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Research article Special Issues

Intelligent recommendation algorithm for social networks based on improving a generalized regression neural network

  • Received: 04 March 2024 Revised: 18 June 2024 Accepted: 21 June 2024 Published: 11 July 2024
  • In recent years, the vigorous development of the Internet has led to the exponential growth of network information. The recommendation system can analyze the potential preferences of users according to their historical behavior data and provide personalized recommendations for users. In this study, the social network model was used for modeling, and the recommendation model was improved based on variational modal decomposition and the whale optimization algorithm. The generalized regression neural network structure and joint probability density function were used for sequencing and optimization, and then the genetic bat population optimization algorithm was used to solve the proposed algorithm. An intelligent recommendation algorithm for social networks based on improved generalized regression neural networks (RA-GNN) was proposed. In this study, three kinds of social network data sets obtained by real crawlers were used to solve the proposed RA-GNN algorithm in the real social network data environment. The experimental results showed that the RA-GNN algorithm proposed in this paper could implement efficient and accurate recommendations for social network information.

    Citation: Gongcai Wu. Intelligent recommendation algorithm for social networks based on improving a generalized regression neural network[J]. Electronic Research Archive, 2024, 32(7): 4378-4397. doi: 10.3934/era.2024197

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  • In recent years, the vigorous development of the Internet has led to the exponential growth of network information. The recommendation system can analyze the potential preferences of users according to their historical behavior data and provide personalized recommendations for users. In this study, the social network model was used for modeling, and the recommendation model was improved based on variational modal decomposition and the whale optimization algorithm. The generalized regression neural network structure and joint probability density function were used for sequencing and optimization, and then the genetic bat population optimization algorithm was used to solve the proposed algorithm. An intelligent recommendation algorithm for social networks based on improved generalized regression neural networks (RA-GNN) was proposed. In this study, three kinds of social network data sets obtained by real crawlers were used to solve the proposed RA-GNN algorithm in the real social network data environment. The experimental results showed that the RA-GNN algorithm proposed in this paper could implement efficient and accurate recommendations for social network information.



    Fractional partial differential equations (FPDEs) are the generalizations of classical partial differential equations with integer orders, which are used to describe several phenomena in many fields of sciences, such as mechanics, signal processing, plasma physics, systems identification, electricity, chemistry, biology, control theory and other areas.

    The exact solutions of FPDEs play a crucial role in the study of nonlinear sciences. It is used to describe observed various qualitative and quantitative features of nonlinear phenomenons in many fields of mathematical physics, it can let our better understand some complex physics phenomena. Therefore, it is an important task to seek more exact solutions of different forms for the FPDEs.

    In recent decades, with the development of science and technology, especially symbolic computation package such as Maple and Mathematica, many researchers have presented many direct and powerful approaches to establish exact solutions of fractional partial differential equations. For example, the fractional sub-equation method [1,2], the first integral method [3], the extended fractional Riccati expansion method [4], the fractional complex transform [5], the Jacobi elliptic equation method [6], the fractional mapping method [7], the (G/G)-expansion method [8], the improved fractional (DαG/G) method [9], the extended fractional (DαξG/G)-expansion method [10], the separation variables approach [11], the modified extended tanh method [12], the exp(Φ(ξ)) method [13,14], the invariant subspace method [15], and other methods [16,17,18,19]. Due to these methods, various exact solutions or numerical solutions of FPDEs have been established successfully.

    The two variable (ϕ/ϕ,1/ϕ)-expansion method is the generalization of (G/G)-expansion method, the main idea of this method is that the solutions to FPDEs are represented as a polynomial in two variables (ϕ/ϕ) and (1/ϕ), wherein ϕ=ϕ(ξ) satisfies the second order ODE ϕ+δϕ=μ, where δ and μ are constants. The objective of this article is to establish further general and some fresh close form solitary wave solution to the time-fractional Kuramoto-Sivashinsky (K-S) equation, (3+1)-dimensional time-fractional KdV-Zakharov-Kuznetsov (KdV-ZK) equation and time-fractional Sharma-Tasso-Olver (FSTO) equation by means of the two variable (ϕ/ϕ,1/ϕ)-expansion method, the results suggest that the method is significative and further general.

    The organization of the paper is as follows. In Section 2, the description of conformable fractional derivative and its properties are given. In Section 3, we describe the algorithm for solving time-fractional partial differential equations by using the two variable (ϕ/ϕ,1/ϕ)-expansion method with the help of fractional complex transform. In Section 4, we apply the two variable (ϕ/ϕ,1/ϕ)-expansion to the time-fractional K-S equation, (3+1)-dimensional KdV-ZK equation and FSTO equation. In Section 5, some typical wave figures of the exact solutions are given. Results and discussion part are added in Section 6. The conclusion part is in Section 7.

    In fractional calculus, the most famous fractional derivatives are the Riemann-Liouville and the Caputo fractional derivatives, the Riemann-Liouville fractional derivative is defined as follows [20]:

    If n is a positive integer and αϵ[n1,n], the α derivative of a function f is given by

     Dαt(f)(t)=1Γ(nα)dndtntaf(x)(tx)αn+1dx. (2.1)

    Also, the Caputo fractional derivative is defined as follows [20]

     Dαt(f)(t)=1Γ(nα)dndtntaf(n)(x)(tx)αn+1dx. (2.2)

    Some flaws arise in these definitions of these fractional derivatives, for example, all these derivatives do not satisfy: the known formula of the derivative of the product of two functions, the known formula of the derivative of the quotient of two functions and the chain rule of two functions.

    In 2014, Khalil et al. [21] introduced a novel definition of fractional derivative named the conformable fractional derivative to overcome the flaws found in Riemann-Liouville and the Caupto fractional derivatives.

    Definition 1. Suppose f: [0,)R is a function. Then, the conformable fractional derivative of f of order α is defined as

     Dαt(f)(t)=limϵ0f(t+ϵt1α)f(t)ϵ, (2.3)

    for all t>0 and α(0,1]. If f is α-differentiable in some (0,a), a>0, and limt0+f(α)(t) exists, then f(α)(0)=limt0+f(α)(t).

    Some properties of the conformable fractional derivative are given below as in [21]

    Thereom 1. Suppose α(0,1], and f=f(t) and g=g(t) are αdifferentiable at t>0. Then

     Dαt(af+bg)=aDαt(f)+bDαt(g),     a,bR. (2.4)
     Dαt(tμ)=μtμα,     μR. (2.5)
     Dαt(fg)=fDαt(g)+gDαt(f). (2.6)
     Dαt(fg)=gDαt(f)fDαt(g)g2. (2.7)

    If, in addition to f differentiable, then

     Dαt(f)(t)=t1αdfdt. (2.8)

    Thereom 2. Suppose functions f,g: [0,)R be αdifferentiable, where (0<α1). Then the following rule is obtained

     Dαt(fg)(t)=t1αg(t)f(g(t)). (2.9)

    The above equations play an important role in fractional calculus in the following sections.

    In this section we give the description of the two variable (ϕ/ϕ,1/ϕ)-expansion method to find exact traveling wave solutions of time-fractional partial differential equation.

    Suppose that a time-fractional partial differential equation in the variables x,y,z,t is given by

     P(u,ux,uy,uz,uxx,uxy,uxz,uxxx,,Dαtu,D2αttu,)=0,    0<α1, (3.1)

    where Dαtu,D2αttu are fraction-order derivatives of u with respect to t, P is a polynomial of u=u(x,y,z,t) and its various partial conformable derivatives including the highest order derivatives and nonlinear terms.

    We use the conformable wave transformation:

     u(x,y,z,t)=u(ξ),ξ=c(x+y+zυtαα), (3.2)

    where c and υ are constant to be determine later, the FPDE (3.1) is reduced to the following nonlinear ordinary differential equation (ODE) for u(x,y,z,t)=u(ξ):

     P(u,cu,c2u,c3u,,cυu,)=0, (3.3)

    where u=uξ,u=uξξ,.

    We suppose the solution u of (3.3) can be expressed in the following form:

    u=ni=0ai(ϕϕ)i+n1j=0bi(ϕϕ)j1ϕ, (3.4)

    where ai,bj(i=0,1,2,,n;j=0,1,2,,n1) are constants and anbn10. The positive number n can be determined by considering the homogeneous balance between the highest order derivatives and nonlinear terms appearing in (3.3). The function ϕ=ϕ(ξ) satisfies the second order linear ODE in the form

    ϕ+δϕ=μ, (3.5)

    where δ and μ are constants. Equation (3.5) has three types of general solution with double arbitrary parameters as follows [22]:

     ϕ(ξ)={A1cosh(δξ)+A2sinh(δξ)+μδ, when   δ<0,A1cos(δξ)+A2sin(δξ)+μδ,         when   δ>0,A1ξ+A2+μ2ξ2,                             when   δ=0.  (3.6)

    and

     (ϕϕ)2={(δA21δA22μ2δ)(1ϕ)2δ+2μϕ,   when δ<0,                (δA21+δA22μ2δ)(1ϕ)2δ+2μϕ,   when δ>0,                 (A212μA2)(1ϕ)2+2μϕ,              when δ=0.                  (3.7)

    where A1,A2 are arbitrary constants.

    By substituting (3.4) into (3.3) and using the second order linear ODE (3.5) and (3.7), collecting all terms with the same order of 1ϕi and 1ϕiϕϕ together, the left-hand side of (3.3) is converted into another polynomial in 1ϕi and 1ϕiϕϕ. Equating each coefficient of this different power terms to zero yields a set of algebraic equations for ai,bj(i=0,1,2,,n;j=0,1,2,,n1),δ,μ,c and υ.

    Assuming constants ai,bj(i=0,1,2,,n;j=0,1,2,,n1),δ,μ,c and υ can be determined by solving the nonlinear algebraic equations. Then substituting these terms and the general solutions (3.6) of (3.5) into (3.4), we can obtain more exact traveling wave solutions of (3.1).

    In this subsection, we investigate more general and new exact traveling wave solutions of time-fractional differential equations by means of the two variable (ϕ/ϕ,1/ϕ)-expansion method.

    we consider the time-fractional Kuramoto-Sivashinsky (K-S) equation [23]:

     Dαtu+auux+buxx+kuxxxx=0, (4.1)

    where 0<α1 and a,b,k are arbitrary constants.

    The K-S equation (4.1) was examined as a prototypical example of spatiotemporal chaos in one space dimension. This equation represents the motion of a fluid going down a vertical wall, the variations of the position of a flame front, or a spatially uniform oscillating chemical reaction in a homogeneous medium.

    To solve (4.1), we use the wave transformations:

     u=u(ξ),   ξ=c(xυtαα), (4.2)

    then (4.1) is reduced into a nonlinear ODE in the form

     cυu(ξ)+acu(ξ)u(ξ)+bc2u(ξ)+kc4u(4)(ξ)=0. (4.3)

    By reducing (4.3), we get

     υu(ξ)+au(ξ)u(ξ)+bcu(ξ)+kc3u(4)(ξ)=0. (4.4)

    By balancing the highest order derivative term u(4) and nonlinear term uu in (4.4), the value of n can be determined, which is n=3 in this problem. Therefore, by (3.4), we have the following ansatz:

    u(ξ)=a0+a1(ϕϕ)+a2(ϕϕ)2+a3(ϕϕ)3+b01ϕ+b1(ϕϕ)1ϕ+b2(ϕϕ)21ϕ, (4.5)

    where a0,a1,a2,a3,b0,b1 and b2 are constants to be determined later, and function ϕ(ξ) satisfies (3.5).

    By substituting (4.5) into (4.4) and using the second order linear ODE (3.5) and (3.7), collecting all terms with the same order of 1ϕi and 1ϕiϕϕ together, the left-hand side of (4.4) is converted into another polynomial in 1ϕi and 1ϕiϕϕ. Equating each coefficient of this different power terms to zero yields a set of algebraic equations for a0,a1,a2,a3,b0,b1,b2,δ,μ,k,a,b,c and υ. Solving this system of algebraic equations, with the aid of Maple, we obtain

    1.a1=±3b2δ2Ξi, a2=b2μ2Ξi, a3=±b2Ξi,b0=b2(μ2+Ξiδ)Ξi, b1=3b2μ2Ξi, b=±19b2aδ60cΞi,  
     k=±ab260c3Ξi,  υ=a(b2μδ+2a0Ξi)2Ξi,                                                               (4.6)
    2.a1=±21b2δ22Ξi, a2=b2μ2Ξi, a3=±b2Ξi,b0=b2(11μ2+5Ξiδ)11Ξi,  b1=3b2μ2Ξi,                 
     b=19b2aδ660cΞi,  k=±ab260c3Ξi,  υ=a(b2μδ+2a0Ξi)2Ξi,                                          (4.7)

    where Ξi(i=1,2,3) are given later.

    Substituting (4.6) and (4.7) and the general solutions (3.6) of Eq. (3.5) into (4.5), we obtain more exact traveling wave solutions of (4.1):

    u1i(ξ)=a0±3b2δ2ΞiΦib2μ2ΞiΦ2i±b2ΞiΦ3i+Ψi(b2(μ2+Ξiδ)Ξi3b2μ2ΞiΦi+b2Φ2i), (4.8)

    where ξ=c(x(b2δμ+2a0Ξi)a2Ξiαtα),  b=±19b2aδ60cΞi,  k=±ab260c3Ξi.

    u2i(ξ)=a0±21b2δ22ΞiΦib2μ2ΞiΦ2i±b2ΞiΦ3i+Ψi(b2(11μ2+5Ξiδ)11Ξi3b2μ2ΞiΦi+b2Φ2i), (4.9)

    where ξ=c(x(b2δμ+2a0Ξi)a2Ξiαtα),  b=19b2aδ660cΞi,  k=±ab260c3Ξi.

    When i=1 for δ<0, i=2 for δ>0, i=3 for δ=0. And

    Φ1=A1sinh(δξ)+A2cosh(δξ)A1cosh(δξ)+A2sinh(δξ)+μ/δδ,                          (4.10)
    Ψ1=1A1cosh(δξ)+A2sinh(δξ)+μ/δ,  Ξ1=A21δA22δμ2/δ. (4.11)
    Φ2=A1sin(δξ)+A2cos(δξ)A1cos(δξ)+A2sin(δξ)+μ/δδ,                                     (4.12)
    Ψ2=1A1cos(δξ)+A2sin(δξ)+μ/δ,  Ξ2=A21δ+A22δμ2/δ.         (4.13)
    Φ3=A1+μξA1ξ+A2+μξ2/2, Ψ3=1A1ξ+A2+μξ2/2,  Ξ3=A212A2μ.    (4.14)

    Since A1 and A2 are arbitrary constants, one may choose arbitrarily their values. For example, if we choose A1=0, A20 and μ=0 in (4.8), we obtain some traveling wave solutions.

    Case 1.1 when δ<0, we have

    u1(ξ)=a0+b2δA2(32coth(δξ)coth3(δξ)csch3(δξ)),(A2>0),    (4.15)

    where ξ=c(xa0aαtα),b=19b2aδ60A2cδ,  k=ab260c3A2δ.

    u2(ξ)=a0b2δA2(32coth(δξ)coth3(δξ)+csch3(δξ)),(A2<0),    (4.16)

    where ξ=c(xa0aαtα),b=19b2aδ60A2cδ,  k=ab260c3A2δ.

    Case 1.2 when δ>0, we have

    u3(ξ)=a0+b2δA2(32cot(δξ)+cot3(δξ)+csc3(δξ)),(A2>0),    (4.17)

    where ξ=c(xa0aαtα),b=19b2aδ60A2cδ,  k=ab260c3A2δ.

    u4(ξ)=a0b2δA2(32cot(δξ)+cot3(δξ)csc3(δξ)),(A2<0),    (4.18)

    where ξ=c(xa0aαtα),b=19b2aδ60A2cδ,  k=ab260c3A2δ.

    Again if A2=0, A10 and μ=0 in (4.8), we obtain some traveling wave solutions.

    Case 2.1 when δ<0, we have

    u5(ξ)=a0+b2δδA21δ(32tanh(δξ)tanh3(δξ))+b2δA1sech3(δξ), (4.19)

    where ξ=c(xa0aαtα),b=19b2aδ60cA21δ,  k=ab260c3A21δ.

    Case 2.2 when δ>0, we have

    u6(ξ)=a0b2δA1(32tan(δξ)+tan3(δξ))sec3(δξ)),(A1>0), (4.20)

    where ξ=c(xa0aαtα),b=19b2aδ60cA1δ,  k=ab260c3A1δ.

    u7(ξ)=a0+b2δA1(32tan(δξ)+tan3(δξ))+sec3(δξ)),(A1<0), (4.21)

    where ξ=c(xa0aαtα),b=19b2aδ60cA1δ,  k=ab260c3A1δ.

    If we choose A1=0, A20 and μ=0 in (4.9), we obtain some traveling wave solutions, for example

    Case 3.1 when δ<0, we have

    u8(ξ)=a0+b2δA2(2122coth(δξ)coth3(δξ)+(511coth2(δξ))csch(δξ)),(A2>0),    (4.22)

    where ξ=c(xa0aαtα),b=19b2aδ660A2cδ,  k=ab260c3A2δ.

    u9(ξ)=a0b2δA2(2122coth(δξ)coth3(δξ)(511coth2(δξ))csch(δξ)),(A2<0),    (4.23)

    where ξ=c(xa0aαtα),b=19b2aδ660A2cδ,  k=ab260c3A2δ.

    Case 3.2 when δ>0, we have

    u10(ξ)=a0+b2δA2(2122cot(δξ)+cot3(δξ)+(511+cot2(δξ))csc(δξ)),(A2>0),    (4.24)

    where ξ=c(xa0aαtα),b=19b2aδ660A2cδ,  k=ab260c3A2δ.

    u11(ξ)=a0b2δA2(2122cot(δξ)+cot3(δξ)(511+cot2(δξ))csc(δξ)),(A2<0),    (4.25)

    where ξ=c(xa0aαtα),b=19b2aδ660A2cδ,  k=ab260c3A2δ.

    Again if A2=0, A10 and μ=0 in (4.9), we obtain some traveling wave solutions.

    Case 4.1 when δ<0, we have

    u12(ξ)=a0+b2δδA21δ(2122tanh(δξ)tanh3(δξ))+b2δA1(511tanh2(δξ))sech(δξ), (4.26)

    where ξ=c(xa0aαtα),b=19b2aδ660cA21δ,  k=ab260c3A21δ.

    Case 4.2 when δ>0, we have

    u13(ξ)=a0b2δA1(2122tan(δξ)+tan3(δξ)(511+tan2(δξ))sec(δξ)),(A1>0),    (4.27)

    where ξ=c(xa0aαtα),b=19b2aδ660A1cδ,  k=ab260c3A1δ.

    u14(ξ)=a0+b2δA1(2122tan(δξ)+tan3(δξ)+(511+tan2(δξ))sec(δξ)),(A1<0),    (4.28)

    where ξ=c(xa0aαtα),b=19b2aδ660A1cδ,  k=ab260c3A1δ.

    Consider the (3+1)-dimensional time-fractional KdV-Zakharov-Kuznetsov (KdV-ZK) equation [24,25]:

     Dαtu+auux+uxxx+b(uxyy+uxzz)=0, (4.29)

    where 0<α1 and a,b are arbitrary constants.

    It is well known that the Korteweg-de Vries (KdV) equation arises as an model for one-dimensional long wavelength surface waves propagating in weakly nonlinear dispersive media, as well as the evolution of weakly nonlinear ion acoustic waves in plasmas. The ZK equation is one of two well-studied canonical two-dimensional extensions of the Korteweg-de Vries equation. In recent, S. Shoo et al. [25] found some new exact traveling wave solutions of Eq. (4.29) by the simplest equation method.

    To solve (4.29), we use the wave transformations:

     u=u(ξ),   ξ=c(x+y+zυtαα), (4.30)

    then (4.29) is reduced into a nonlinear ODE in the form

     cυu(ξ)+acu(ξ)u(ξ)+c3(1+2b)u(ξ)=0. (4.31)

    By reducing (4.31), we get

     υu(ξ)+au(ξ)u(ξ)+c2(1+2b)u(ξ)=0. (4.32)

    Further by integrating (4.32) with respect to ξ, we get

     υu(ξ)+a2u2(ξ)+c2(1+2b)u(ξ)=0. (4.33)

    By balancing the highest order derivative term u and nonlinear term u2 in (4.33), the value of n can be determined, which is n=2 in this problem. Therefore, by equation (3.4), we have the following ansatz:

    u(ξ)=a0+a1(ϕϕ)+a2(ϕϕ)2+b01ϕ+b1(ϕϕ)1ϕ, (4.34)

    where a0,a1,a2,b0 and b1 are constants to be determined later, and function ϕ(ξ) satisfies (3.5).

    By substituting (4.34) into (4.33) and using the second order linear ODE (3.5) and (3.7), collecting all terms with the same order of 1ϕi and 1ϕiϕϕ together, the left-hand side of (4.33) is converted into another polynomial in 1ϕi and 1ϕiϕϕ. Equating each coefficient of this different power terms to zero yields a set of algebraic equations for a0,a1,a2,b0,b1,δ,μ,a,b,c and υ. Solving this system of algebraic equations, with the aid of Maple, we obtain

     1.a0=±b1δΞi,  a1=0,  a2=±b1Ξi,  b0=b1μΞi,  b=6c2Ξi±ab112c2Ξi,  υ=±δab16Ξi.   (4.35)
     2.a0=±2b1δ3Ξi,  a1=0,  a2=±b1Ξi,  b0=b1μΞi,  b=6c2Ξi±ab112c2Ξi,  υ=δab16Ξi.   (4.36)

    Substituting (4.35) and (4.36) and the general solutions (3.6) of Eq. (3.5) into (4.34), we obtain more exact solutions of (4.29):

    u1i(ξ)=±b1δΞi±b1ΞiΦ2i+b1Ψi(μΞi+Φi), (4.37)

    where ξ=c(x+y+zδab16Ξiαtα),  b=6c2Ξi±ab112c2Ξi.

    u2i(ξ)=±2b1δ3Ξi±b1ΞiΦ2i+b1Ψi(μΞi+Φi), (4.38)

    where ξ=c(x+y+z±δab16Ξiαtα),  b=6c2Ξi±ab112c2Ξi, in which i=1 for δ<0, i=2 for δ>0, i=3 for δ=0, and Φi,Ψi,Ξi, (i=1,2,3) see (4.10)-(4.14).

    Here A1 and A2 are arbitrary constants. Therefore, one can freely select their values. If we choose A1=0, A20, μ=0 and δ>0 in (4.37), we obtain some traveling wave solutions.

    u1(ξ)=b1δA2(csc2(δξ)+cot(δξ)csc(δξ)),(A2>0),  (4.39)

    where ξ=c(x+y+zδab16A2αδtα),b=6c2A2δ+ab112c2A2δ.

    u2(ξ)=b1δA2(csc2(δξ)cot(δξ)csc(δξ)),(A2<0),  (4.40)

    where ξ=c(x+y+z+δab16A2αδtα),b=6c2A2δ+ab112c2A2δ.

    If we choose A1=0, A20, μ=0 and δ<0 in (4.38), we obtain some other traveling wave solutions.

    u3(ξ)=b1δA2(23coth2(δξ)coth(δξ)csch(δξ)),(A2>0),  (4.41)

    where ξ=c(x+y+z+δab16A2αδtα),b=6c2A2δ+ab112c2A2δ.

    u4(ξ)=b1δA2(23coth2(δξ)+coth(δξ)csch(δξ)),(A2<0),  (4.42)

    where ξ=c(x+y+zδab16A2αδtα),b=6c2A2δ+ab112c2A2δ.

    If we choose A1=0, A20, μ=0 and δ>0 in (4.38), we obtain some traveling wave solutions.

    u5(ξ)=b1δA2(23+cot2(δξ)+cot(δξ)csc(δξ)),(A2>0),  (4.43)

    where ξ=c(x+y+z+δab16A2αδtα),b=6c2A2δ+ab112c2A2δ.

    u6(ξ)=b1δA2(23+cot2(δξ)cot(δξ)csc(δξ)),(A2>0),  (4.44)

    where ξ=c(x+y+zδab16A2αδtα),b=6c2A2δ+ab112c2A2δ.

    Similarly, we can write down the other families of exact solutions of Eq. (4.29) which are omitted for convenience.

    Consider the time-fractional Sharma-Tasso-Olver (FSTO) equation [26,27]:

     Dαtu+3au2x+3au2ux+3auuxx+auxxx=0, (4.45)

    where a is an arbitrary constant and 0<α1. The function u(x,t) is assumed to be a causal function of time. i.e. vanishing for t<0. The general response expression contains a parameter describing the order of the fractional derivative that can be varied to obtain various responses. In the case of α=1, Eq. (4.45) reduces to the classical nonlinear STO equation. L. Song [26] found a rational approximation solution of Eq. (4.45) by the variational iteration method, the Adomian decomposition method and the homotopy perturbation method.

    To solve (4.45), we use the wave transformations:

     u=u(ξ),   ξ=c(xυtαα), (4.46)

    then (4.45) is reduced into a nonlinear ODE in the form

     cυu(ξ)+3ac2u2(ξ)+3acu2(ξ)u(ξ)+3ac2u(ξ)u(ξ)+ac3u(ξ)=0. (4.47)

    By reducing (4.47), we get

     υu(ξ)+3acu2(ξ)+3au2(ξ)u(ξ)+3acu(ξ)u(ξ)+ac2u(ξ)=0. (4.48)

    Further by integrating (4.48) with respect to ξ, we get

     υu(ξ)+3acu(ξ)u(ξ)+au3(ξ)+ac2u(ξ)=0. (4.49)

    By balancing the highest order derivative term u and nonlinear term u3 in (4.49), the value of n can be determined, which is n=1 in this problem. Therefore, by Eq. (3.4), we have the following ansatz:

    u(ξ)=a0+a1(ϕϕ)+b01ϕ, (4.50)

    where a0,a1 and b0 are constants to be determined later, and function ϕ(ξ) satisfies (3.5).

    By substituting (4.50) into (4.49) and using the second order linear ODE (3.5) and (3.7), collecting all terms with the same order of 1ϕi and 1ϕiϕϕ together, the left-hand side of (4.49) is converted into another polynomial in 1ϕi and 1ϕiϕϕ. Equating each coefficient of this different power terms to zero yields a set of algebraic equations for a0,a1,b0,δ,μ,a,c and υ. Solving this system of algebraic equations, with the aid of Maple, we obtain

     1.a0=0,  a1=c,  b0=±Ξic,  υ=ac2δ.                  (4.51)
     2.a0=0,  a1=±b0Ξi,  c=±2b0Ξi,  υ=b20aδΞi.             (4.52)
     3.a0=±δΞib0,  a1=b0Ξi,  c=2b0Ξi,  υ=4b20aδΞi.    (4.53)
     4.a0=±δΞib0,  a1=b0Ξi,  c=2b0Ξi,  υ=4b20aδΞi. (4.54)

    Substituting (4.51)-(4.54) and the general solutions (3.6) of Eq. (3.5) into (4.50), we obtain more exact solutions of (4.45):

    u1i(ξ)=cΦi±ΞicΨi, (4.55)

    where ξ=c(x+ac2δtαα).

    u2i(ξ)=±b0ΞiΦi+b0Ψi, (4.56)

    where ξ=±2b0Ξi(x+b20aδtαΞiα).

    u3i(ξ)=±δΞib0+b0ΞiΦi+b0Ψi, (4.57)

    where ξ=2b0Ξi(x+4b20aδtαΞiα).

    u4i(ξ)=±δΞib0b0ΞiΦi+b0Ψi, (4.58)

    where ξ=2b0Ξi(x+4b20aδtαΞiα), in which i=1 for δ<0, i=2 for δ>0, i=3 for δ=0, and Φi,Ψi,Ξi, (i=1,2,3) see (4.10)-(4.14).

    Here A1 and A2 are arbitrary constants. Therefore, one can freely select their values. If we choose A1=0, A20, μ=0 and δ<0 in (4.55), we the traveling wave solution:

    u1(ξ)=cδ(coth(δξ)±csch(δξ)).  (4.59)

    If we choose A1=0, A20, μ=0 and δ>0 in (4.55), we obtain the traveling wave solution:

    u2(ξ)=cδ(cot(δξ)±csc(δξ)).  (4.60)

    If we choose A2=0, A10, μ=0 and δ>0 in (4.55), we obtain the traveling wave solution:

    u3(ξ)=cδ(tan(δξ)±sec(δξ)).  (4.61)

    where ξ=c(x+ac2δαtα).

    Similarly, we can write down the other families of exact solutions of Eq. (4.45) which are omitted for convenience.

    In this section, some typical wave figures are given as follows (Figure 1-3):

    Figure 1.  (a) 2D figure of solution u11(ξ) in (4.8) with A1=1,μ=1,δ=1,A2=1,c=0.5,a0=2,a=1,b2=1, (b) 2D figure of solution u12(ξ) in (4.8) with A1=1,μ=1,δ=1,A2=1,c=0.5,a0=2,a=1,b2=1.
    Figure 2.  (a) 2D figure of solution u11(ξ) in (4.37) with A1=1,μ=2,δ=1,A2=1,c=1,a=1,b1=1,y=1,z=1, (b) 2D figure of solution u12(ξ) in (4.37) with A1=1,μ=1,δ=1,A2=1,c=1,a=1,b1=1,y=1,z=1.
    Figure 3.  (a) 2D figure of solution u11(ξ) in (4.55) with A1=1,μ=2,δ=1,A2=1,c=1,a=1, (b) 2D figure of solution u12(ξ) in (4.55) with A1=1,μ=1,δ=1,A2=1,c=1,a=1.

    The basic idea of the two variable (ϕ/ϕ,1/ϕ)-expansion method is to research the new exact traveling wave solutions of the mentioned Eqs. (4.1), (4.29) and Eq. (4.45). The Eqs. (4.1), (4.29) and (4.29) have been studied using various techniques, among them, Authors obtained some new solutions, but the researches considered the Jumaries modified Riemann-Liouville derivative sense for their solution techniques. Nonetheless, the existing analytical solutions reported in [23,24,27] are not correct because the utilized definitions of fractional derivative have some shortcomings that could not be overlooked [21]. Chen et al. [25] found some new solutions of Eq. (4.29) expressed by tanh, coth, tan and cot form. In our case, first time we considered the conformable fractional derivative sense and two variable (ϕ/ϕ,1/ϕ)-expansion method for the Eqs. (4.1), (4.29) and (4.45), we found some new solutions expressed by tanh, coth, sech, csch, tan, cot, sec and csc form. To our knowledge, the solutions obtained have not been reported in former literature. So, all the solutions are new in this article.

    In this study, the two variable (ϕ/ϕ,1/ϕ)-expansion method with the help of conformable wave transformation has been applied to find out exact traveling wave solutions of time-fractional differential equations. We have obtained some new and further general solitary wave solutions to three nonlinear time fractional differential equation, namely, time-fractional K-S equation, (3+1)-dimensional KdV-ZK equation and FSTO equation in terms of hyperbolic, trigonometric and rational function solution involving parameters. These solutions have important physical implications, for example, these solutions forces are convenient to characterize the hydromagnetic waves in cold plasma, acoustic waves in inharmonic crystals and acoustic-gravity waves incompressible fluids. The obtained results show that the two variable (ϕ/ϕ,1/ϕ)-expansion method is direct, consistent, reliable, very much attractive and an effective powerful mathematical tool for obtaining the exact solutions of other time fractional differential equations, and it can be generalized to nonlinear space-time fractional differential equations and space fractional differential equations. Finally, our results in this article have been checked using the Maple by putting them back into the original equation.

    The authors would like to express their deepest appreciation to the reviewers for their valuable suggestions and comments to improve the article.

    This work was supported by the Middle-Aged Academic Backbone of Honghe University (No. 2014GG0105; No.2015GG0207), Scientific Research Foundation of Yunnan Education Department (No. 2018JS479) Yunnan Applied Basic Research Project(No.2018FH001013; 2018FH001014) and the Natural Science Foundation of Education Committee of Yunnan Province (No. 2019J0558).

    The authors declare no conflict of interest.



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