mathematics, 2024, 9(5): 10561-10579. doi: 10.3934/math.2024516
    [6] Khalid Khan, Amir Ali, Muhammad Irfan, Zareen A. Khan . Solitary wave solutions in time-fractional Korteweg-de Vries equations with power law kernel. AIMS Mathematics, 2023, 8(1): 792-814. doi: 10.3934/math.2023039
    [7] Gulalai, Shabir Ahmad, Fathalla Ali Rihan, Aman Ullah, Qasem M. Al-Mdallal, Ali Akgül . Nonlinear analysis of a nonlinear modified KdV equation under Atangana Baleanu Caputo derivative. AIMS Mathematics, 2022, 7(5): 7847-7865. doi: 10.3934/math.2022439
    [8] Aslı Alkan, Halil Anaç . The novel numerical solutions for time-fractional Fornberg-Whitham equation by using fractional natural transform decomposition method. AIMS Mathematics, 2024, 9(9): 25333-25359. doi: 10.3934/math.20241237
    [9] Ahu Ercan . Comparative analysis for fractional nonlinear Sturm-Liouville equations with singular and non-singular kernels. AIMS Mathematics, 2022, 7(7): 13325-13343. doi: 10.3934/math.2022736
    [10] Eman A. A. Ziada, Salwa El-Morsy, Osama Moaaz, Sameh S. Askar, Ahmad M. Alshamrani, Monica Botros . Solution of the SIR epidemic model of arbitrary orders containing Caputo-Fabrizio, Atangana-Baleanu and Caputo derivatives. AIMS Mathematics, 2024, 9(7): 18324-18355. doi: 10.3934/math.2024894
  • This paper considers the problem of optimal investment-reinsurance for the insurer and reinsurer under the constant elasticity of variance (CEV) model. It is assumed that the net claims process is approximated by a diffusion process, both the insurer and reinsurer can invest in risk-free assets and risky assets. We use the variance premium principle to calculate the premiums of the insurer and reinsurer, and the reinsurance proportion is constrained by the net profit condition. Our objective is to maximize the joint exponential utility of the insurer and reinsurer's terminal wealth for a fixed time. By solving the HJB equation, we obtain the explicit expressions of the optimal investment-reinsurance strategy and value function. We find that the optimal reinsurance strategy can be divided into many cases and is related to the risk aversion coefficient of the insurer and reinsurer, but independent of the price of risky assets. Furthermore, we give the proof of the verification theorem. Finally, we demonstrate a numerical analysis to explain the results.



    Fractional calculus is as old as ordinary calculus, i. e. at three centuries; however, it is not widely used in research and engineering. In a letter to Leibniz dated September 30, 1695, L'Hopital introduced the concept of fractional-order derivatives. In Lacroix's writings, P. S. Laplace defined a fractional derivative of arbitrary order in 1812. Several researchers have developed excellent literature on fractional differentiation and integration operators for the purposes of extending scientific and technical areas, including Caputo [1], Oldham and Spanier [2], Carpinteri and Mainardi [3], Samko et al. [4], Ahmed et al. [5], Podlubny [6], Atangana and Alabaraoye [7], Kumar et al. [8], Yin et al. [9] and Arife et al. [10]. The beauty of fractional derivatives is that they are not local point properties. The genetic and nonlocal dispersed effects are taken into account in fractional calculus. This property makes it more accurate than the integer-order derivative description.

    Due to their proven applications in science and engineering, fractional differential equations have grown in prominence and popularity. These equations, for example, are increasingly being utilized to simulate problems in signal processing, biology, fluid mechanics, acoustics, diffusion, electromagnetism and a wide range of other physical phenomena. The nonlocal quality of fractional differential equations is the most essential advantage of utilizing them in these and other applications. The integer order differential operator is well-known to be a local operator, whereas the fractional order differential operator is not. This indicates that a system's next state is determined not just by its current state, but also by all of its previous states. The theory of fractional differential equations better and more systematically describes natural occurrences [11,12,13,14,15,16,17,18,19].

    Fractional coupled systems are commonly used to investigate the complex behavior of plasma that contains several components such as atoms, free electrons and ions. Many scholars have tried to assess this behavior. Recently, Paul Kersten and Joseph Krasil'shchik investigated the Korteweg-de Vries (KdV) equation and modified KdV (mKdV) equation, proposing absolute complexity between coupled KdV-mKdV nonlinear systems for the investigation of nonlinear system behavior [20,21,22,23]. Many scholars have proposed numerous variants of this Kersten-Krasil'shchik coupled KdV-mKdV nonlinear system [24,25,26,27,28]. Among these variants, the nonlinear fractional Kersten-Krasil'shchik linked KdV-mKdV system provides a mathematical model for understanding the behavior of multi-component plasma for waves travelling along the positive zeta axis:

    DαχF+F3ϑ6FFϑ+3GG3ϑ+3GϑG2ϑ3FϑG2+6FGGϑ=0,  χ>0,  ϑR,  0<α1,DαχG+G3ϑ3G2Gϑ3FGϑ+3FϑG=0,  χ>0,  ϑR,  0<α1, (1.1)

    where ϑ is a spatial coordinate and χ is a time coordinate. The fractional operator's order is represented by the factor α. The Caputo form is used to study this operator. When α=1, the fractional coupled system becomes a classical system, as follows:

    Fχ+F3ϑ6FFϑ+3GG3ϑ+3GϑG2ϑ3FϑG2+6FGGϑ=0,  χ>0,  ϑR,Gχ+G3ϑ3G2Gϑ3FGϑ+3FϑG=0,  χ>0,  ϑR. (1.2)

    If G=0, the Kersten-Krasil'shchik linked KdV-mKdV system is converted to the well-known KdV system as follows:

    Fχ+F3ϑ6FFϑ=0,  χ>0,  ϑR. (1.3)

    When F=0, the Kersten-Krasil'shchik coupled KdV-mKdV system becomes the well-known mKdV system as follows:

    Gχ+G3ϑ3G2Gϑ=0,  χ>0,  ϑR. (1.4)

    As a result, the Kersten-Krasil'shchik linked KdV-mKdV system can be considered of as a combination of the KdV system and the mKdV system, which are represented by (1.2) to (1.4). We also investigate the following fractional nonlinear two component homogeneous time fractional coupled third order KdV system in this work as follows:

    DαχFF3ϑFFϑGGϑ=0,χ>0,ϑR,0<α1,DαχG+2G3ϑFGϑ=0,χ>0,ϑR,0<α1, (1.5)

    where χ is the temporal coordinate, ϑ is the spatial coordinate and α is the fractional operator's order factor. The Caputo form is used to study this operator. When α=1, the fractional coupled system becomes a classical system, as follows:

    FχF3ϑFFϑGGϑ=0,  χ>0,  ϑR,Gχ+2G3ϑFGϑ=0,  χ>0,ϑR. (1.6)

    To solve the differential equations, we employ the natural decomposition method (NDM), which combines the natural transform (NT) and Adomian decomposition method and offers the approximate solution in series form. The proposed method has been implemented with the aid of two different fractional derivatives to solve two nonlinear systems. Many researchers have employed the NDM to obtain approximate analytical solutions, and it has provided reliable and closely convergent results. The calculations were done in Maple. The convergence of the proposed technique was also achieved by extending the concept discussed in [29,30].

    The organization of the present paper is as follows: Section 2 gives some basic definitions and the properties of the natural transform that is used in our present work. Section 3 handles the methodology of the proposed technique. In Section 4, we presented the convergence analysis of the suggested technique. Section 5 gives the implementation of the suggested approach to approximate the solution of the above systems. Finally, we discuss the obtained results and conclusion.

    In this section, we recall some basic definitions and results from fractional calculus.

    Definition 2.1. The Riemann-Liouville integral of a function jCμ, μ1, having fractional-order is defined as [31]

    Iαj(ρ)=1Γ(α)ρ0(ρμ)α1j(μ)dμ,  α>0,  ρ>0,and  I0j(ρ)=j(ρ). (2.1)

    Definition 2.2. The derivative of j(ρ) with fractional-order in the Caputo sense is given as [31]

    Dαρj(ρ)=ImαDmj(ρ)=1Γ(mα)ρ0(ρμ)mα1D(j(μ))dμ, (2.2)

    for m1<αm,  mN,  ρ>0,jCmμ,μ1.

    Definition 2.3. The derivative of j(ρ) with fractional-order in the Caputo-Fabrizio (CF) manner is given as [31]

    Dαρj(ρ)=F(α)1αρ0exp(α(ρμ)1α)D(j(μ))dμ, (2.3)

    where 0<α<1 and F(α) is a normalization function with F(0)=F(1)=1.

    Definition 2.4. The derivative of j(ρ) with fractional-order in the Atangana-Baleanu-Caputo operator (ABC) manner is given as [31]

    Dαρj(ρ)=B(α)1αρ0Eα(α(ρμ)α1α)D(j(μ))dμ, (2.4)

    where 0<α<1, B(α) is normalization function and Eα(z)=m=0zmΓ(αm+1) is the Mittag-Leffler function.

    Definition 2.5. For the function F(χ), the natural transformation is given as

    N(F(χ))=U(ζ,τ)=eζχF(τχ)dχ,  ζ,τ(,), (2.5)

    and for χ(0,), the natural transformation of F(χ) is given as

    N(F(χ)H(χ))=N+F(χ)=U+(ζ,τ)=0eζχF(τχ)dχ,  ζ,τ(0,), (2.6)

    where H(χ) is the Heaviside function.

    Definition 2.6. For the function F(ζ,τ), the inverse natural transformation is given as

    N1[U(ζ,τ)]=F(χ),  χ0. (2.7)

    Lemma 2.1. Let the F1(χ) and F2(χ) natural transformations be U1(ζ,τ) and U2(ζ,τ); so,

    N[c1F1(χ)+c2F2(χ)]=c1N[F1(χ)]+c2N[F2(χ)]=c1U1(ζ,τ)+c2U2(ζ,τ), (2.8)

    where c1 and c2 constants.

    Lemma 2.2. Let the F1(χ) and F2(χ) inverse natural transformations be F1(ζ,τ) and F2(ζ,τ); so,

    {N}1[c1U1(ζ,τ)+c2U2(ζ,τ)]=c1N1[U1(ζ,τ)]+c2N1[U2(ζ,τ)]=c1F1(χ)+c2F2(χ), (2.9)

    where c1 and c2 constants.

    Definition 2.7. The NT of DαχF(χ) in the Caputo sense is stated as [31]

    N[DαχF(χ)]=(ζτ)α(N[F(χ)](1ζ)F(0)). (2.10)

    Definition 2.8. The NT of DαχF(χ) in the CF sense is defined as [31]

    N[DαχF(χ)]=11α+α(τζ)(N[F(χ)](1ζ)F(0)). (2.11)

    Definition 2.9. The NT of DαχF(χ) in the ABC manner is given as [31]

    N[DαχF(χ)]=M[α]1α+α(τζ)α(N[F(χ)](1ζ)F(0)), (2.12)

    with M[α] denoting a normalization function.

    This section is concerned with the general procedure for numerical treatment of the below equation.

    DαχF(ϑ,χ)=L(F(ϑ,χ))+N(F(ϑ,χ))+h(ϑ,χ)=M(ϑ,χ), (3.1)

    where the initial condition

    F(ϑ,0)=ϕ(ϑ) (3.2)

    has L and N linear and nonlinear terms, and where h(ϑ,χ) represents the source term.

    By means of the NT and CF fractional derivative, Eq (3.1) can be stated as

    1p(α,τ,ζ)(N[F(ϑ,χ)]ϕ(ϑ)ζ)=N[M(ϑ,χ)], (3.3)

    with

    p(α,τ,ζ)=1α+α(τζ). (3.4)

    By taking the natural inverse transform, we get

    F(ϑ,χ)=N1(ϕ(ϑ)ζ+p(α,τ,ζ)N[M(ϑ,χ)]). (3.5)

    Assume that for F(ϑ,χ), the series form solution is determined as

    F(ϑ,χ)=i=0Fi(ϑ,χ), (3.6)

    and the N(F(ϑ,χ)) decomposition is given as

    N(F(ϑ,χ))=i=0Ai(F0,...,Fi), (3.7)

    with Ai representing the Adomian polynomials, which is illustrated as

    An=1n!dndεnN(ε,Σnk=0εkFk)|ε=0.

    By putting Eqs (3.6) and (3.7) into Eq (3.5), we have

    i=0Fi(ϑ,χ)=N1(ϕ(ϑ)ζ+p(α,τ,ζ)N[h(ϑ,χ)])+N1(p(α,τ,ζ)N[i=0L(Fi(ϑ,χ))+Ai]). (3.8)

    From Eq (3.8), we obtain

    FCF0(ϑ,χ)=N1(ϕ(ϑ)ζ+p(α,τ,ζ)N[h(ϑ,χ)]),FCF1(ϑ,χ)=N1(p(α,τ,ζ)N[L(F0(ϑ,χ))+A0]),FCFl+1(ϑ,χ)=N1(p(α,τ,ζ)N[L(Fl(ϑ,χ))+Al]),  l=1,2,3,. (3.9)

    In this way, the solution of Eq (3.1) is obtained by putting Eq (3.9) into Eq (3.6) to solve for the NTDMCF,

    FCF(ϑ,χ)=FCF0(ϑ,χ)+FCF1(ϑ,χ)+FCF2(ϑ,χ)+. (3.10)

    By means of the NT and ABC fractional derivative, Eq (3.1) can be stated as

    1q(α,τ,ζ)(N[F(ϑ,χ)]ϕ(ϑ)ζ)=N[M(ϑ,χ)], (3.11)

    with

    q(α,τ,ζ)=1α+α(τζ)αB(α). (3.12)

    By taking the natural inverse transform, we get

    F(ϑ,χ)=N1(ϕ(ϑ)ζ+q(α,τ,ζ)N[M(ϑ,χ)]). (3.13)

    In terms of the Adomain decomposition, we have

    i=0Fi(ϑ,χ)=N1(ϕ(ϑ)ζ+q(α,τ,ζ)N[h(ϑ,χ)])+N1(q(α,τ,ζ)N[i=0L(Fi(ϑ,χ))+Ai]). (3.14)

    From Eq (3.8), we have the following:

    FABC0(ϑ,χ)=N1(ϕ(ϑ)ζ+q(α,τ,ζ)N[h(ϑ,χ)]),FABC1(ϑ,χ)=N1(q(α,τ,ζ)N[L(F0(ϑ,χ))+A0]),FABCl+1(ϑ,χ)=N1(q(α,τ,ζ)N[L(Fl(ϑ,χ))+Al]),  l=1,2,3,. (3.15)

    In this way, the solution of Eq (3.1) is obtained to solve for the NTDMABC:

    FABC(ϑ,χ)=FABC0(ϑ,χ)+FABC1(ϑ,χ)+FABC2(ϑ,χ)+. (3.16)

    This section is concerned with the NTDMABC and NTDMCF convergence and uniqueness.

    Theorem 4.1. Let |L(F)L(F)|<γ1|FF| and |N(F)N(F)|<γ2|FF|, where F:=F(μ,χ) and F:=F(μ,χ) are two variable functions values, and γ1, γ2 are Lipschitz constants.

    The operators L and N are given in Eq (3.1). Thus, the solution for the NTDMCF is unique for Eq (3.1) when 0<(γ1+γ2)(1α+αχ)<1 for all χ.

    Proof. Let K=(C[J],||.||), where norm ||ϕ(χ)||=maxχJ|ϕ(χ)| is the Banach space and continuous on the J=[0,T] interval. Let I:KK be a nonlinear mapping with

    FCl+1=FC0+N1[p(α,τ,ζ)N[L(Fl(μ,χ))+N(Fl(μ,χ))]],  l0.
    ||I(F)I(F)||maxχJ|N1[p(α,τ,ζ)N[L(F)L(F)]+p(α,τ,ζ)N[N(F)N(F)]|]maxχJ[γ1N1[p(α,τ,ζ)N[|FF|]]+γ2N1[p(α,τ,ζ)N[|FF|]]]maxχJ(γ1+γ2)[N1[p(α,τ,ζ)N|FF|]](γ1+γ2)[N1[p(α,τ,ζ)N||FF||]]=(γ1+γ2)(1α+αχ)||FF||. (4.1)

    So, I is a contraction as 0<(γ1+γ2)(1α+αχ)<1. Thus, by means of the Banach fixed point theorem, the solution of Eq (3.1) is unique.

    Theorem 4.2. According to the above theorem, the solution of Eq (3.1) is unique for the NTDMABC when 0<(γ1+γ2)(1α+αχαΓ(α+1))<1 for all χ.

    Proof. Now, from the theorem above, let K=(C[J],||.||) be the Banach space that is continuous on the J=[0,T] interval. Let I:KK be the nonlinear mapping with

    FCl+1=FC0+N1[p(α,τ,ζ)N[L(Fl(μ,χ))+N(Fl(μ,χ))]],  l0.
    ||I(F)I(F)||maxχJ|N1[q(α,τ,ζ)N[L(F)L(F)]+q(α,τ,ζ)N[N(F)N(F)]|]maxχJ[γ1N1[q(α,τ,ζ)N[|FF|]]+γ2N1[q(α,τ,ζ)N[|FF|]]]maxχJ(γ1+γ2)[N1[q(α,τ,ζ)N|FF|]](γ1+γ2)[N1[q(α,τ,ζ)N||FF||]]=(γ1+γ2)(1α+αχαΓ(α+1))||FF||. (4.2)

    So, I is a contraction as 0<(γ1+γ2)(1α+αχαΓ(α+1))<1. Thus, by means of the Banach fixed point theorem, the solution of Eq (3.1) is unique.

    Theorem 4.3. Let L and N be Lipschitz functions as given in the above theorems; then, the solution for the NTDMCF is convergent for Eq (3.1).

    Proof. Let us consider K to be the Banach space as stated above and let Fm=mr=0Fr(μ,χ). To prove that Fm is a Cauchy sequence in H, let

    ||FmFn||=maxχJ|mr=n+1Fr|,  n=1,2,3,maxχJ|N1[p(α,τ,ζ)N[mr=n+1(L(Fr1)+N(Fr1))]]|=maxχJ|N1[p(α,τ,ζ)N[m1r=n+1(L(Fr)+N(Fr))]]|maxχJ|N1[p(α,τ,ζ)N[(L(Fm1)L(Fn1)+N(Fm1)N(Fn1))]]|γ1maxχJ|N1[p(α,τ,ζ)N[(L(Fm1)L(Fn1))]]|+γ2maxχJ|N1[p(α,τ,ζ)N[(N(Fm1)N(Fn1))]]|=(γ1+γ2)(1α+αχ)||Fm1Fn1||. (4.3)

    Let m=n+1; then,

    ||Fn+1Fn||γ||FnFn1||γ2||Fn1Fn2||γn||F1F0||, (4.4)

    where γ=(γ1+γ2)(1α+αχ). Thus, we have that

    ||FmFn||||Fn+1Fn||+||Fn+2Fn+1||++||FmFm1||,(γn+γn+1++γm1)||F1F0||γn(1γmn1γ)||F1||. (4.5)

    As 0<γ<1, we have that 1γmn<1. Thus,

    ||FmFn||γn1γmaxχJ||F1||. (4.6)

    Since ||F1||<,  ||FmFn||0 when n. In this way, Fm is a Cauchy sequence in K and is convergent.

    Theorem 4.4. Let L and N be Lipschitz functions as given in the above theorems; then, the solution for the NTDMABC is convergent for Eq (3.1).

    Proof. Suppose Fm=mr=0Fr(μ,χ). To prove that Fm is a Cauchy sequence in K, let

    ||FmFn||=maxχJ|mr=n+1Fr|,  n=1,2,3,maxχJ|N1[q(α,τ,ζ)N[mr=n+1(L(Fr1)+N(Fr1))]]|=maxχJ|N1[q(α,τ,ζ)N[m1r=n+1(L(Fr)+N(ur))]]|maxχJ|N1[q(α,τ,ζ)N[(L(Fm1)L(Fn1)+N(Fm1)N(Fn1))]]|
    γ1maxχJ|N1[q(α,τ,ζ)N[(L(Fm1)L(Fn1))]]|+γ2maxχJ|N1[p(α,τ,ζ)N[(N(Fm1)N(Fn1))]]|=(γ1+γ2)(1α+αχαΓ(α+1))||Fm1Fn1||. (4.7)

    Suppose m=n+1; thus,

    ||Fn+1Fn||γ||FnFn1||γ2||Fn1Fn2||γn||F1F0||, (4.8)

    where γ=(γ1+γ2)(1α+αχαΓ(α+1)). Thus, we have that

    ||FmFn||||Fn+1Fn||+||Fn+2Fn+1||++||FmFm1||,(γn+γn+1++γm1)||F1F0||γn(1γmn1γ)||F1||. (4.9)

    As 0<γ<1, we have that 1γmn<1. Thus,

    ||FmFn||γn1γmaxχJ||F1||. (4.10)

    Since ||F1||<,  ||FmFn||0 when n. In this way, Fm is a Cauchy sequence in K and convergent.

    Example 5.1. Let us consider the fractional Kersten-Krasil'shchik coupled KdV-mKdV nonlinear system as

    DαχF+F3ϑ6FFϑ+3GG3ϑ+3GϑG2ϑ3FϑG2+6FGGϑ=0,  χ>0,  ϑR,  0<α1,DαχG+G3ϑ3G2Gϑ3FGϑ+3FϑG=0, (5.1)

    where the initial conditions are as follows:

    F(ϑ,0)=c2csech2(cϑ),    c>0,G(ϑ,0)=2csech(cϑ). (5.2)

    By taking the NT, we get

    N[DαχF(ϑ,χ)]=N[F3ϑ6FFϑ+3GG3ϑ+3GϑG2ϑ3FϑG2+6FGGϑ],N[DαχG(ϑ,χ)]=N[G3ϑ3G2Gϑ3FGϑ+3FϑG]. (5.3)

    Thus, we have that

    1ζαN[F(ϑ,χ)]ζ2αF(ϑ,0)=N[F3ϑ6FFϑ+3GG3ϑ+3GϑG2ϑ3FϑG2+6FGGϑ],1ζαN[G(ϑ,χ)]ζ2αF(ϑ,0)=N[G3ϑ3G2Gϑ3FGϑ+3FϑG]. (5.4)

    By simplification, we get

    N[F(ϑ,χ)]=ζ2[c2csech2(cϑ)]α(ζα(ζα))ζ2N[F3ϑ6FFϑ+3GG3ϑ+3GϑG2ϑ3FϑG2+6FGGϑ],N[G(ϑ,χ)]=ζ2[2csech(cϑ)]α(ζα(ζα))ζ2N[G3ϑ3G2Gϑ3FGϑ+3FϑG]. (5.5)

    By taking the inverse NT, we have that

    F(ϑ,χ)=[c2csech2(cϑ)]N1[α(ζα(ζα))ζ2N{F3ϑ6FFϑ+3GG3ϑ+3GϑG2ϑ3FϑG2+6FGGϑ}],G(ϑ,χ)=[2csech(cϑ)]N1[α(ζα(ζα))ζ2N{G3ϑ3G2Gϑ3FGϑ+3FϑG}]. (5.6)

    Solution for the NDMCF:

    Assume that for the unknown functions F(ϑ,χ) and G(ϑ,χ), the series form solutions are given as

    F(ϑ,χ)=l=0Fl(ϑ,χ)andG(ϑ,χ)=l=0Fl(ϑ,χ). (5.7)

    The nonlinear components in terms of the Adomian polynomials are given as 6FFϑ+3GG3ϑ=m=0Am, 3GϑG2ϑ3FϑG2=m=0Bm, 6FGGϑ=m=0Cm and 3G2Gϑ3FGϑ+3FϑG=m=0Dm. With the help of these terms, Eq (5.6) can be stated as

    l=0Fl+1(ϑ,χ)=c2csech2(cϑ)N1[α(ζα(ζα))ζ2N{F3ϑ+l=0Al+l=0Bl+l=0Cl}],l=0Gl+1(ϑ,χ)=2csech(cϑ)N1[α(ζα(ζα))ζ2N{F3ϑ+l=0Dl}]. (5.8)

    By comparing both sides of Eq (5.8), we have that

    F0(ϑ,χ)=c2csech2(cϑ),G0(ϑ,χ)=2csech(cϑ),
    F1(ϑ,χ)=8c52sinh(cϑ)sech3(cϑ)(α(χ1)+1),G1(ϑ,χ)=4c2sinh(cϑ)sech2(cϑ)(α(χ1)+1), (5.9)
    F2(ϑ,χ)=16c4[2cosh2(cϑ)3]sech4(cϑ)((1α)2+2α(1α)χ+α2χ22),G2(ϑ,χ)=8c72[cosh2(cϑ)2]sech3(cϑ)((1α)2+2α(1α)χ+α2χ22). (5.10)

    In this way, given (l3), the remaining terms for Fl and Gl are easy to get. Thus, the series form solutions are given as

    F(ϑ,χ)=l=0Fl(ϑ,χ)=F0(ϑ,χ)+F1(ϑ,χ)+F2(ϑ,χ)+,F(ϑ,χ)=c2csech2(cϑ)+8c52sinh(cϑ)sech3(cϑ)(α(χ1)+1)16c4[2cosh2(cϑ)3]sech4(cϑ)((1α)2+2α(1α)χ+α2χ22)+,G(ϑ,χ)=l=0Gl(ϑ,χ)=G0(ϑ,χ)+G1(ϑ,χ)+G2(ϑ,χ)+,G(ϑ,χ)=2csech(cϑ)4c2sinh(cϑ)sech2(cϑ)(α(χ1)+1)+8c72[cosh2(cϑ)2]sech3(cϑ)((1α)2+2α(1α)χ+α2χ22)+. (5.11)

    Solution for the NDMABC:

    Assume that for the unknown functions F(ϑ,χ) and G(ϑ,χ), the series form solutions respectively are given as

    F(ϑ,χ)=l=0Fl(ϑ,χ),G(ϑ,χ)=l=0Fl(ϑ,χ). (5.12)

    The nonlinear components in terms of the Adomian polynomials are given as 6FFϑ+3GG3ϑ=m=0Am, 3GϑG2ϑ3FϑG2=m=0Bm, 6FGGϑ=m=0Cm and 3G2Gϑ3FGϑ+3FϑG=m=0Dm. With the help of these terms, Eq (5.6) can be stated as

    l=0Fl+1(ϑ,χ)=c2csech2(cϑ)N1[τα(ζα+α(ταζα))ζ2αN{F3ϑ+l=0Al+l=0Bl+l=0Cl}],l=0Gl+1(ϑ,χ)=2csech(cϑ)N1[τα(ζα+α(ταζα))ζ2αN{F3ϑ+l=0Dl}]. (5.13)

    By comparing both sides of Eq (5.13), we have that

    F0(ϑ,χ)=c2csech2(cϑ),G0(ϑ,χ)=2csech(cϑ),
    F1(ϑ,χ)=8c52sinh(cϑ)sech3(cϑ)(1α+αχαΓ(α+1)),G1(ϑ,χ)=4c2sinh(cϑ)sech2(cϑ)(1α+αχαΓ(α+1)), (5.14)
    F2(ϑ,χ)=16c4[2cosh2(cϑ)3]sech4(cϑ)[α2χ2αΓ(2α+1)+2α(1α)χαΓ(α+1)+(1α)2],G2(ϑ,χ)=8c72[cosh2(cϑ)2]sech3(cϑ)[α2χ2αΓ(2α+1)+2α(1α)χαΓ(α+1)+(1α)2]. (5.15)

    In this way, given (l3), the remaining terms for Fl and Gl are easy to get. Thus, the series form solutions are given as

    F(ϑ,χ)=l=0Fl(ϑ,χ)=F0(ϑ,χ)+F1(ϑ,χ)+F2(ϑ,χ)+,F(ϑ,χ)=c2csech2(cϑ)+8c52sinh(cϑ)sech3(cϑ)(1α+αχαΓ(α+1))16c4[2cosh2(cϑ)3]sech4(cϑ)[α2χ2αΓ(2α+1)+2α(1α)χαΓ(α+1)+(1α)2]+,G(ϑ,χ)=l=0Gl(ϑ,χ)=G0(ϑ,χ)+G1(ϑ,χ)+G2(ϑ,χ)+,G(ϑ,χ)=2csech(cϑ)4c2sinh(cϑ)sech2(cϑ)(1α+αχαΓ(α+1))+8c72[cosh2(cϑ)2]sech3(cϑ)[α2χ2αΓ(2α+1)+2α(1α)χαΓ(α+1)+(1α)2]+. (5.16)

    When α=1, we get the exact solution as

    F(ϑ,χ)=c2csech2(c(ϑ+2cχ)),G(ϑ,χ)=2csech(c(ϑ+2cχ)). (5.17)

    Example 5.2. Let us consider the time-fractional homogeneous two component coupled third order KdV system as

    DαχFF3ϑFFϑGGϑ=0,  χ>0,  ϑR,  0<α1,DαχG+2G3ϑFGϑ=0, (5.18)

    where the initial conditions are as follows:

    F(ϑ,0)=36tanh2(ϑ2),G(ϑ,0)=3c2tanh(ϑ2). (5.19)

    By taking the NT, we get

    N[DαχF(ϑ,χ)]=N[F3ϑFFϑGGϑ],N[DαχG(ϑ,χ)]=N[2G3ϑFGϑ]. (5.20)

    Thus, we have

    1ζαN[F(ϑ,χ)]ζ2αF(ϑ,0)=N[F3ϑFFϑGGϑ],1ζαN[G(ϑ,χ)]ζ2αF(ϑ,0)=N[2G3ϑFGϑ]. (5.21)

    By simplification, we get

    N[F(ϑ,χ)]=ζ2[36tanh2(ϑ2)]α(ζα(ζα))ζ2N[F3ϑFFϑGGϑ],N[G(ϑ,χ)]=ζ2[3c2tanh(ϑ2)]α(ζα(ζα))ζ2N[2G3ϑFGϑ]. (5.22)

    By taking the inverse NT, we have that

    F(ϑ,χ)=36tanh2(ϑ2)N1[α(ζα(ζα))ζ2N{F3ϑFFϑGGϑ}],G(ϑ,χ)=[3c2tanh(ϑ2)]N1[α(ζα(ζα))ζ2N{2G3ϑFGϑ}]. (5.23)

    Solution for the NTDMCF:

    Assume that for the unknown functions F(ϑ,χ) and G(ϑ,χ), the series form solution are given as

    F(ϑ,χ)=l=0Fl(ϑ,χ)andG(ϑ,χ)=l=0Fl(ϑ,χ). (5.24)

    The nonlinear components in terms of the Adomian polynomials are given as FFϑGGϑ=m=0Am and FGϑ=m=0Bm. With the help of these terms, Eq (5.23) can be stated as

    l=0Fl+1(ϑ,χ)=36tanh2(ϑ2)N1[α(ζα(ζα))ζ2N{F3ϑ+l=0Al}],l=0Gl+1(ϑ,χ)=3c2tanh(ϑ2)N1[α(ζα(ζα))ζ2N{2G3ϑl=0Bl}]. (5.25)

    By comparing both sides of Eq (5.25), we have that

    F0(ϑ,χ)=36tanh2(ϑ2),G0(ϑ,χ)=3c2tanh(ϑ2),
    F1(ϑ,χ)=6sech2(ϑ2)tanh(ϑ2)(α(χ1)+1),G1(ϑ,χ)=3c2sech2(ϑ2)tanh(ϑ2)(α(χ1)+1), (5.26)
    F2(ϑ,χ)=3[2+7sech2(ϑ2)15sech4(ϑ2)]sech2(ϑ2)((1α)2+2α(1α)χ+α2χ22),G2(ϑ,χ)=3c22[2+21sech2(ϑ2)24sech4(ϑ2)]sech2(ϑ2)((1α)2+2α(1α)χ+α2χ22). (5.27)

    In this way, given (l3), the remaining terms for Fl and Gl are easy to get. Thus, the series form solutions are given as

    F(ϑ,χ)=l=0Fl(ϑ,χ)=F0(ϑ,χ)+F1(ϑ,χ)+F2(ϑ,χ)+,F(ϑ,χ)=36tanh2(ϑ2)+6sech2(ϑ2)tanh(ϑ2)(α(χ1)+1)+3[2+7sech2(ϑ2)15sech4(ϑ2)]sech2(ϑ2)((1α)2+2α(1α)χ+α2χ22)+,G(ϑ,χ)=l=0Gl(ϑ,χ)=G0(ϑ,χ)+G1(ϑ,χ)+G2(ϑ,χ)+,G(ϑ,χ)=3c2tanh(ϑ2)+3c2sech2(ϑ2)tanh(ϑ2)(α(χ1)+1)+3c22[2+21sech2(ϑ2)24sech4(ϑ2)]sech2(ϑ2)((1α)2+2α(1α)χ+α2χ22)+. (5.28)

    Solution for the NTDMABC:

    Assume that for the unknown functions F(ϑ,χ) and G(ϑ,χ), the series form solutions are given as

    F(ϑ,χ)=l=0Fl(ϑ,χ),G(ϑ,χ)=l=0Fl(ϑ,χ). (5.29)

    The nonlinear components in terms of the Adomian polynomials are given as FFϑGGϑ=m=0Am and FGϑ=m=0Bm. Given these terms, Eq (5.23) can be stated as

    l=0Fl+1(ϑ,χ)=36tanh2(ϑ2)+N1[τα(ζα+α(ταζα))ζ2αN{F3ϑ+l=0Al}],l=0Gl+1(ϑ,χ)=3c2tanh(ϑ2)+N1[τα(ζα+α(ταζα))ζ2αN{2G3ϑl=0Bl}]. (5.30)

    By comparing both sides of Eq (5.30), we have that

    F0(ϑ,χ)=36tanh2(ϑ2),G0(ϑ,χ)=3c2tanh(ϑ2),
    F1(ϑ,χ)=6sech2(ϑ2)tanh(ϑ2)(1α+αχαΓ(α+1)),G1(ϑ,χ)=3c2sech2(ϑ2)tanh(ϑ2)(1α+αχαΓ(α+1)), (5.31)
    F2(ϑ,χ)=3[2+7sech2(ϑ2)15sech4(ϑ2)]sech2(ϑ2)[α2χ2αΓ(2α+1)+2α(1α)χαΓ(α+1)+(1α)2],G2(ϑ,χ)=3c22[2+21sech2(ϑ2)24sech4(ϑ2)]sech2(ϑ2)[α2χ2αΓ(2α+1)+2α(1α)χαΓ(α+1)+(1α)2]. (5.32)

    In this way, given (l3), the remaining terms for Fl and Gl are easy to get. Thus, the series form solutions are given as

    F(ϑ,χ)=l=0Fl(ϑ,χ)=F0(ϑ,χ)+F1(ϑ,χ)+F2(ϑ,χ)+,F(ϑ,χ)=36tanh2(ϑ2)+6sech2(ϑ2)tanh(ϑ2)(1α+αχαΓ(α+1))+3[2+7sech2(ϑ2)15sech4(ϑ2)]sech2(ϑ2)[α2χ2αΓ(2α+1)+2α(1α)χαΓ(α+1)+(1α)2]+,G(ϑ,χ)=l=0Gl(ϑ,χ)=G0(ϑ,χ)+G1(ϑ,χ)+G2(ϑ,χ)+,G(ϑ,χ)=3c2tanh(ϑ2)+3c2sech2(ϑ2)tanh(ϑ2)(1α+αχαΓ(α+1))+3c22[2+21sech2(ϑ2)24sech4(ϑ2)]sech2(ϑ2)[α2χ2αΓ(2α+1)+2α(1α)χαΓ(α+1)+(1α)2]+. (5.33)

    When α=1, we get the exact solution as

    F(ϑ,χ)=36tanh2(ϑ+χ2),G(ϑ,χ)=3c2tanh(ϑ+χ2). (5.34)

    In Figure 1, the actual and suggested methods solutions of F(ϑ,χ) are calculated at α=1. Figure 2 gives the graphical layouts of F(ϑ,χ) when α=0.8 and 0.6. In Figure 3, the 2D and 3D behaviors of F(ϑ,χ) for different fractional orders are respectively given. In Figure 4, the actual and suggested methods solutions of G(ϑ,χ) are calculated at α=1. Figure 5 gives the graphical layouts of G(ϑ,χ) when α=0.8 and 0.6. In Figure 6, the 2D and 3D behaviors of G(ϑ,χ) for different fractional orders are respectively given. The graphical layout of Example 5.1 confirms that our solutions are in a strong agreement with the exact solution. Similarly, in Figures 7, the actual and suggested methods solutions of F(ϑ,χ) are respectively presented for α=1. Figures 8 gives the graphical layouts of F(ϑ,χ) when α=0.8 and 0.6, while Figures 9 shows the 2D and 3D behaviors of F(ϑ,χ) for different fractional orders, respectively. Also, in Figures 10, the actual and suggested methods solutions of G(ϑ,χ) are respectively presented for α=1. Figures 11 gives the graphical layouts of G(ϑ,χ) when α=0.8 and 0.6, while Figures 12 shows the 2D and 3D behaviors of G(ϑ,χ) for different fractional orders, respectively. In the same way, the graphical layout of Example 5.2 confirms that our solutions are in a strong agreement with the exact solution. All the figures have been drawn at c = 0.1 and χ=0.01 within the domain 5ϑ5. Furthermore, Tables 1 and 2 shows the approximate solution of Example 5.1 at different values of ϑ and χ. Tables 3 and 4 show a numerical comparison of the reduced differential transform method and proposed method in terms of the absolute error for Example 5.1. Finally, Tables 5 and 6 show the approximate solution of Example 5.2 at different values of ϑ and χ. From the figures and tables, it can be observed that our methods solution and the exact solution are very close to each other and possess a higher degree of accuracy.

    Figure 1.  Exact and proposed method solution at α=1 for Example 5.1.
    Figure 2.  Proposed method solution at α=0.8,0.6 for Example 5.1.
    Figure 3.  Proposed method solution at different values of α for Example 5.1.
    Figure 4.  Exact and proposed method solution at α=1 for Example 5.1.
    Figure 5.  Proposed method solution at α=0.8,0.6 for Example 5.1.
    Figure 6.  Proposed method solution at different values of α for Example 5.1.
    Figure 7.  Exact and proposed method solution at α=1 for Example 5.2.
    Figure 8.  Proposed method solution at α=0.8,0.6 for Example 5.2.
    Figure 9.  Proposed method solution at different values of α for Example 5.2.
    Figure 10.  Exact and proposed method solution at α=1 for Example 5.2.
    Figure 11.  Proposed method solution at α=0.8,0.6 for Example 5.2.
    Figure 12.  Proposed method solution at different values of α for Example 5.2.
    Table 1.  For Example 5.1, the suggested technique solution for F(ϑ,χ) given c = 0.1 at various fractional orders.
    (ϑ,χ) (NTDMABC) at α= 0.5 (NTDMCF) at α= 0.75 (NTDMABC) at α= 1 (NTDMCF) at α= 1 Exact result
    (0.2, 0.01) -0.099152 -0.099184 -0.099200 -0.099200 -0.099200
    (0.4, 0.02) -0.096736 -0.096799 -0.096830 -0.096830 -0.096830
    (0.6, 0.03) -0.092826 -0.092918 -0.092964 -0.092964 -0.092964
    (0.2, 0.01) -0.099150 -0.099182 -0.099198 -0.099198 -0.099198
    (0.4, 0.02) -0.096732 -0.096795 -0.096827 -0.096827 -0.096827
    (0.6, 0.03) -0.092821 -0.092913 -0.092960 -0.092960 -0.092960
    (0.2, 0.01) -0.099148 -0.099181 -0.099197 -0.099197 -0.099197
    (0.4, 0.02) -0.096728 -0.096792 -0.096824 -0.096824 -0.096824
    (0.6, 0.03) -0.092815 -0.092909 -0.092955 -0.092955 -0.092955
    (0.2, 0.01) -0.099147 -0.099179 -0.099195 -0.099195 -0.099195
    (0.4, 0.02) -0.096725 -0.096789 -0.096821 -0.096821 -0.096821
    (0.6, 0.03) -0.092810 -0.092904 -0.092951 -0.092951 -0.092951
    (0.2, 0.01) -0.099145 -0.099177 -0.099194 -0.099194 -0.099194
    (0.4, 0.02) -0.096721 -0.096786 -0.096818 -0.096818 -0.096818
    (0.6, 0.03) -0.092805 -0.092899 -0.092946 -0.092946 -0.092946

     | Show Table
    DownLoad: CSV
    Table 2.  For Example 5.1, the suggested technique solution for G(ϑ,χ) given c = 0.1 at various fractional orders.
    (ϑ,χ) (NTDMABC) at α=0.5 (NTDMCF) at α=0.75 (NTDMABC) at α= 1 (NTDMCF) at α= 1 Exact result
    (0.2, 0.01) 0.631114 0.631164 0.631190 0.631190 0.631190
    (0.4, 0.02) 0.627273 0.627374 0.627424 0.627424 0.627424
    (0.6, 0.03) 0.621009 0.621158 0.621232 0.621232 0.621232
    (0.2, 0.01) 0.631111 0.631162 0.631187 0.631187 0.631187
    (0.4, 0.02) 0.627267 0.627368 0.627419 0.627419 0.627419
    (0.6, 0.03) 0.621001 0.621150 0.621224 0.621224 0.621224
    (0.2, 0.01) 0.631108 0.631159 0.631185 0.631185 0.631185
    (0.4, 0.02) 0.627262 0.627363 0.627414 0.627414 0.627414
    (0.6, 0.03) 0.620992 0.621142 0.621217 0.621217 0.621217
    (0.2, 0.01) 0.631105 0.631156 0.631182 0.631182 0.631182
    (0.4, 0.02) 0.627256 0.627358 0.627409 0.627409 0.627409
    (0.6, 0.03) 0.620984 0.621135 0.621210 0.621210 0.621210
    (0.2, 0.01) 0.631102 0.631154 0.631180 0.631180 0.631180
    (0.4, 0.02) 0.627250 0.627353 0.627404 0.627404 0.627404
    (0.6, 0.03) 0.620976 0.621127 0.621202 0.621202 0.621202

     | Show Table
    DownLoad: CSV
    Table 3.  For Example 5.1, the suggested technique absolute error comparison with a reduced differential transform method (RDTM) for F(ϑ,χ) at c = 1.
    χ ϑ |RDTM| |NTDMCF| |NTDMCF|
    -2 9.00000000E-09 8.5920000000E-09 8.5920000000E-09
    -1 2.22440000E-06 1.3071200000E-08 1.3071200000E-08
    0.05 0 7.51000000E-07 2.0000000000E-08 2.0000000000E-08
    1 2.29510000E-06 1.2990800000E-07 1.2990800000E-07
    2 2.77000000E-08 7.9080000000E-08 7.9080000000E-08
    -2 7.14000000E-08 3.5763000000E-09 3.5763000000E-09
    -1 6.89230000E-05 5.2446300000E-08 5.2446300000E-08
    0.1 0 4.73670000E-05 7.9998000000E-07 7.9998000000E-07
    1 7.35887000E-05 5.1802700000E-08 5.1802700000E-08
    2 1.11602000E-06 3.0257000000E-07 3.0257000000E-07
    -2 3.75120000E-06 8.3575000000E-08 8.3575000000E-08
    -1 4.99186000E-04 1.1836350000E-07 1.1836350000E-07
    0.15 0 5.26076000E-04 1.7998900000E-07 1.7998900000E-07
    1 5.56398000E-04 1.1619250000E-06 1.1619250000E-06
    2 9.98978000E-06 6.5015000000E-08 6.5015000000E-08

     | Show Table
    DownLoad: CSV
    Table 4.  For Example 5.1, the suggested technique absolute error comparison for G(ϑ,χ) at c = 1.
    χ ϑ |RDTM| |NTDMCF| |NTDMCF|
    -2 1.1860000E-07 9.8320000000E-09 9.8320000000E-09
    -1 2.1200000E-07 2.4506000000E-08 2.4506000000E-08
    0.05 0 1.6800000E-07 3.1623000000E-08 3.1623000000E-08
    1 2.8200000E-07 2.4420000000E-09 2.4420000000E-09
    2 1.0710000E-07 9.7370000000E-08 9.7370000000E-08
    -2 4.0069000E-06 3.9524000000E-08 3.9524000000E-08
    -1 5.3900000E-06 9.8199000000E-07 9.8199000000E-07
    0.1 0 1.0671000E-05 1.2648900000E-08 1.2648900000E-08
    1 9.8860000E-06 9.7508000000E-08 9.7508000000E-08
    2 3.2565000E-06 3.8752000000E-07 3.8752000000E-07
    -2 3.2082600E-05 8.9365000000E-08 8.9365000000E-08
    -1 2.8970000E-05 2.2133100000E-07 2.2133100000E-07
    0.15 0 1.1917600E-04 2.8459400000E-07 2.8459400000E-07
    1 8.0549000E-05 2.1900500000E-07 2.1900500000E-07
    2 2.3525200E-05 8.6759000000E-06 8.6759000000E-06

     | Show Table
    DownLoad: CSV
    Table 5.  For Example 5.2, the suggested technique solution for F(ϑ,χ) given c = 0.1 at various fractional orders.
    (ϑ,χ) (NTDMABC) at α=0.5 (NTDMCF) at α=0.75 (NTDMABC) at α= 1 (NTDMCF) at α= 1 Exact result
    (0.2, 0.01) 2.952239 2.946318 2.940397 2.940397 2.940397
    (0.4, 0.01) 2.789020 2.777639 2.766257 2.766257 2.766257
    (0.6, 0.01) 2.522812 2.506817 2.490821 2.490821 2.490821
    (0.2, 0.02) 2.952239 2.946318 2.940397 2.940397 2.940397
    (0.4, 0.02) 2.789020 2.777639 2.766257 2.766257 2.766257
    (0.6, 0.02) 2.522812 2.506817 2.490821 2.490821 2.490821
    (0.2, 0.03) 2.952239 2.946318 2.940397 2.940397 2.940397
    (0.4, 0.03) 2.789020 2.777639 2.766257 2.766257 2.766257
    (0.6, 0.03) 2.522812 2.506817 2.490821 2.490821 2.490821
    (0.2, 0.04) 2.952239 2.946318 2.940397 2.940397 2.940397
    (0.4, 0.04) 2.789020 2.777639 2.766257 2.766257 2.766257
    (0.6, 0.04) 2.522812 2.506817 2.490821 2.490821 2.490821
    (0.2, 0.05) 2.952239 2.946318 2.940397 2.940397 2.940397
    (0.4, 0.05) 2.789020 2.777639 2.766257 2.766257 2.766257
    (0.6, 0.05) 2.522812 2.506817 2.490821 2.490821 2.490821

     | Show Table
    DownLoad: CSV
    Table 6.  For Example 5.2, the suggested technique solution for G(ϑ,χ) given c=0.1 at various fractional orders.
    (ϑ,χ) (NTDMABC) at α=0.5 (NTDMCF) at α=0.75 (NTDMABC) at α= 1 (NTDMCF) at α= 1 Exact result
    (0.2,0.01) -0.000410 -0.000418 -0.000422 -0.000422 -0.000422
    (0.4,0.01) -0.000813 -0.000829 -0.000837 -0.000837 -0.000837
    (0.6,0.01) -0.001202 -0.001224 -0.001235 -0.001235 -0.001235
    (0.2,0.02) -0.000410 -0.000418 -0.000422 -0.000422 -0.000422
    (0.4,0.02) -0.000813 -0.000829 -0.000837 -0.000837 -0.000837
    (0.6,0.02) -0.001201 -0.001224 -0.001235 -0.001235 -0.001235
    (0.2,0.03) -0.000410 -0.000418 -0.000422 -0.000422 -0.000422
    (0.4,0.03) -0.000813 -0.000829 -0.000837 -0.000837 -0.000837
    (0.6,0.03) -0.001201 -0.001224 -0.001235 -0.001235 -0.001235
    (0.2,0.04) -0.000410 -0.000418 -0.000422 -0.000422 -0.000422
    (0.4,0.04) -0.000813 -0.000829 -0.000837 -0.000837 -0.000837
    (0.6,0.04) -0.001201 -0.001224 -0.001235 -0.001235 -0.001235
    (0.2,0.05) -0.000410 -0.000418 -0.000422 -0.000422 -0.000422
    (0.4,0.05) -0.000813 -0.000829 -0.000837 -0.000837 -0.000837
    (0.6,0.05) -0.001201 -0.001224 -0.001235 -0.001235 -0.001235

     | Show Table
    DownLoad: CSV

    The main goal of this work as to develop a fractional-order Kersten-Krasil' shchik coupled KdV-mKdV nonlinear system approximate analytical solution. Using the NDM, we were able to achieve this goal. The numerical solutions can be achieved in two steps. The targeted problems were first simplified using the NT; then, the decomposition approach was employed to get the solutions. The method's fundamental benefit is that it gives the user an analytical approximation, and in many cases an exact solution, in a quickly converging sequence with elegantly computed terms. The suggested method has been applied to obtain the solution of the given two problems. The method's small computational size in comparison to the computational size required by other numerical methods, as well as its rapid convergence, demonstrate that it is reliable and a significant improvement on existing methods in terms of solving the generalized Kersten-Krasil' shchik coupled KdV-mKdV equation. The results we obtained have been illustrated with the help of plots and tables which confirm the validity of the proposed method. Furthermore, the proposed method is simple, straightforward, and requires minimal computational time; it may also be extended to solve other fractional-order partial differential equations.

    This research received funding support from the NSRF via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation.

    The authors declare that they have no competing interests.



    [1] S. Browne, Optimal investment policies for a firm with a random risk process: exponential utility and minimizing the probability of ruin, Math. Oper. Res., 20 (1995), 937–958. https://doi.org/10.1287/moor.20.4.937 doi: 10.1287/moor.20.4.937
    [2] J. C. Cox, S. A. Ross, The valuation of options for alternative stochastic processes, J. Financ. Econ., 3 (1976), 145–166. https://doi.org/10.1016/0304-405x(76)90023-4 doi: 10.1016/0304-405x(76)90023-4
    [3] S. Asmussen, M. Taksar, Controlled diffusion models for optimal dividend pay-out, Insur. Math. Econ., 20 (1997), 1–15. https://doi.org/10.1016/s0167-6687(96)00017-0 doi: 10.1016/s0167-6687(96)00017-0
    [4] M. I. Taksar, Optimal risk and dividend distribution control models for an insurance company, Math. Method. Oper. Res., 51 (2000), 1–42. https://doi.org/10.1007/s001860050001 doi: 10.1007/s001860050001
    [5] L. Bai, J. Guo, Optimal proportional reinsurance and investment with multiple risky assets and no-shorting constraint, Insur. Math. Econ., 42 (2008), 968–975. https://doi.org/10.1016/j.insmatheco.2007.11.002 doi: 10.1016/j.insmatheco.2007.11.002
    [6] Z. Sun, K. C. Yuen, J. Guo, A BSDE approach to a class of dependent risk model of mean-variance insurers with stochastic volatility and no-short selling, J. Comput. Appl. Math., 366 (2020), 112413. https://doi.org/10.1016/j.cam.2019.112413 doi: 10.1016/j.cam.2019.112413
    [7] A. Gu, X. Guo, Z. Li, Y. Zeng, Optimal control of excess-of-loss reinsurance and investment for insurers under a CEV model, Insur. Math. Econ., 51 (2012), 674–684. https://doi.org/10.1016/j.insmatheco.2012.09.003 doi: 10.1016/j.insmatheco.2012.09.003
    [8] J. Cao, D. Landriault, B. Li, Optimal reinsurance-investment strategy for a dynamic contagion claim model, Insur. Math. Econ., 93 (2020), 206–215. https://doi.org/10.1016/j.insmatheco.2020.04.013 doi: 10.1016/j.insmatheco.2020.04.013
    [9] X. Jiang, K. C. Yuen, M. Chen, Optimal investment and reinsurance with premium control, J. Ind. Manag. Optim., 16 (2020), 2781–2797. https://doi.org/10.3934/jimo.2019080 doi: 10.3934/jimo.2019080
    [10] L. Xu, D. Yao, G. Cheng, Optimal investment and dividend for an insurer under a Markov regime switching market with high gain tax, J. Ind. Manag. Optim., 16 (2020), 325–356. https://doi.org/10.3934/jimo.2018154 doi: 10.3934/jimo.2018154
    [11] Y. Zhang, P. Zhao, B. Kou, Optimal excess-of-loss reinsurance and investment problem with thinning dependent risks under Heston model, J. Comput. Appl. Math., 382 (2021), 113082. https://doi.org/10.1016/j.cam.2020.113082 doi: 10.1016/j.cam.2020.113082
    [12] Z. Sun, X. Zhang, K. C. Yuen, Mean-variance asset-liability management with affine diffusion factor process and a reinsurance option, Scand. Actuar. J., 2020 (2020), 218–244. https://doi.org/10.1080/03461238.2019.1658619 doi: 10.1080/03461238.2019.1658619
    [13] M. Chen, K. C. Yuen, W. Wang, Optimal reinsurance and dividends with transaction costs and taxes under thinning structure, Scand. Actuar. J., 2021 (2021), 198–217. https://doi.org/10.1080/03461238.2020.1824158 doi: 10.1080/03461238.2020.1824158
    [14] M. Kaluszka, Optimal reinsurance under mean-variance premium principles, Insur. Math. Econ., 28 (2001), 61–67. https://doi.org/10.1016/s0167-6687(00)00066-4 doi: 10.1016/s0167-6687(00)00066-4
    [15] M. Kaluszka, Mean-variance optimal reinsurance arrangements, Scand. Actuar. J., 2004 (2004), 28–41. https://doi.org/10.1080/03461230410019222 doi: 10.1080/03461230410019222
    [16] Z. Liang, K. C. Yuen, Optimal dynamic reinsurance with dependent risks: variance premium principle, Scand. Actuar. J., 2016 (2016), 18–36. https://doi.org/10.1080/03461238.2014.892899 doi: 10.1080/03461238.2014.892899
    [17] X. Zhang, H. Meng, Y. Zeng, Optimal investment and reinsurance strategies for insurers with generalized mean-variance premium principle and no-short selling, Insur. Math. Econ., 67 (2016), 125–132. https://doi.org/10.1016/j.insmatheco.2016.01.001 doi: 10.1016/j.insmatheco.2016.01.001
    [18] X. Liang, Z. Liang, V. R. Young, Optimal reinsurance under the mean-variance premium principle to minimize the probability of ruin, Insur. Math. Econ., 92 (2020), 128–146. https://doi.org/10.1016/j.insmatheco.2020.03.008 doi: 10.1016/j.insmatheco.2020.03.008
    [19] K. Borch, Reciprocal reinsurance treaties, ASTIN Bulletin: The Journal of the IAA, 1 (1960), 170–191. https://doi.org/10.1017/s0515036100009557 doi: 10.1017/s0515036100009557
    [20] V. K. Kaishev, Optimal retention levels, given the joint survival of cedent and reinsurer, Scand. Actuar. J., 2004 (2004), 401–430. https://doi.org/10.1080/03461230410020437 doi: 10.1080/03461230410020437
    [21] V. K. Kaishev, D. S. Dimitrova, Excess of loss reinsurance under joint survival optimality, Insur. Math. Econ., 39 (2006), 376–389. https://doi.org/10.1016/j.insmatheco.2006.05.005 doi: 10.1016/j.insmatheco.2006.05.005
    [22] J. Cai, Y. Fang, Z. Li, G. E. Willmot, Optimal reciprocal reinsurance treaties under the joint survival probability and the joint profitable probability, J. Risk. Insur., 80 (2013), 145–168. https://doi.org/10.1111/j.1539-6975.2012.01462.x doi: 10.1111/j.1539-6975.2012.01462.x
    [23] D. Li, X. Rong, H. Zhao, Optimal reinsurance-investment problem for maximizing the product of the insurer's and the reinsurer's utilities under a CEV model, J. Comput. Appl. Math., 255 (2014), 671–683. https://doi.org/10.1016/j.cam.2013.06.033 doi: 10.1016/j.cam.2013.06.033
    [24] D. Li, X. Rong, H. Zhao, Time-consistent reinsurance-investment strategy for an insurer and a reinsurer with mean-variance criterion under the CEV model, J. Comput. Appl. Math., 283 (2015), 142–162. https://doi.org/10.1016/j.cam.2015.01.038 doi: 10.1016/j.cam.2015.01.038
    [25] H. Zhao, C. Weng, Y. Shen, Y. Zeng, Time-consistent investment-reinsurance strategies towards joint interests of the insurer and the reinsurer under CEV models, Sci. China Math., 60 (2017), 317–344. https://doi.org/10.1007/s11425-015-0542-7 doi: 10.1007/s11425-015-0542-7
    [26] N. Zhang, Z. Jin, L. Qian, R. Wang, Optimal quota-share reinsurance based on the mutual benefit of insurer and reinsurer, J. Comput. Appl. Math., 342 (2018), 337–351. https://doi.org/10.1016/j.cam.2018.04.030 doi: 10.1016/j.cam.2018.04.030
    [27] Y. Bai, Z. Zhou, R. Gao, H. Xiao, Nash equilibrium investment-reinsurance strategies for an insurer and a reinsurer with intertemporal restrictions and common interests, Mathematics, 8 (2020), 139. https://doi.org/10.3390/math8010139 doi: 10.3390/math8010139
    [28] Y. Huang, Y. Ouyang, L. Tang, J. Zhou, Robust optimal investment and reinsurance problem for the product of the insurer's and the reinsurer's utilities, J. Comput. Appl. Math., 344 (2018), 532–552. https://doi.org/10.1016/j.cam.2018.05.060 doi: 10.1016/j.cam.2018.05.060
    [29] J. Grandell, Aspects of risk theory, New York: Springer, 1991. https://doi.org/10.1007/978-1-4613-9058-9
    [30] T. S. Ferguson, Betting systems which minimize the probability of ruin, J. Soc. Indust. Appl. Math., 13 (1965), 795–818. https://doi.org/10.1137/0113051 doi: 10.1137/0113051
    [31] H. U. Gerber, An introduction to mathematical risk theory, New York: R. D. Irwin, 1979.
    [32] W. H. Fleming, H. M. Soner, Controlled Markov processes and viscosity solutions, 2 Eds., New York: Springer, 2006. https://doi.org/10.1007/0-387-31071-1
    [33] X. Zeng, M. Taksar, A stochastic volatility model and optimal portfolio selection, Quant. Financ., 13 (2013), 1547–1558. https://doi.org/10.1080/14697688.2012.740568 doi: 10.1080/14697688.2012.740568
  • This article has been cited by:

    1. Muhammad Naeem, Humaira Yasmin, Nehad Ali Shah, Jeevan Kafle, Kamsing Nonlaopon, Analytical Approaches for Approximate Solution of the Time-Fractional Coupled Schrödinger–KdV Equation, 2022, 14, 2073-8994, 2602, 10.3390/sym14122602
    2. Naveed Iqbal, Muhammad Tajammal Chughtai, Roman Ullah, Fractional Study of the Non-Linear Burgers’ Equations via a Semi-Analytical Technique, 2023, 7, 2504-3110, 103, 10.3390/fractalfract7020103
    3. Meshari Alesemi, Jameelah S. Al Shahrani, Naveed Iqbal, Rasool Shah, Kamsing Nonlaopon, Analysis and Numerical Simulation of System of Fractional Partial Differential Equations with Non-Singular Kernel Operators, 2023, 15, 2073-8994, 233, 10.3390/sym15010233
    4. M. Mossa Al-Sawalha, Rasool Shah, Kamsing Nonlaopon, Osama Y. Ababneh, Numerical investigation of fractional-order wave-like equation, 2022, 8, 2473-6988, 5281, 10.3934/math.2023265
    5. M. Mossa Al-Sawalha, Osama Y. Ababneh, Rasool Shah, Amjad khan, Kamsing Nonlaopon, Numerical analysis of fractional-order Whitham-Broer-Kaup equations with non-singular kernel operators, 2022, 8, 2473-6988, 2308, 10.3934/math.2023120
    6. Naveed Iqbal, Imran Khan, Rasool Shah, Kamsing Nonlaopon, The fuzzy fractional acoustic waves model in terms of the Caputo-Fabrizio operator, 2023, 8, 2473-6988, 1770, 10.3934/math.2023091
    7. Aliyu Muhammed Awwal, Adamu Ishaku, Abubakar Sani Halilu, Predrag S. Stanimirović, Nuttapol Pakkaranang, Bancha Panyanak, Descent Derivative-Free Method Involving Symmetric Rank-One Update for Solving Convex Constrained Nonlinear Monotone Equations and Application to Image Recovery, 2022, 14, 2073-8994, 2375, 10.3390/sym14112375
    8. Sultan Alyobi, Rasool Shah, Adnan Khan, Nehad Ali Shah, Kamsing Nonlaopon, Fractional Analysis of Nonlinear Boussinesq Equation under Atangana–Baleanu–Caputo Operator, 2022, 14, 2073-8994, 2417, 10.3390/sym14112417
    9. Haifa A. Alyousef, Rasool Shah, Kamsing Nonlaopon, Lamiaa S. El-Sherif, Samir A. El-Tantawy, An Efficient Analytical Method for Analyzing the Nonlinear Fractional Klein–Fock–Gordon Equations, 2022, 14, 2073-8994, 2640, 10.3390/sym14122640
    10. Muhammad Naeem, Humaira Yasmin, Rasool Shah, Nehad Ali Shah, Jae Dong Chung, A Comparative Study of Fractional Partial Differential Equations with the Help of Yang Transform, 2023, 15, 2073-8994, 146, 10.3390/sym15010146
    11. Thongchai Botmart, Badriah Alotaibi, Rasool Shah, Lamiaa El-Sherif, Samir El-Tantawy, A Reliable Way to Deal with the Coupled Fractional Korteweg-De Vries Equations within the Caputo Operator, 2022, 14, 2073-8994, 2452, 10.3390/sym14112452
    12. Aisha Abdullah Alderremy, Rasool Shah, Naveed Iqbal, Shaban Aly, Kamsing Nonlaopon, Fractional Series Solution Construction for Nonlinear Fractional Reaction-Diffusion Brusselator Model Utilizing Laplace Residual Power Series, 2022, 14, 2073-8994, 1944, 10.3390/sym14091944
    13. Fatemah Mofarreh, Asfandyar Khan, Rasool Shah, Alrazi Abdeljabbar, A Comparative Analysis of Fractional-Order Fokker–Planck Equation, 2023, 15, 2073-8994, 430, 10.3390/sym15020430
    14. Badriah M. Alotaibi, Rasool Shah, Kamsing Nonlaopon, Sherif. M. E. Ismaeel, Samir A. El-Tantawy, Investigation of the Time-Fractional Generalized Burgers–Fisher Equation via Novel Techniques, 2022, 15, 2073-8994, 108, 10.3390/sym15010108
    15. Saleh Alshammari, M. Mossa Al-Sawalha, Rasool Shah, Approximate Analytical Methods for a Fractional-Order Nonlinear System of Jaulent–Miodek Equation with Energy-Dependent Schrödinger Potential, 2023, 7, 2504-3110, 140, 10.3390/fractalfract7020140
    16. Haifa A. Alyousef, Rasool Shah, Nehad Ali Shah, Jae Dong Chung, Sherif M. E. Ismaeel, Samir A. El-Tantawy, The Fractional Analysis of a Nonlinear mKdV Equation with Caputo Operator, 2023, 7, 2504-3110, 259, 10.3390/fractalfract7030259
    17. Dowlath Fathima, Reham A. Alahmadi, Adnan Khan, Afroza Akhter, Abdul Hamid Ganie, An Efficient Analytical Approach to Investigate Fractional Caudrey–Dodd–Gibbon Equations with Non-Singular Kernel Derivatives, 2023, 15, 2073-8994, 850, 10.3390/sym15040850
    18. Naveed Iqbal, Muhammad Tajammal Chughtai, Nehad Ali Shah, Numerical simulation of fractional-order two-dimensional Helmholtz equations, 2023, 8, 2473-6988, 13205, 10.3934/math.2023667
    19. Waleed Hamali, Abdulah A. Alghamdi, Exact solutions to the fractional nonlinear phenomena in fluid dynamics via the Riccati-Bernoulli sub-ODE method, 2024, 9, 2473-6988, 31142, 10.3934/math.20241501
    20. Saima Noor, Wedad Albalawi, Rasool Shah, M. Mossa Al-Sawalha, Sherif M. E. Ismaeel, Mathematical frameworks for investigating fractional nonlinear coupled Korteweg-de Vries and Burger’s equations, 2024, 12, 2296-424X, 10.3389/fphy.2024.1374452
    21. Humaira Yasmin, Haifa A. Alyousef, Sadia Asad, Imran Khan, R. T. Matoog, S. A. El-Tantawy, The Riccati-Bernoulli sub-optimal differential equation method for analyzing the fractional Dullin-Gottwald-Holm equation and modeling nonlinear waves in fluid mediums, 2024, 9, 2473-6988, 16146, 10.3934/math.2024781
    22. Abdulah A. Alghamdi, Analytical discovery of dark soliton lattices in (2+1)-dimensional generalized fractional Kundu-Mukherjee-Naskar equation, 2024, 9, 2473-6988, 23100, 10.3934/math.20241123
    23. Abdul Hamid Ganie, Fatemah Mofarreh, Adnan Khan, A Fractional Analysis of Zakharov–Kuznetsov Equations with the Liouville–Caputo Operator, 2023, 12, 2075-1680, 609, 10.3390/axioms12060609
    24. Noorah Mshary, Exploration of nonlinear traveling wave phenomena in quintic conformable Benney-Lin equation within a liquid film, 2024, 9, 2473-6988, 11051, 10.3934/math.2024542
    25. Khudhayr A. Rashedi, Saima Noor, Tariq S. Alshammari, Imran Khan, Lump and kink soliton phenomena of Vakhnenko equation, 2024, 9, 2473-6988, 21079, 10.3934/math.20241024
    26. Meshari Alesemi, Innovative approaches of a time-fractional system of Boussinesq equations within a Mohand transform, 2024, 9, 2473-6988, 29269, 10.3934/math.20241419
    27. Alexander J. Zaslavski, Special Issue: Nonlinear Analysis and Its Applications in Symmetry II, 2024, 16, 2073-8994, 1409, 10.3390/sym16111409
    28. Elkhateeb Sobhy Aly, Manoj Singh, Mohammed Ali Aiyashi, Mohammed Daher Albalwi, Modeling monkeypox virus transmission: Stability analysis and comparison of analytical techniques, 2024, 22, 2391-5471, 10.1515/phys-2024-0056
    29. Abdulrahman B. M. Alzahrani, Ghadah Alhawael, Novel Computations of the Time-Fractional Coupled Korteweg–de Vries Equations via Non-Singular Kernel Operators in Terms of the Natural Transform, 2023, 15, 2073-8994, 2010, 10.3390/sym15112010
    30. Azzh Saad Alshehry, Humaira Yasmin, Ahmed A. Khammash, Rasool Shah, Numerical analysis of dengue transmission model using Caputo–Fabrizio fractional derivative, 2024, 22, 2391-5471, 10.1515/phys-2023-0169
    31. Mashael M. AlBaidani, Abdul Hamid Ganie, Adnan Khan, The dynamics of fractional KdV type equations occurring in magneto-acoustic waves through non-singular kernel derivatives, 2023, 13, 2158-3226, 10.1063/5.0176042
    32. Nader Al-Rashidi, Innovative approaches to fractional modeling: Aboodh transform for the Keller-Segel equation, 2024, 9, 2473-6988, 14949, 10.3934/math.2024724
    33. Aisha A. Alderremy, Humaira Yasmin, Rasool Shah, Ali M. Mahnashi, Shaban Aly, Numerical simulation and analysis of Airy's-type equation, 2023, 21, 2391-5471, 10.1515/phys-2023-0144
    34. Naveed Iqbal, Wael W. Mohammed, Mohammad Alqudah, Amjad E. Hamza, Shah Hussain, Periodic and Axial Perturbations of Chaotic Solitons in the Realm of Complex Structured Quintic Swift-Hohenberg Equation, 2024, 29, 2297-8747, 86, 10.3390/mca29050086
    35. Waleed Hamali, Abdullah A. Zaagan, Hamad Zogan, Analysis of peakon-like soliton solutions: (3+1)-dimensional Fractional Klein-Gordon equation, 2024, 9, 2473-6988, 14913, 10.3934/math.2024722
    36. Saima Noor, Wedad Albalawi, Rasool Shah, Ahmad Shafee, Sherif M. E. Ismaeel, S. A. El-Tantawy, A comparative analytical investigation for some linear and nonlinear time-fractional partial differential equations in the framework of the Aboodh transformation, 2024, 12, 2296-424X, 10.3389/fphy.2024.1374049
    37. Mohammad Alqudah, Safyan Mukhtar, Haifa A. Alyousef, Sherif M. E. Ismaeel, S. A. El-Tantawy, Fazal Ghani, Probing the diversity of soliton phenomena within conformable Estevez-Mansfield-Clarkson equation in shallow water, 2024, 9, 2473-6988, 21212, 10.3934/math.20241030
    38. Waleed Hamali, Hamad Zogan, Abdulhadi A. Altherwi, Dark and bright hump solitons in the realm of the quintic Benney-Lin equation governing a liquid film, 2024, 9, 2473-6988, 29167, 10.3934/math.20241414
    39. Saima Noor, Wedad Albalawi, Rasool Shah, M. Mossa Al-Sawalha, Sherif M. E. Ismaeel, S. A. El-Tantawy, On the approximations to fractional nonlinear damped Burger’s-type equations that arise in fluids and plasmas using Aboodh residual power series and Aboodh transform iteration methods, 2024, 12, 2296-424X, 10.3389/fphy.2024.1374481
    40. Mohammad Alshammari, Khaled Moaddy, Muhammad Naeem, Zainab Alsheekhhussain, Saleh Alshammari, M. Mossa Al-Sawalha, Solitary and Periodic Wave Solutions of Fractional Zoomeron Equation, 2024, 8, 2504-3110, 222, 10.3390/fractalfract8040222
    41. Mohammad Alqudah, Manoj Singh, Applications of soliton solutions of the two-dimensional nonlinear complex coupled Maccari equations, 2024, 9, 2473-6988, 31636, 10.3934/math.20241521
    42. Aziz El Ghazouani, M’hamed Elomari, Said Melliani, A semi-analytical solution approach for fuzzy fractional acoustic waves equations using the Atangana Baleanu Caputo fractional operator, 2024, 28, 1432-7643, 9307, 10.1007/s00500-024-09857-y
    43. Sultan Alyobi, Mohammed Alharthi, Yasser Alrashedi, Imran Khan, Kink phenomena of the time-space fractional Sharma-Tasso-Olver (STO) equation, 2024, 99, 0031-8949, 095265, 10.1088/1402-4896/ad6f4c
    44. Mubashir Qayyum, Efaza Ahmad, Ali Akgül, Sayed M. El Din, Fuzzy-fractional modeling of Korteweg-de Vries equations in Gaussian-Caputo sense: New solutions via extended He-Mahgoub algorithm, 2024, 15, 20904479, 102623, 10.1016/j.asej.2023.102623
    45. Azzh Saad Alshehry, Safyan Mukhtar, Ali M. Mahnashi, Analytical methods in fractional biological population modeling: Unveiling solitary wave solutions, 2024, 9, 2473-6988, 15966, 10.3934/math.2024773
    46. Musawa Yahya Almusawa, Hassan Almusawa, Dark and bright soliton phenomena of the generalized time-space fractional equation with gas bubbles, 2024, 9, 2473-6988, 30043, 10.3934/math.20241451
    47. Mashael M. AlBaidani, Fahad Aljuaydi, N. S. Alharthi, Adnan Khan, Abdul Hamid Ganie, Study of fractional forced KdV equation with Caputo–Fabrizio and Atangana–Baleanu–Caputo differential operators, 2024, 14, 2158-3226, 10.1063/5.0185670
    48. Abdul Hamid Ganie, Fatemah Mofarreh, N. S. Alharthi, Adnan Khan, Novel computations of the time-fractional chemical Schnakenberg mathematical model via non-singular kernel operators, 2025, 2025, 1687-2770, 10.1186/s13661-024-01979-4
    49. Khudhayr A. Rashedi, Musawa Yahya Almusawa, Hassan Almusawa, Tariq S. Alshammari, Adel Almarashi, Applications of Riccati–Bernoulli and Bäcklund Methods to the Kuralay-II System in Nonlinear Sciences, 2024, 13, 2227-7390, 84, 10.3390/math13010084
    50. Azzh Saad Alshehry, Humaira Yasmin, Ali M. Mahnashi, Exploring fractional Advection-Dispersion equations with computational methods: Caputo operator and Mohand techniques, 2025, 10, 2473-6988, 234, 10.3934/math.2025012
    51. Khudhayr A. Rashedi, Musawa Yahya Almusawa, Hassan Almusawa, Tariq S. Alshammari, Adel Almarashi, Fractional Dynamics: Applications of the Caputo Operator in Solving the Sawada–Kotera and Rosenau–Hyman Equations, 2025, 13, 2227-7390, 193, 10.3390/math13020193
    52. Hussain Gissy, Abdullah Ali H. Ahmadini, Ali H. Hakami, The solitary wave phenomena of the fractional Calogero-Bogoyavlenskii-Schiff equation, 2025, 10, 2473-6988, 420, 10.3934/math.2025020
    53. Nisar Gul, Saima Noor, Abdulkafi Mohammed Saeed, Musaad S. Aldhabani, Roman Ullah, Analytical solution of the systems of nonlinear fractional partial differential equations using conformable Laplace transform iterative method, 2025, 10, 2473-6988, 1945, 10.3934/math.2025091
    54. Mrutyunjaya Sahoo, Dhabaleswar Mohapatra, S. Chakraverty, Wave solution for time fractional geophysical KdV equation in uncertain environment, 2025, 5, 2767-8946, 61, 10.3934/mmc.2025005
    55. Shuai Wang, Ziyang Wang, Wu Xie, Yunfei Qi, Tao Liu, An Accelerated Sixth-Order Procedure to Determine the Matrix Sign Function Computationally, 2025, 13, 2227-7390, 1080, 10.3390/math13071080
    56. M. Mossa Al-Sawalha, Safyan Mukhtar, Azzh Saad Alshehry, Mohammad Alqudah, Musaad S. Aldhabani, Chaotic perturbations of solitons in complex conformable Maccari system, 2025, 10, 2473-6988, 6664, 10.3934/math.2025305
  • Reader Comments
  • © 2023 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(1491) PDF downloads(71) Cited by(2)

Figures and Tables

Figures(9)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog