Processing math: 80%
Research article Special Issues

Properties of fractional generalized entropy in ordered variables and symmetry testing

  • Uncertainty measures are widely used in various statistical applications, including hypothesis testing and characterizations. Numerous generalizations of information measures with different extensions have been developed. Inspired by this, our study introduced the principle of the fractional generalized entropy measure and investigated its properties through stochastic comparisons and characterizations using order statistics and upper random variables. We explored the monotonicity and symmetry properties of the fractional generalized entropy, emphasizing conditions under which it uniquely identified the parent distribution. In the case of distributions that were completely continuous, The symmetrical nature of order statistics suggested that symmetry of the underpinning distribution. Based on the fractional generalized entropy measure in non-parametric estimate of order statistics, a new test for the symmetry hypothesis was put forward. This test offered the supremacy of not requiring the symmetry center to be specified. Additionally, an example of real-world data was shown to illustrate how the suggested technique might be applied.

    Citation: Mohamed Said Mohamed, Muqrin A. Almuqrin. Properties of fractional generalized entropy in ordered variables and symmetry testing[J]. AIMS Mathematics, 2025, 10(1): 1116-1141. doi: 10.3934/math.2025053

    Related Papers:

    [1] Wenjia Li, Guanglan Wang, Guoliang Li . The local boundary estimate of weak solutions to fractional p-Laplace equations. AIMS Mathematics, 2025, 10(4): 8002-8021. doi: 10.3934/math.2025367
    [2] Ibtehal Alazman, Ibtisam Aldawish, Mohamed Jleli, Bessem Samet . A higher order evolution inequality with a gradient term in the exterior of the half-ball. AIMS Mathematics, 2023, 8(4): 9230-9246. doi: 10.3934/math.2023463
    [3] Ibtehal Alazman, Ibtisam Aldawish, Mohamed Jleli, Bessem Samet . Hyperbolic inequalities with a Hardy potential singular on the boundary of an annulus. AIMS Mathematics, 2023, 8(5): 11629-11650. doi: 10.3934/math.2023589
    [4] Yasir Nadeem Anjam . The qualitative analysis of solution of the Stokes and Navier-Stokes system in non-smooth domains with weighted Sobolev spaces. AIMS Mathematics, 2021, 6(6): 5647-5674. doi: 10.3934/math.2021334
    [5] Jishan Fan, Tohru Ozawa . A note on 2D Navier-Stokes system in a bounded domain. AIMS Mathematics, 2024, 9(9): 24908-24911. doi: 10.3934/math.20241213
    [6] Abdulrahman B. Albidah, Ibraheem M. Alsulami, Essam R. El-Zahar, Abdelhalim Ebaid . Advances in mathematical analysis for solving inhomogeneous scalar differential equation. AIMS Mathematics, 2024, 9(9): 23331-23343. doi: 10.3934/math.20241134
    [7] Zhongzi Zhao, Meng Yan . Positive radial solutions for the problem with Minkowski-curvature operator on an exterior domain. AIMS Mathematics, 2023, 8(9): 20654-20664. doi: 10.3934/math.20231052
    [8] Zaihua Xu, Jian Li . Adaptive prescribed performance control for wave equations with dynamic boundary and multiple parametric uncertainties. AIMS Mathematics, 2024, 9(2): 3019-3034. doi: 10.3934/math.2024148
    [9] Mogtaba Mohammed . Homogenization of nonlinear hyperbolic problem with a dynamical boundary condition. AIMS Mathematics, 2023, 8(5): 12093-12108. doi: 10.3934/math.2023609
    [10] Yongxiang Li, Mei Wei . Positive radial solutions of p-Laplace equations on exterior domains. AIMS Mathematics, 2021, 6(8): 8949-8958. doi: 10.3934/math.2021519
  • Uncertainty measures are widely used in various statistical applications, including hypothesis testing and characterizations. Numerous generalizations of information measures with different extensions have been developed. Inspired by this, our study introduced the principle of the fractional generalized entropy measure and investigated its properties through stochastic comparisons and characterizations using order statistics and upper random variables. We explored the monotonicity and symmetry properties of the fractional generalized entropy, emphasizing conditions under which it uniquely identified the parent distribution. In the case of distributions that were completely continuous, The symmetrical nature of order statistics suggested that symmetry of the underpinning distribution. Based on the fractional generalized entropy measure in non-parametric estimate of order statistics, a new test for the symmetry hypothesis was put forward. This test offered the supremacy of not requiring the symmetry center to be specified. Additionally, an example of real-world data was shown to illustrate how the suggested technique might be applied.



    This article studies the questions of existence and nonexistence of weak solutions to the system of polyharmonic wave inequalities

    {utt+(Δ)mu|x|a|v|p,(t,x)(0,)×RN¯B1,vtt+(Δ)mv|x|b|u|q,(t,x)(0,)×RN¯B1. (1.1)

    Here, (u,v)=(u(t,x),v(t,x)), N2, B1 is the open unit ball of RN, m1 is an integer, a,b2m, (a,b)(2m,2m), and p,q>1. We will investigate (1.1) under the Navier-type boundary conditions

    {(Δ)iufi(x),i=0,,m1,(t,x)(0,)×B1,(Δ)ivgi(x),i=0,,m1,(t,x)(0,)×B1, (1.2)

    where fi,giL1(B1) and (Δ)0 is the identity operator. Notice that no restriction on the signs of fi or gi is imposed.

    The study of semilinear wave inequalities in RN was firstly considered by Kato [1] and Pohozaev & Véron [2]. It was shown that the problem

    uttΔu|u|p,(t,x)(0,)×RN (1.3)

    possesses a critical exponent pK=N+1N1 in the following sense:

    (ⅰ) If N2 and 1<ppK, then (1.3) possesses no global weak solution, provided

    RNut(0,x)dx>0. (1.4)

    (ⅱ) If p>pK, there are global positive solutions satisfying (1.4).

    Caristi [3] studied the higher-order evolution polyharmonic inequality

    jutj|x|αΔmu|u|p,(t,x)(0,)×RN, (1.5)

    where α2m. Caristi discussed separately the cases α=2m and α<2m. For instance, when j=2 and α=0, it was shown that, if Nm+1 and 1<pN+mNm, then (1.5) possesses no global weak solution, provided (1.4) holds. Other existence and nonexistence results for evolution inequalities involving the polyharmonic operator in the whole space can be found in [4,5,6].

    The study of the blow-up for semilinear wave equations in exterior domains was firstly considered by Zhang [7]. Namely, among many other problems, Zhang investigated the equation

    uttΔu=|x|a|u|p,(t,x)(0,)×RND, (1.6)

    where N3, a>2, and D is a smooth bounded subset of RN. It was shown that (1.6) under the Neumann boundary condition

    uν=f(x)0,(t,x)(0,)×D,

    admits a critical exponent N+aN2 in the following sense:

    (ⅰ) If 1<p<N+aN2, then (1.6) admits no global solution, provided f0.

    (ⅱ) If p>N+aN2, then (1.6) admits global solutions for some f>0.

    In [8,9], it was shown that the critical value p=N+aN2 belongs to case (ⅰ). Furthermore, the same result holds true, if (1.6) is considered under the Dirichlet boundary condition

    u=f(x)0,(t,x)(0,)×D,

    where D=¯B1.

    In [10], the authors considered the system of wave inequalities (1.1) in the case m=1. The system was studied under different types of inhomogeneous boundary conditions. In particular, under the boundary conditions (1.2) with m=1 (Dirichlet-type boundary conditions), the authors obtained the following result: Assume that a,b2, (a,b)(2,2), If0:=B1f0dSx0, Ig0:=B1g0dSx0, (If0,Ig0)(0,0), and p,q>1. If N=2; or N3 and

    N<max{sign(If0)2p(q+1)+pb+apq1,sign(Ig0)2q(p+1)+qa+bpq1},

    then (1.1)-(1.2) (with m=1) admits no weak solution. Moreover, the authors pointed out the sharpness of the above condition.

    In the case m=2, the system (1.1) was recently studied in [11] under different types of boundary conditions. In particular, under the boundary conditions (1.2) with f00 and g00, i.e.,

    {u0,Δuf1(x),(t,x)(0,)×B1,v0,Δvg1(x),(t,x)(0,)×B1. (1.7)

    Namely, the following result was obtained: Let N2, a,b4, (a,b)(4,4), B1f1dSx>0, B1g1dSx>0, and p,q>1. If N{2,3,4}; or

    N5,N<max{4p(q+1)+pb+apq1,4q(p+1)+qa+bpq1},

    then (1.1) (with m=2) under the boundary conditions (1.7) admits no weak solution. Moreover, it was shown that the above condition is sharp.

    Further results related to the existence and nonexistence of solutions for evolution problems in exterior domains can be found in [12,13,14,15,16,17].

    The present work aims to extend the obtained results in [10,11] from m{1,2} to an arbitrary m1. Before presenting our main results, we need to define weak solutions to the considered problem.

    Let

    Q=(0,)×RNB1,ΣQ=(0,)×B1.

    Notice that ΣQQ.

    Definition 1.1. We say that φ is an admissible test function, if

    (i) φC2,2mt,x(Q);

    (ii) supp(φ)⊂⊂Q (φ is compactly supported in Q);

    (iii) φ0;

    (iv) For all j=0,1,,m1,

    Δjφ|ΣQ=0,(1)j(Δjφ)ν|ΣQ0,

    where ν denotes the outward unit normal vector on B1, relative to RNB1.

    The set of all admissible test functions is denoted by Φ.

    Definition 1.2. We say that the pair (u,v) is a weak solution to (1.1)-(1.2), if

    (u,v)Lqloc(Q)×Lploc(Q),Q|x|a|v|pφdxdtm1i=0ΣQfi(x)((Δ)m1iφ)νdσdtQu(Δ)mφdxdt+Quφttdxdt (1.8)

    and

    Q|x|b|u|qφdxdtm1i=0ΣQgi((Δ)m1iφ)νdσdtQv(Δ)mφdxdt+Qvφttdxdt (1.9)

    for every φΦ.

    Notice that, if (u,v) is a regular solution to (1.1)-(1.2), then (u,v) is a weak solution in the sense of Definition 1.2.

    For every function fL1(B1), we set

    If=B1f(x)dσ.

    Our first main result is stated in the following theorem.

    Theorem 1.1. Let p,q>1, N2, and a,b2m with (a,b)(2m,2m). Let fi,giL1(B1) for every i=0,,m1. Assume that Ifm1,Igm10 and (Ifm1,Igm1)(0,0). If N2m; or N2m+1 and

    N<max{sign(Ifm1)×2mp(q+1)+pb+apq1,sign(Igm1)×2mq(p+1)+qa+bpq1}, (1.10)

    then (1.1)-(1.2) possesses no weak solution.

    Remark 1.1. Notice that (1.10) is equivalent to

    N2m<α,Ifm1>0; orN2m<β,Igm1>0, (1.11)

    where

    α=a+2m+p(b+2m)pq1 (1.12)

    and

    β=b+2m+q(a+2m)pq1. (1.13)

    On the other hand, due to the condition a,b2m and (a,b)(2m,2m), we have α,β>0, which shows that, if N2m, then (1.10) is always satisfied.

    The proof of Theorem 1.1 is based on the construction of a suitable admissible test function and integral estimates. The construction of the admissible test function is specifically adapted to the polyharmonic operator (Δ)m, the geometry of the domain, and the Navier-type boundary conditions (1.2).

    Remark 1.2. By Theorem 1.1, we recover the nonexistence result obtained in [10] in the case m=1. We also recover the nonexistence result obtained in [11] in the case m=2.

    Next, we are concerned with the existence of solutions to (1.1)-(1.2). Our second main result shows the sharpness of condition (1.10).

    Theorem 1.2. Let p,q>1 and a,b2m with (a,b)(2m,2m). If

    N2m>max{α,β}, (1.14)

    where α and β are given by (1.12) and (1.13), then (1.1)-(1.2) admits stationary solutions for some fi,giL1(B1) (i=0,,m1) with Ifm1,Igm1>0.

    Theorem 1.2 will be proved by the construction of explicit stationary solutions to (1.1)-(1.2).

    Remark 1.3. At this moment, we don't know whether there is existence or nonexistence in the critical case N2m+1,

    N=max{sign(Ifm1)×2mp(q+1)+pb+apq1,sign(Igm1)×2mq(p+1)+qa+bpq1}.

    This question is left open.

    From Theorem 1.1, we deduce the following nonexistence result for the corresponding stationary polyharmonic system

    {(Δ)mu|x|a|v|p,xRN¯B1,(Δ)mv|x|b|u|q,xRN¯B1, (1.15)

    under the Navier-type boundary conditions

    {(Δ)iufi(x),i=0,,m1,xB1,(Δ)ivgi(x),i=0,,m1,xB1. (1.16)

    Corollary 1.1. Let p,q>1, N2, and a,b2m with (a,b)(2m,2m). Let fi,giL1(B1) for every i=0,,m1. Assume that Ifm1,Igm10 and (Ifm1,Igm1)(0,0). If N2m; or N2m+1 and (1.10) holds, then (1.15)-(1.16) possesses no weak solution.

    The rest of this manuscript is organized as follows: Section 2 is devoted to some auxiliary results. Namely, we first construct an admissible test function in the sense of Definition 1.1. Next, we establish some useful integral estimates involving the constructed test function. The proofs of Theorems 1.1 and 1.2 are provided in Section 3.

    Throughout this paper, the letter C denotes a positive constant that is independent of the scaling parameters T, τ, and the solution (u,v). The value of C is not necessarily the same from one line to another.

    In this section, we establish some auxiliary results that will be used later in the proof of our main result.

    Let us introduce the radial function H defined in RNB1 by

    H(x)={ln|x|ifN=2,1|x|2NifN3. (2.1)

    We collect below some useful properties of the function H.

    Lemma 2.1. The function H satisfies the following properties:

    (i) H0;

    (ii) HC2m(RNB1);

    (iii) H|B1=0;

    (iv) ΔH=0 in RNB1;

    (v) For all j1,

    ΔjH|B1=(ΔjH)ν|B1=0;

    (vi) Hν|B1=C.

    Proof. (ⅰ)–(ⅴ) follow immediately from (2.1). On the other hand, we have

    Hν|B1={1ifN=2,(N2)ifN3,

    which proves (ⅵ).

    We next consider a cut-off function ξC(R) satisfying the following properties:

    0ξ1,ξ(s)=1 if |s|1,ξ(s)=0 if |s|2. (2.2)

    For all τ1, let

    ξτ(x)=ξ(|x|τ),xRNB1,

    that is (from (2.2)),

    ξτ(x)={1if1|x|τ,ξ(|x|τ)ifτ|x|2τ,0if|x|2τ. (2.3)

    For k1, we introduce the function

    ζτ(x)=H(x)ξkτ(x),xRNB1. (2.4)

    We now introduce a second cut-off function GC(R) satisfying the following properties:

    G0,supp(G)⊂⊂(0,1). (2.5)

    For T>0 and k1, let

    GT(t)=Gk(tT),t0. (2.6)

    Let φ be the function defined by

    φ(t,x)=GT(t)ζτ(x),(t,x)Q. (2.7)

    By Lemma 2.1, (2.3)–(2.7), we obtain the following result.

    Lemma 2.2. The function φ belongs to Φ.

    For all λ>1, μ2m, and φΦ, we consider the integral terms

    J(λ,μ,φ)=Q|x|μλ1φ1λ1|(Δ)mφ|λλ1dxdt (2.8)

    and

    K(λ,μ,φ)=Q|x|μλ1φ1λ1|φtt|λλ1dxdt. (2.9)

    Lemma 2.3. Let φ be the admissible test function defined by (2.7). Assume that

    (i) J(p,a,φ),J(q,b,φ),K(p,a,φ),K(q,b,φ)<;

    (ii) Ifm1,Igm10.

    If (u,v) is a weak solution to (1.1)-(1.2), then

    Ifm1CT1([J(p,a,φ)]p1p+[K(p,a,φ)]p1p)ppq1([J(q,b,φ)]q1q+[K(q,b,φ)]q1q)pqpq1 (2.10)

    and

    Igm1CT1([J(q,b,φ)]q1q+[K(q,b,φ)]q1q)qpq1([J(p,a,φ)]p1p+[K(p,a,φ)]p1p)pqpq1. (2.11)

    Proof. Let (u,v) be a weak solution to (1.1)-(1.2) and φ be the admissible test function defined by (2.7). By (1.8), we have

    Q|x|a|v|pφdxdtm1i=0ΣQfi(x)((Δ)m1iφ)νdσdtQu(Δ)mφdxdt+Quφttdxdt.

    On the other hand, by Lemma 2.1: (ⅴ), (ⅵ), (2.5)–(2.7), we have

    m1i=0ΣQfi(x)((Δ)m1iφ)νdσdt=ΣQfm1(x)φνdσdt=CΣQfm1(x)GT(t)dσdt=C(0GT(t)dt)B1fm1(x)dσ=C(0Gk(tT)dt)Ifm1=CT(10Gk(s)ds)Ifm1=CTIfm1.

    Consequently, we obtain

    Q|x|a|v|pφdxdt+CTIfm1Qu(Δ)mφdxdt+Quφttdxdt. (2.12)

    Similarly, by (1.9), we obtain

    Q|x|b|u|qφdxdt+CTIgm1Qv(Δ)mφdxdt+Qvφttdxdt. (2.13)

    Furthermore, by Hölder's inequality, we have

    Qu(Δ)mφdxdtQ|u||(Δ)mφ|dxdt=Q(|x|bq|u|φ1q)(|x|bq|(Δ)mφ|φ1q)dxdt(Q|x|b|u|qφdxdt)1q(Q|x|bq1|(Δ)mφ|qq1φ1q1dxdt)q1q,

    that is,

    Qu(Δ)mφdxdt(Q|x|b|u|qφdxdt)1q[J(q,b,φ)]q1q. (2.14)

    Similarly, we obtain

    Quφttdxdt(Q|x|b|u|qφdxdt)1q[K(q,b,φ)]q1q. (2.15)

    Thus, it follows from (2.12), (2.14), and (2.15) that

    Q|x|a|v|pφdxdt+CTIfm1(Q|x|b|u|qφdxdt)1q([J(q,b,φ)]q1q+[K(q,b,φ)]q1q). (2.16)

    Using (2.13) and proceeding as above, we obtain

    Q|x|b|u|qφdxdt+CTIgm1(Q|x|a|v|pφdxdt)1p([J(p,a,φ)]p1p+[K(p,a,φ)]p1p). (2.17)

    Using (2.16)-(2.17), and taking into consideration that Igm10, we obtain

    Q|x|a|v|pφdxdt+CTIfm1(Q|x|a|v|pφdxdt)1pq([J(p,a,φ)]p1p+[K(p,a,φ)]p1p)1q([J(q,b,φ)]q1q+[K(q,b,φ)]q1q).

    Then, by Young's inequality, it holds that

    Q|x|a|v|pφdxdt+CTIfm11pqQ|x|a|v|pφdxdt+pq1pq([J(p,a,φ)]p1p+[K(p,a,φ)]p1p)pqq(pq1)([J(q,b,φ)]q1q+[K(q,b,φ)]q1q)pqpq1.

    Consequently, we have

    (11pq)Q|x|a|v|pφdxdt+CTIfm1pq1pq([J(p,a,φ)]p1p+[K(p,a,φ)]p1p)ppq1([J(q,b,φ)]q1q+[K(q,b,φ)]q1q)pqpq1,

    which yields (2.10). Similarly, using (2.16)-(2.17), and taking into consideration that Ifm10, we obtain

    Q|x|b|u|qφdxdt+CTIgm1(Q|x|b|u|qφdxdt)1pq([J(q,b,φ)]q1q+[K(q,b,φ)]q1q)1p([J(p,a,φ)]p1p+[K(p,a,φ)]p1p),

    which implies by Young's inequality that

    Q|x|b|u|qφdxdt+CTIgm11pqQ|x|b|u|qφdxdt+pq1pq([J(q,b,φ)]q1q+[K(q,b,φ)]q1q)pqp(pq1)([J(p,a,φ)]p1p+[K(p,a,φ)]p1p)pqpq1.

    Thus, it holds that

    (11pq)Q|x|b|u|qφdxdt+CTIgm1pq1pq([J(q,b,φ)]q1q+[K(q,b,φ)]q1q)qpq1([J(p,a,φ)]p1p+[K(p,a,φ)]p1p)pqpq1,

    which yields (2.11).

    The aim of this subsection is to estimate the integral terms J(λ,μ,φ) and K(λ,μ,φ), where λ>1, μ2m, and φ is the admissible test function defined by (2.7) with τ,k1.

    The following result follows immediately from (2.5) and (2.6).

    Lemma 2.4. We have

    0GT(t)dt=CT.

    Lemma 2.5. We have

    0G1λ1T|d2GTdt2|λλ1dtCT12λλ1. (2.18)

    Proof. By (2.5) and (2.6), we have

    0G1λ1T|d2GTdt2|λλ1dt=T0G1λ1T|d2GTdt2|λλ1dt (2.19)

    and

    d2GTdt2(t)=kT2Gk2(tT)((k1)G2(tT)+G(tT)G(tT))

    for all t(0,T). The above inequality yields

    |d2GTdt2(t)|CT2Gk2(tT),t(0,T),

    which implies that

    G1λ1T|d2GTdt2|λλ1CT2λλ1Gk2λλ1(tT),t(0,T).

    Then, by (2.19), it holds that

    0G1λ1T|d2GTdt2|λλ1dtCT2λλ1T0Gk2λλ1(tT)dt=CT12λλ110Gk2λλ1(s)ds=CT12λλ1,

    which proves (2.18).

    To estimate J(λ,μ,φ) and K(λ,μ,φ), we consider separately the cases N3 and N=2.

    Lemma 2.6. We have

    RNB1|x|μλ1ζ1λ1τ|(Δ)mζτ|λλ1dxCτNμ+2mλλ1. (2.20)

    Proof. Since H and ξτ are radial functions (see (2.1) and (2.3)), to simplify writing, we set

    H(x)=H(r),ξτ(x)=ξτ(r),

    where r=|x|. By (2.4) and making use of Lemma 2.1 (ⅳ), one can show that for all xRNB1, we have

    Δmζτ(x)=Δm(H(x)ξkτ(x))=2m1i=0diHdri(r)2mij=1Ci,jdjξkτdrj(r)ri+j2m,

    where Ci,j are some constants, which implies by (2.3) that

    supp(Δmζτ){xRN:τ|x|2τ} (2.21)

    and

    |Δmζτ(x)|C2m1i=0|diHdri(r)|2mij=1|djξkτdrj(r)|ri+j2m,xsupp(Δmζτ). (2.22)

    On the other hand, for all xsupp(Δmζτ), we have by (2.1) and (2.3) that

    |diHdri(r)|={H(r)ifi=0,Cr2Niifi=1,,2m1 (2.23)

    and (we recall that 0ξτ1)

    |djξkτdrj(r)|Cτjξkjτ(r)Cτjξk2mτ(r),j=1,,2mi. (2.24)

    Then, in view of (2.1), (2.21)–(2.24), we have

    |Δmζτ(x)|Cξk2mτ(r)(H(r)2mj=1τjrj2m+r2N2m1i=12mij=1τjrj2m)Cξk2mτ(r)(τ2m+τ2N2m)Cτ2mξk2mτ(x)

    for all xsupp(Δmζτ). Taking into consideration that HC for all xsupp(Δmζτ), the above estimate yields

    |x|μλ1ζ1λ1τ|(Δ)mζτ|λλ1Cτ2mλμλ1ξk2mλλ1τ(x),xsupp(Δmζτ). (2.25)

    Finally, by (2.21) and (2.25), we obtain

    RNB1|x|μλ1ζ1λ1τ|(Δ)mζτ|λλ1dx=τ<|x|<2τ|x|μλ1ζ1λ1τ|(Δ)mζτ|λλ1dxCτ2mλμλ1τ<|x|<2τξk2mλλ1τ(x)dxCτ2mλμλ12τr=τrN1dr=CτNμ+2mλλ1,

    which proves (2.20).

    Lemma 2.7. We have

    J(λ,μ,φ)CTτNμ+2mλλ1.

    Proof. By (2.7) and (2.8), we have

    J(λ,μ,φ)=(0GT(t)dt)(RNB1|x|μλ1ζ1λ1τ|(Δ)mζτ|λλ1dx).

    Then, using Lemmas 2.4 and 2.6, we obtain the desired estimate.

    Lemma 2.8. We have

    RNB1|x|μλ1ζτ(x)dxC(τNμλ1+lnτ). (2.26)

    Proof. By (2.1)–(2.4), we have

    RNB1|x|μλ1ζτ(x)dx=1<|x|<2τ|x|μλ1(1|x|2N)ξκ(|x|τ)dx1<|x|<2τ|x|μλ1dx=C2τr=1rN1μλ1dr{CτNμλ1ifNμλ1>0,[4pt]ClnτifNμλ1=0,[4pt]CifNμλ1<0C(τNμλ1+lnτ),

    which proves (2.26).

    Lemma 2.9. We have

    K(λ,μ,φ)CT12λλ1(τNμλ1+lnτ).

    Proof. By (2.7) and (2.9), we have

    K(λ,μ,φ)=(0G1λ1T|d2GTdt2|λλ1dt)(RNB1|x|μλ1ζτ(x)dx).

    Then, using Lemmas 2.5 and 2.7, we obtain the desired estimate.

    Lemma 2.10. We have

    R2B1|x|μλ1ζ1λ1τ|(Δ)mζτ|λλ1dxCτ22mλ+μλ1lnτ. (2.27)

    Proof. Proceeding as in the proof of Lemma 2.6, we obtain

    supp(Δmζτ){xR2:τ|x|2τ}

    and

    |Δmζτ(x)|Cτ2mlnτξk2mτ(x),xsupp(Δmζτ).

    The above estimate yields

    |x|μλ1ζ1λ1τ|(Δ)mζτ|λλ1Cτ2mλμλ1lnτξk2mλλ1τ(x),xsupp(Δmζτ).

    Then, it holds that

    R2B1|x|μλ1ζ1λ1τ|(Δ)mζτ|λλ1dxCτ2mλμλ1lnττ<|x|<2τξk2mλλ1τ(x)dxCτ2mλμλ1lnτ2τr=τrdrCτ22mλ+μλ1lnτ,

    which proves (2.27).

    Using (2.7)-(2.8), Lemma 2.4, and Lemma 2.10, we obtain the following estimate of J(λ,μ,φ).

    Lemma 2.11. We have

    J(λ,μ,φ)CTτ22mλ+μλ1lnτ.

    Lemma 2.12. We have

    R2B1|x|μλ1ζτ(x)dxClnτ(τ2μλ1+lnτ). (2.28)

    Proof. By (2.1)–(2.4), we have

    R2B1|x|μλ1ζτ(x)dx=1<|x|<2τ|x|μλ1ln|x|ξκ(|x|τ)dx1<|x|<2τ|x|μλ1ln|x|dx=C2τr=1r1μλ1lnrdr{Cτ2μλ1lnτif2μλ1>0,[4pt]C(lnτ)2if2μλ1=0,[4pt]Clnτif2μλ1<0Clnτ(τ2μλ1+lnτ),

    which proves (2.28).

    Using (2.7), (2.9), Lemma 2.5, and Lemma 2.12, we obtain the following estimate of K(λ,μ,φ).

    Lemma 2.13. We have

    K(λ,μ,φ)CT12λλ1lnτ(τ2μλ1+lnτ).

    This section is devoted to the proofs of Theorems 1.1 and 1.2.

    By Remark 1.1, (1.10) is equivalent to (1.11). Without restriction of the generality, we assume that

    N2m<α,Ifm1>0. (3.1)

    Indeed, exchanging the roles of (Ifm1,a,p) and (Igm1,b,q), the case

    N2m<β,Igm1>0

    reduces to (3.1).

    We use the contradiction argument. Namely, let us suppose that (u,v) is a weak solution to (1.1)-(1.2) (in the sense of Definition 1.2). For k,T,τ1, let φ be the admissible test function defined by (2.7). Then, by Lemma 2.3, we have

    Ipq1pfm1CTpq1p([J(p,a,φ)]p1p+[K(p,a,φ)]p1p)([J(q,b,φ)]q1q+[K(q,b,φ)]q1q)q. (3.2)

    Making use of Lemmas 2.7 and 2.12, we obtain that for all N2,

    J(λ,μ,φ)CTτNμ+2mλλ1lnτ,λ>1,μ2m. (3.3)

    Similarly, by Lemmas 2.9 and 2.13, we obtain that for all N2,

    K(λ,μ,φ)CT12λλ1(τNμλ1+lnτ)lnτ,λ>1,μ2m. (3.4)

    In particular, for (λ,μ)=(p,a), we obtain by (3.3) and (3.4) that

    [J(p,a,φ)]p1p+[K(p,a,φ)]p1pC[Tp1pτ(Na+2mpp1)p1p(lnτ)p1p+T(12pp1)p1p(τNap1+lnτ)p1p(lnτ)p1p]=CTp1pτ(Na+2mpp1)p1p(lnτ)p1p[1+T2(τ2mpp1+τ(Na+2mpp1)lnτ)p1p]. (3.5)

    Furthermore, taking T=τθ, where

    \begin{equation} \theta > \max\left\{m, \left(\frac{a+2mp}{p-1}-N\right)\frac{p-1}{p}\right\}, \end{equation} (3.6)

    we obtain

    1+T^{-2}\left(\tau^{\frac{2mp}{p-1}}+\tau^{-\left(N-\frac{a+2mp}{p-1}\right)}\ln\tau\right)^{\frac{p-1}{p}}\leq C.

    Then, from (3.5), we deduce that

    \begin{equation} \left[J(p, a, \varphi)\right]^{\frac{p-1}{p}}+\left[K(p, a, \varphi)\right]^{\frac{p-1}{p}}\leq C \left[\tau^{\theta+ N-\frac{a+2mp}{p-1}}\ln\tau\right]^{\frac{p-1}{p}}. \end{equation} (3.7)

    Similarly, for

    \begin{equation} \theta > \max\left\{m, \left(\frac{b+2mq}{q-1}-N\right)\frac{q-1}{q}\right\}, \end{equation} (3.8)

    we obtain

    \begin{equation} \left(\left[J(q, b, \varphi)\right]^{\frac{q-1}{q}}+\left[K(q, b, \varphi)\right]^{\frac{q-1}{q}}\right)^{q} \leq C \left[\tau^{\theta+ N-\frac{b+2mq}{q-1}}\ln\tau\right]^{q-1}. \end{equation} (3.9)

    Thus, for T = \tau^\theta , where \theta satisfies (3.6) and (3.8), we obtain by (3.2), (3.7), and (3.9) that

    I_{f_{m-1}}^{\frac{pq-1}{p}}\leq C\tau^{-\frac{\theta(pq-1)}{p}}\left[\tau^{\theta+ N-\frac{a+2mp}{p-1}}\ln\tau\right]^{\frac{p-1}{p}}\left[\tau^{\theta+ N-\frac{b+2mq}{q-1}}\ln\tau\right]^{q-1},

    that is,

    \begin{equation} I_{f_{m-1}}^{\frac{pq-1}{p}}\leq C \tau^\delta (\ln \tau)^{\frac{pq-1}{p}}, \end{equation} (3.10)

    where

    \begin{aligned} \delta & = \frac{pq-1}{p}\left[N-\frac{(b+2mq)p+a+2mp}{pq-1}\right]\\ & = \frac{pq-1}{p} \left(N-2m-\alpha\right). \end{aligned}

    Since N-2m < \alpha , we have \delta < 0 . Then, passing to the limit as \tau\to \infty in (3.10), we reach a contradiction with I_{f_{m-1}} > 0 . This completes the proof of Theorem 1.1.

    Let us introduce the family of polynomial functions \left\{P_i\right\}_{0\leq i\leq m} , where

    P_i(z) = \left\{\begin{array}{llll} 1 &\mbox{if}& i = 0, \\[10pt] \prod\limits_{j = 0}^{i-1} (z+2j)\prod\limits_{j = 1}^i (N-2j-z)&\mbox{if}& i = 1, \cdots, m. \end{array} \right.

    From (1.14), we deduce that

    N-2j > \max\left\{\alpha, \beta\right\}, \quad j = 1, \cdots, m.

    Furthermore, because a, b\geq -2m and (a, b)\neq (-2m, -2m) , we have \alpha, \beta > 0 . Then,

    \begin{equation} P_i(z) > 0, \quad i = 0, 1, \cdots, m, \quad z\in \{\alpha, \beta\}. \end{equation} (3.11)

    For all

    \begin{equation} 0 < \varepsilon\leq \min\left\{[P_m(\alpha)]^{\frac{1}{p-1}}, [P_m(\beta)]^{\frac{1}{q-1}}\right\}, \end{equation} (3.12)

    we consider functions of the forms

    \begin{equation} u_\varepsilon(x) = \varepsilon |x|^{-\alpha}, \quad x\in \mathbb{R}^N\backslash B_1 \end{equation} (3.13)

    and

    \begin{equation} v_\varepsilon(x) = \varepsilon |x|^{-\beta}, \quad x\in \mathbb{R}^N\backslash B_1. \end{equation} (3.14)

    Since u_\varepsilon and v_\varepsilon are radial functions, elementary calculations show that

    \begin{equation} (-\Delta)^i u_\varepsilon(x) = \varepsilon P_i(\alpha)|x|^{-\alpha-2i}, \quad i = 0, 1, \cdots, m, \quad x\in\mathbb{R}^N\backslash B_1 \end{equation} (3.15)

    and

    \begin{equation} (-\Delta)^i v_\varepsilon(x) = \varepsilon P_i(\beta)|x|^{-\beta-2i}, \quad i = 0, 1, \cdots, m, \quad x\in \mathbb{R}^N\backslash B_1. \end{equation} (3.16)

    Taking i = m in (3.15), using (3.11)–(3.14), we obtain

    \begin{aligned} (-\Delta)^m u_\varepsilon(x)& = \varepsilon P_m(\alpha)|x|^{-\alpha-2m}\\ & = |x|^a \varepsilon^p |x|^{-\beta p} \left(\varepsilon^{1-p}P_m(\alpha) |x|^{-\alpha-2m-a+\beta p}\right)\\ &\geq |x|^a v_\varepsilon^{p}(x)|x|^{-\alpha-2m-a+\beta p}. \end{aligned}

    On the other hand, by (1.12) and (1.13), one can show that

    -\alpha-2m-a+\beta p = 0.

    Then, we obtain

    \begin{equation} (-\Delta)^m u_\varepsilon(x)\geq |x|^a v_\varepsilon^{p}(x), \quad x\in \mathbb{R}^N\backslash B_1. \end{equation} (3.17)

    Similarly, taking m = i in (3.16), using (3.11)–(3.14), we obtain

    \begin{aligned} (-\Delta)^m v_\varepsilon(x)& = \varepsilon P_m(\beta)|x|^{-\beta-2m}\\ & = |x|^b \varepsilon^q |x|^{-\alpha q} \left(\varepsilon^{1-q}P_m(\beta) |x|^{-\beta-2m-b+\alpha q}\right)\\ &\geq |x|^b u_\varepsilon^{q}(x)|x|^{-\beta-2m-b+\alpha q}. \end{aligned}

    Using that

    -\beta-2m-b+\alpha q = 0,

    we obtain

    \begin{equation} (-\Delta)^m v_\varepsilon(x)\geq |x|^b u_\varepsilon^{q}(x), \quad x\in \mathbb{R}^N\backslash B_1. \end{equation} (3.18)

    Furthermore, by (3.11) and (3.15), for all i = 0, \cdots, m-1 , we have

    \begin{equation} (-\Delta)^i u_\varepsilon(x) = \varepsilon P_i(\alpha) > 0, \quad x\in \partial B_1. \end{equation} (3.19)

    Similarly, by (3.11) and (3.16), for all i = 0, \cdots, m-1 , we have

    \begin{equation} (-\Delta)^i v_\varepsilon(x) = \varepsilon P_i(\beta) > 0, \quad x\in \partial B_1. \end{equation} (3.20)

    Finally, (3.17)–(3.20) show that for all \varepsilon satisfying (3.12), the pair of functions (u_\varepsilon, v_\varepsilon) given by (3.13) and (3.14) is a stationary solution to (1.1)-(1.2) with f_i\equiv \varepsilon P_i(\alpha) and g_i\equiv \varepsilon P_i(\beta) for all i = 0, \cdots, m-1 . The proof of Theorem 1.2 is then completed.

    The system of polyharmonic wave inequalities (1.1) under the inhomogeneous Navier-type boundary conditions (1.2) was investigated. First, we established a nonexistence criterium for the nonexistence of weak solutions (see Theorem 1.1). Namely, under condition (1.10), we proved that (1.1)-(1.2) possesses no weak solution, provided I_{f_{m-1}}, I_{g_{m-1}}\geq 0 and (I_{f_{m-1}}, I_{g_{m-1}})\neq (0, 0) . Next, we proved the sharpness of the obtained criterium (1.10) by showing that under condition (1.14), (1.1)-(1.2) possesses weak solutions (stationary solutions) for some f_i, g_i\in L^1(\partial B_1) ( i = 0, \cdots, m-1 ) with I_{f_{m-1}}, I_{g_{m-1}} > 0 (see Theorem 1.2). From Theorem 1.1, we deduced an optimal criterium for the nonexistence of weak solutions to the corresponding stationary polyharmonic system (1.15) under the Navier-type boundary conditions (1.16) (see Corollary 1.1).

    In this study, the critical case N\geq 2m+1 ,

    N = \max\left\{{\rm{sign}}(I_{f_{m-1}})\times \frac{2mp(q+1)+pb+a}{pq-1}, {\rm{sign}}(I_{g_{m-1}})\times \frac{2mq(p+1)+qa+b}{pq-1}\right\}

    is not investigated. It would be interesting to know whether there is existence or nonexistence of weak solutions in this case.

    Manal Alfulaij: validation, investigation, writing review and editing; Mohamed Jleli: Conceptualization, methodology, investigation and formal analysis; Bessem Samet: Conceptualization, methodology, validation and investigation. All authors have read and approved the final version of the manuscript for publication.

    The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.

    Mohamed Jleli is supported by Researchers Supporting Project number (RSP2024R57), King Saud University, Riyadh, Saudi Arabia.

    The authors declare no conflicts of interest.



    [1] M. AbaOud, M. A. Almuqrin, The weighted inverse Weibull distribution: Heavy-tailed characteristics, Monte Carlo simulation with medical application, Alex. Eng. J., 102 (2024), 99–107. https://doi.org/10.1016/j.aej.2024.05.056 doi: 10.1016/j.aej.2024.05.056
    [2] J. Ahmadi, Characterization results for symmetric continuous distributions based on the properties of k-records and spacings, Stat. Probabil. Lett., 162 (2020), 108764. https://doi.org/10.1016/j.spl.2020.108764 doi: 10.1016/j.spl.2020.108764
    [3] C. D. Aliprantis, O. Burkinshaw, Principles of real analysis, London: Edward Arnold, 1981.
    [4] M. A. Almuqrin, A new flexible distribution with applications to engineering data, Alex. Eng. J., 69 (2023), 371–382. https://doi.org/10.1016/j.aej.2023.01.046 doi: 10.1016/j.aej.2023.01.046
    [5] M. A. Almuqrin, Next-generation statistical methodology: Advances health science research, Alex. Eng. J., 108 (2024), 459–475. https://doi.org/10.1016/j.aej.2024.07.097 doi: 10.1016/j.aej.2024.07.097
    [6] G. Alomani, M. Kayid, Stochastic properties of fractional generalized cumulative residual entropy and its extensions, Entropy, 24 (2022), 1041. https://doi.org/10.3390/e24081041 doi: 10.3390/e24081041
    [7] A. Baklizi, A conditional distribution runs test for symmetry, J. Nonparametr. Stat., 15 (2003), 713–718. https://doi.org/10.1080/10485250310001634737 doi: 10.1080/10485250310001634737
    [8] A. Baklizi, Testing symmetry using a trimmed longest run statistic, Aust. N. Z. J. Stat., 49 (2007), 339–347. https://doi.org/10.1111/j.1467-842X.2007.00485.x doi: 10.1111/j.1467-842X.2007.00485.x
    [9] A. Baklizi, Improving the power of the hybrid test, Int. J. Contemp. Math. Sciences, 3 (2008), 497–499.
    [10] N. Balakrishnan, A. Selvitella, Symmetry of a distribution via symmetry of order statistics, Stat. Probabil. Lett., 129 (2017), 367–372. https://doi.org/10.1016/j.spl.2017.06.023 doi: 10.1016/j.spl.2017.06.023
    [11] F. Belzunce, R. E. Lillo, J. M. Ruiz, M. Shaked, Stochastic comparisons of nonhomogeneous processes, Probab. Eng. Inform. Sc., 15 (2001), 199–224. https://doi.org/10.1017/S0269964801152058 doi: 10.1017/S0269964801152058
    [12] V. Bozin, B. Milosevic, Y. Y. Nikitin, M. Obradovic, New characterization-based symmetry tests, Bull. Malays. Math. Sci. Soc., 43 (2020), 297–320. https://doi.org/10.1007/s40840-018-0680-3 doi: 10.1007/s40840-018-0680-3
    [13] W. H. Cheng, N. Balakrishnan, A modified sign test for symmetry, Commun. Stat.-Simul. C., 33 (2004), 703–709. https://doi.org/10.1081/SAC-200033302 doi: 10.1081/SAC-200033302
    [14] J. Corzo, G. Babativa, A modified runs test for symmetry, J. Stat. Comput. Sim., 83 (2013), 984–991. https://doi.org/10.1080/00949655.2011.647026 doi: 10.1080/00949655.2011.647026
    [15] X. J. Dai, C. Z. Niu, X. Guo, Testing for central symmetry and inference of the unknown center, Comput. Stat. Data An., 127 (2018), 15–31. https://doi.org/10.1016/j.csda.2018.05.007 doi: 10.1016/j.csda.2018.05.007
    [16] A. Di Crescenzo, M. Longobardi, On cumulative entropies, J. Stat. Plan. Infer., 139 (2009), 4072–4087. https://doi.org/10.1016/j.jspi.2009.05.038
    [17] A. Di Crescenzo, S. Kayal, A. Meoli, Fractional generalized cumulative entropy and its dynamic version, Commun. Nonlinear Sci., 102 (2021), 105899. https://doi.org/10.1016/j.cnsns.2021.105899 doi: 10.1016/j.cnsns.2021.105899
    [18] G. W. Cobb, The problem of the Nile: conditional solution to a change point problem, Biometrika, 65 (1978), 243–251. https://doi.org/10.1093/biomet/65.2.243 doi: 10.1093/biomet/65.2.243
    [19] M. Fashandi, J. Ahmadi, Characterizations of symmetric distributions based on Renyi entropy, Stat. Probabil. Lett., 82 (2012), 798–804. https://doi.org/10.1016/j.spl.2012.01.004 doi: 10.1016/j.spl.2012.01.004
    [20] J. D. Gibbons, S. Chakraborti, Nonparametric statistical inference, New York: Dekker, 1992.
    [21] C. Goffman, G. R. Pedrick, First course in functional analysis, Englewood Cliffs: Prentice-Hall, 1965.
    [22] P. Crzegorzewski, R. Wieczorkowski, Entropy-based goodness-of-fit test for exponentiality, Commun. Stat.-Theor. M., 28 (1999), 1183–1202. https://doi.org/10.1080/03610929908832351 doi: 10.1080/03610929908832351
    [23] N. Gupta, S. K. Chaudhary, Some characterizations of continuous symmetric distributions based on extropy of record values, Stat. Papers, 65 (2024), 291–308. https://doi.org/10.1007/s00362-022-01392-y doi: 10.1007/s00362-022-01392-y
    [24] I. A. Husseiny, H. M. Barakat, M. Nagy, A. H. Mansi, Analyzing symmetric distributions by utilizing extropy measures based on order statistics, J. Radiat. Res. Appl. Sc., 17 (2024), 101100. https://doi.org/10.1016/j.jrras.2024.101100 doi: 10.1016/j.jrras.2024.101100
    [25] J. Jose, E. I. A. Sathar, Symmetry being tested through simultaneous application of upper and lower k-records in extropy, J. Stat. Comput. Sim., 92 (2022), 830–846. https://doi.org/10.1080/00949655.2021.1975283 doi: 10.1080/00949655.2021.1975283
    [26] J. Jozefczyk, Data driven score tests for univariate symmetry based on nonsmooth functions, Probab. Math. Stat., 32 (2012), 301–322.
    [27] J. T. Machado, Fractional order generalized information, Entropy, 16 (2014), 2350–2361. https://doi.org/10.3390/e16042350 doi: 10.3390/e16042350
    [28] M. Mahdizadeh, E. Zamanzade, Estimation of a symmetric distribution function in multistage ranked set sampling, Stat. Papers, 61 (2020), 851–867. https://doi.org/10.1007/s00362-017-0965-x doi: 10.1007/s00362-017-0965-x
    [29] T. P. McWilliams, A distribution-free test for symmetry based on a runs statistic, J. Am. Stat. Assoc., 85 (1990), 1130–1133. https://doi.org/10.2307/2289611 doi: 10.2307/2289611
    [30] R. Modarres, J. L. Gastwirth, A modified runs test for symmetry, Stat. Probabil. Lett., 31 (1996), 107–112. https://doi.org/10.1016/S0167-7152(96)00020-X doi: 10.1016/S0167-7152(96)00020-X
    [31] M. S. Mohamed, On concomitants of ordered random variables under general forms of Morgenstern family, Filomat, 33 (2019), 2771–2780. https://doi.org/10.2298/FIL1909771M doi: 10.2298/FIL1909771M
    [32] M. S. Mohamed, A measure of inaccuracy in concomitants of ordered random variables under Farlie-Gumbel-Morgenstern family, Filomat, 33 (2019), 4931–4942. https://doi.org/10.2298/FIL1915931M doi: 10.2298/FIL1915931M
    [33] M. S. Mohamed, On cumulative residual Tsallis entropy and its dynamic version of concomitants of generalized order statistics, Comm. Statist. Theory Methods, 51 (2022), 2534–2551. https://doi.org/10.1080/03610926.2020.1777306 doi: 10.1080/03610926.2020.1777306
    [34] J. Navarro, Y. del Aguila, M. Asadi, Some new results on the cumulative residual entropy, J. Stat. Plan. Infer., 140 (2010), 310–322. https://doi.org/10.1016/j.jspi.2009.07.015 doi: 10.1016/j.jspi.2009.07.015
    [35] H. A. Noughabi, Tests of symmetry based on the sample entropy of order statistics and power comparison, Sankhya B, 77 (2015), 240–255. https://doi.org/10.1007/s13571-015-0103-5 doi: 10.1007/s13571-015-0103-5
    [36] H. A. Noughabi, J. Jarrahiferiz, Extropy of order statistics applied to testing symmetry, Commun. Stat.-Simul. C., 51 (2022), 3389–3399. https://doi.org/10.1080/03610918.2020.1714660 doi: 10.1080/03610918.2020.1714660
    [37] S. Park, A goodness-of-fit test for normality based on the sample entropy of order statistics, Stat. Probabil. Lett., 44 (1999), 359–363. https://doi.org/10.1016/S0167-7152(99)00027-9 doi: 10.1016/S0167-7152(99)00027-9
    [38] G. Psarrakos, J. Navarro, Generalized cumulative residual entropy and record values, Metrika, 76 (2013), 623–640. https://doi.org/10.1007/s00184-012-0408-6 doi: 10.1007/s00184-012-0408-6
    [39] G. Psarrakos, A. Toomaj, On the generalized cumulative residual entropy with applications in actuarial science, J. Comput. Appl. Math., 309 (2017), 186–199. https://doi.org/10.1016/j.cam.2016.06.037 doi: 10.1016/j.cam.2016.06.037
    [40] M. Rao, Y. Chen, B. C. Vemuri, F. Wang, Cumulative residual entropy: a new measure of information, IEEE T. Inform. Theory, 50 (2004), 1220–1228. https://doi.org/10.1109/TIT.2004.828057 doi: 10.1109/TIT.2004.828057
    [41] H. H. Sakr, M. S. Mohamed, Sharma-Taneja-Mittal entropy and its application of obesity in Saudi Arabia, Mathematics, 12 (2024), 2639. https://doi.org/10.3390/math12172639 doi: 10.3390/math12172639
    [42] M. Shaked, J. G. Shanthikumar, Stochastic orders and their applications, San Diego: Academic Press, 1994.
    [43] C. E. Shannon, A mathematical theory of communication, Bell System Technical Journal, 27 (1948), 379–423. http://doi.org/10.1002/j.1538-7305.1948.tb01338.x doi: 10.1002/j.1538-7305.1948.tb01338.x
    [44] I. H. Tajuddin, Distribution-free test for symmetry based on the Wilcoxon two-sample test, J. Appl. Stat., 21 (1994), 409–415. https://doi.org/10.1080/757584017 doi: 10.1080/757584017
    [45] A. Toomaj, A. Di Crescenzo, Generalized entropies, variance and applications, Entropy, 22 (2020), 709. https://doi.org/10.3390/e22060709
    [46] M. R. Ubriaco, Entropies based on fractional calculus, Phys. Lett. A, 373 (2009), 2516–2519. https://doi.org/10.1016/j.physleta.2009.05.026 doi: 10.1016/j.physleta.2009.05.026
    [47] O. Vasicek, A test for normality based on sample entropy, J. R. Stat. Soc. B, 38 (1976), 54–59. https://doi.org/10.1111/j.2517-6161.1976.tb01566.x doi: 10.1111/j.2517-6161.1976.tb01566.x
    [48] H. Xiong, P. J. Shang, Y. L. Zhang, Fractional cumulative residual entropy, Commun. Nonlinear Sci., 78 (2019), 104879. https://doi.org/10.1016/j.cnsns.2019.104879 doi: 10.1016/j.cnsns.2019.104879
    [49] P. H. Xiong, W. W. Zhuang, G. X. Qiu, Testing symmetry based on the extropy of record values, J. Nonparametr. Stat., 33 (2021), 134–155. https://doi.org/10.1080/10485252.2021.1914338 doi: 10.1080/10485252.2021.1914338
    [50] S. Yin, Y. D. Zhao, A. Hussain, K. Ullah, Comprehensive evaluation of rural regional integrated clean energy systems considering multi-subject interest coordination with pythagorean fuzzy information, Eng. Appl. Artif. Intel., 138 (2024), 109342. https://doi.org/10.1016/j.engappai.2024.109342 doi: 10.1016/j.engappai.2024.109342
  • Reader Comments
  • © 2025 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(696) PDF downloads(50) Cited by(1)

Figures and Tables

Figures(6)  /  Tables(4)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog