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Research article Special Issues

Improving performance of decision threshold moving-based strategies by integrating density-based clustering technique

  • Received: 31 December 2022 Revised: 19 February 2023 Accepted: 23 February 2023 Published: 06 March 2023
  • Class imbalance learning (CIL), which aims to addressing the performance degradation problem of traditional supervised learning algorithms in the scenarios of skewed data distribution, has become one of research hotspots in fields of machine learning, data mining, and artificial intelligence. As a postprocessing CIL technique, the decision threshold moving (DTM) has been verified to be an effective strategy to address class imbalance problem. However, no matter adopting random or optimal threshold designation ways, the classification hyperplane could be only moved parallelly, but fails to vary its orientation, thus its performance is restricted, especially on some complex and density variable data. To further improve the performance of the existing DTM strategies, we propose an improved algorithm called CDTM by dividing majority training instances into multiple different density regions, and further conducting DTM procedure on each region independently. Specifically, we adopt the well-known DBSCAN clustering algorithm to split training set as it could adapt density variation well. In context of support vector machine (SVM) and extreme learning machine (ELM), we respectively verified the effectiveness and superiority of the proposed CDTM algorithm. The experimental results on 40 benchmark class imbalance datasets indicate that the proposed CDTM algorithm is superior to several other state-of-the-art DTM algorithms in term of G-mean performance metric.

    Citation: Mengke Lu, Shang Gao, Xibei Yang, Hualong Yu. Improving performance of decision threshold moving-based strategies by integrating density-based clustering technique[J]. Electronic Research Archive, 2023, 31(5): 2501-2518. doi: 10.3934/era.2023127

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  • Class imbalance learning (CIL), which aims to addressing the performance degradation problem of traditional supervised learning algorithms in the scenarios of skewed data distribution, has become one of research hotspots in fields of machine learning, data mining, and artificial intelligence. As a postprocessing CIL technique, the decision threshold moving (DTM) has been verified to be an effective strategy to address class imbalance problem. However, no matter adopting random or optimal threshold designation ways, the classification hyperplane could be only moved parallelly, but fails to vary its orientation, thus its performance is restricted, especially on some complex and density variable data. To further improve the performance of the existing DTM strategies, we propose an improved algorithm called CDTM by dividing majority training instances into multiple different density regions, and further conducting DTM procedure on each region independently. Specifically, we adopt the well-known DBSCAN clustering algorithm to split training set as it could adapt density variation well. In context of support vector machine (SVM) and extreme learning machine (ELM), we respectively verified the effectiveness and superiority of the proposed CDTM algorithm. The experimental results on 40 benchmark class imbalance datasets indicate that the proposed CDTM algorithm is superior to several other state-of-the-art DTM algorithms in term of G-mean performance metric.



    Nematic liquid crystals are aggregates of molecules which possess same orientational order and are made of elongated, rod-like molecules. Hence, in the study of nematic liquid crystals, one approach is to consider the behavior of the director field d in the absence of the velocity fields. Unfortunately, the flow velocity does disturb the alignment of the molecules. More importantly, the converse is also true, that is, a change in the alignment will induce velocity. This velocity will in turn affect the time evolution of the director field. In this process, we cannot assume that the velocity field will remain small even when we start with zero velocity field.

    In the 1960's, Ericksen [3,4] and Leslie [10,11] developed the hydrodynamic theory of liquid crystals. The Ericksen-Leslie system consists of the following equations [12]:

    {ρt+(ρu)=0,(ρu)t=ρFi+σji,j,ρ1(ωi)t=ρ1Gi+gi+πji,j, (1.1)

    where (1.1)1, (1.1)2 and (1.1)3, represent the conservation of mass, linear momentum and angular momentum respectively. Besides, ρ denotes the fluid density, u=(u1,u2,u3) is the velocity vector and d=(d1,d2,d3) the direction vector,

    {σji=PδijρFdk,j+ˆσji,πji=βjdi+ρFdi,j,gi=γdiβjdi,jρFdi+ˆgi, (1.2)

    where Fi is the external body force, Gi denotes the external director body force and β, γ come from the restriction of the direction vector |d|=1. The following relations also hold:

    {2ρF=k22di,jdi,j+(k11k22k24)di,idj,j+(k33k22)didjdk,idkj+k24di,jdj,i,ˆσji=μ1dkdpAkpdidj+μ2djNi+μ3diNj+μ4Aij+μ5djdkAki+μ6didkAkj,ˆgi=λ1Ni+λ2djAji, (1.3)

    and

    {ωi=˙di=dit+udi,Ni=ωi+ωkidk,Nij=ωi,j+ωkidk,j, (1.4)

    where

    2Aij=ui,j+uj,i,2ωi,j=ui,juj,i.

    On the basis of the second law of thermodynamics and Onsager reciprocal relation, one obtain

    λ1=μ2μ3,λ2=μ5μ6=(μ2+μ3).

    The nonlinear constraint |d|=1 can also be relaxed by using the Ginzburg-Landau approximation, that is, instead of the restriction |d|=1, we add the term 1ε2(|d|21)2 in ρF. In addition, to further simplify the calculation, one take ρ1=0, βj=0, γ=0, Fi=0 and ρF=|d|2+1ε2(|d|21)2, choose the domain Ω=R3, obtain the simplified model of nematic liquid crystals:

    {ρt+(ρu)=0,(ρu)t+(ρuu)μΔu(μ+λ)u+p(ρ)=Δdd,dt+ud=Δdf(d), (1.5)

    with the following initial conditions

    ρ(x,0)=ρ0(x),u(x,0)=u0(x),d(x,0)=d0(x),|d0(x)|=1, (1.6)

    and

    ρ0ˉρHN(R3),u0HN(R3),d0ω0HN(R3), (1.7)

    for any integer N3 with a fixed vector ω0S2, that is, |ω0|=1. In this paper, we assume that f(d)=1ε2(|d|21)d (ε>0) is the Ginzburg-Landau approximation and the pressure p=p(ρ) is a smooth function in a neighborhood of ˉρ with p(ˉρ)>0 for ˉρ>0. Moreover, μ and λ are the shear viscosity and the bulk viscosity coefficients of the fluid, respectively. As usual, the following inequalities hold:

    μ>0,3λ+2μ0.

    The study of liquid crystals can be traced back to Ericksen [3,4] and Leslie [10,11] in the 1960s. Since then, there is a huge amount of literature on this topic. For the incompressible case, we refer the author to [2,6,12,13,20] and the reference therein. There are also many papers related to the compressible case, see for instance, [1,5,7,8,17,19] and the reference cited therein.

    In [19], the authors rewrote system (1.5) in the perturbation form as

    {ϱt+ˉρu=ϱuuϱ,utˉμΔu(ˉμ+ˉλ)u+γˉρϱ=uuh(ϱ)(ˉμΔu+(ˉμ+ˉλ)u)g(ϱ)ϱϕ(Δdd),dt+ud=Δdf(d), (1.8)

    where ϱ=ρˉρ, ˉμ=μˉρ, ˉλ=λˉρ, γ=p(ˉρ)¯ρ2 and the nonlinear functions of ϱ are defined by

    h(ϱ)=ϱϱ+ˉρ,g(ϱ)=p(ϱ+ˉρ)ϱ+ˉρp(ˉρ)ˉρ,ϕ(ϱ)=1ρ+ˉρ.

    We remark that the functions h(ϱ), g(ϱ) and ϕ(ϱ) satisfy (see [19])

    |h(ϱ)|,|g(ϱ)|C|ϱ|,|ϕ(l)(ϱ)|,|h(k)(ϱ)|,|g(k)(ϱ)|Cfor anyl0,k1. (1.9)

    Wei, Li and Yao [19] obtained the small initial data global well-posedness provided that ϱ0H3+u0H3+d0ω0H4 is sufficiently small. Moreover, the authors also showed the optimal decay rates of higher order spatial derivatives of of strong solutions provided that (ϱ0,u0,d0)˙Hs for some s[0,12].

    Next, we introduce the main results in [19]:

    Lemma 1.1. (Small initial data global well-posedness [19]) Assume that N3 and (ϱ0,u0,d0ω0)HN(R3)×HN(R3)×HN+1(R3). Then for a unit vector ω0, there exists a positive constant δ0 such that if

    ϱ0H3+u0H3+d0ω0H4δ0, (1.10)

    then problem (1.8) has a unique global solution (ϱ(t),u(t),d(t)) satisfying that for all t0,

    ddt(ϱ2HN+u2HN+d2HN)+C0(ϱ2HN1+u2HN+d2HN)0. (1.11)

    Lemma 1.2. (Decay estimates [19]) Assume that all the assumptions of Lemma 1.1 hold. Then, if (ϱ0,u0,d0)˙Hs for some s[0,12], we have

    Λsϱ(t)2L2+Λsu(t)2L2+Λsd(t)2L2C1,t0, (1.12)

    and

    lϱHNl+luHNl+l+1dHNlC2(1+t)l+s2,t0andl=0,1,,N1. (1.13)

    The main purpose of this paper is to improve the decay results in [19]. First, we give a remark on the symbol stipulations of this paper.

    Remark 1.3. In this paper, we use Hk(R3) (kR), to denote the usual Sobolev spaces with norm Hs, and Lp(R3) (1p) to denote the usual Lp spaces with norm Lp. We also introduce the homogeneous negative index Sobolev space ˙Hs(R3):

    ˙Hs(R3):={fL2(R3):|ξ|sˆf(ξ)L2<}

    endowed with the norm f˙Hs:=|ξ|sˆf(ξ)L2. The symbol l with an integer l0 stands for the usual spatial derivatives of order l. For instance, we define

    lz={αxzi||α|=l,i=1,2,3},z=(z1,z2,z3).

    If l<0 or l is not a positive integer, l stands for Λl defined by

    Λsf(x)=R3|ξ|sˆf(ξ)e2πixξdξ,

    where ˆf is the Fourier transform of f. Besides, C and Ci (i=0,1,2,) will represent generic positive constants that may change from line to line even if in the same inequality. The notation AB means that ACB for a universal constant C>0 that only depends on the parameters coming from the problem.

    It is worth pointing out that in [19], the authors consider problem (1.5) in 3D case, the negative Sobolev norms were shown to be preserved along time evolution and enhance the decay rates. However, because the Ginzburg-Landau approximation term is difficulty to control, only s[0,12] were considered in [19]. In this paper, we ovcome the difficult caused by Ginzburg-Landau approximation, assume that s[0,32), obtain the optimal decay rates of higher order spatial derivatives of strong solutions for problem (1.5). Our main results are stated in the following theorem.

    Theorem 1.4. Assume that all the assumptions of Lemma 1.1 hold. Then, if (ϱ0,u0,d0)˙Hs for some s[0,32), we have

    Λsϱ(t)2L2+Λsu(t)2L2+Λsd(t)2L2C0,t0, (1.14)

    and

    lϱHNl+luHNl+l+1dHNlC(1+t)l+s2,forl=0,1,,N1,t0. (1.15)

    Note that the Hardy-Littlewood-Sobolev theorem implies that for p(1,2], Lp(R3)˙Hs(R3) with s=3(1p12)[0,32). Then, on the basis of Lemma 1.2 and Theorem 1.4, we obtain the optimal decay estimates for system (1.8).

    Corollary 1.5. Under the assumptions of Lemma 1.2 and Theorem 1.4, if we replace the ˙Hs(R3) assumption by

    (ϱ,u0,d0)Lp(R3),1<p2,

    then for l=0,1,,N1, , the following decay estimate holds:

    lϱHNl+luHNl+l+1dHNlC(1+t)[32(1p12)+l2],t0. (1.16)

    Remark 1.6. Lemma 1.1 shows the global well-posedness of strong solutions for system (1.5) provided that the smallness assumption (1.10) holds. One can use the energy method to obtain the higher order energy estimates for the solution to prove this lemma (see [19]). We remark that the negative Sobolev norm estimates did not appear in the proving process of Lemma 1.1, it is only used in the decay estimates. Hence, the value of s in Lemma 1.2 and Theorem 1.4 do not affect the energy estimates (1.10) and (1.11). And those two estimates hold for both Lemma 1.2 and Theorem 1.4.

    Remark 1.7. The main purpose of this paper is to prove Theorem 1.4 and Corollary 1.5 on the asymptotic behavior of strong solutions for a compressible Ericksen-Leslie system. We remark that the global well-posedness and asymptotic behavior of solutions are important for the study of nematic liquid crystals system. Thanks to the above properties of solutions, one can understand the model more profoundly. Our results maybe useful for the study of nematic liquid crystals.

    The structure of this paper is organized as follows. In Section 2, we introduce some preliminary results. The proof of Theorem 1.4 is postponed in Section 3.

    We first show a useful Sobolev embedding theorem in the following Lemma 2.1:

    Lemma 2.1. ([15]) If 0s<32, one have

    uL632s(R3)u˙Hs(R3)forallu˙Hs(R3). (2.1)

    In [14], the author proved the following Gagliardo-Nirenberg inequality:

    Lemma 2.2. ([14]) Let 0m,αl, then we have

    αfLp(R3)mf1θLq(R3)lfθLr(R3), (2.2)

    where θ[0,1] and α satisfies

    α31p=(m31q)(1θ)+(l31r)θ. (2.3)

    Here, when p=, we require that 0<θ<1.

    One also introduce the Kato-Ponce inequality which is of great importance in our paper.

    Lemma 2.3. ([9]) Let 1<p<, s>0. There exists a positive constant C such that

    s(fg)Lp(R3)fLp1(R3)sgLp2(R3)+sfLq1(R3)gLq2(R3), (2.4)

    where p2,q2(1,) satisfying 1p=1p1+1p2=1q1+1q2.

    The Hardy-Littlewood-Sobolev theorem implies the following Lp type inequality:

    Lemma 2.4. ([16]) Let 0s<32, 1<p2 and 12+s3=1p, then

    f˙Hs(R3)fLp(R3). (2.5)

    In the end, we introduce the special Sobolev interpolation lemma, which will be used in the proof of Theorem 1.4.

    Lemma 2.5. ([18]) Let s0 and l0, then

    lfL2(R3)l+1f1θL2(R3)fθ˙Hs(R3),withθ=1l+1+s. (2.6)

    Equation (1.8)3 can be rewritten as

    (dω0)tΔ(dω0)=u(dω0)[f(d)f(ω0)]. (3.1)

    In [19], the authors proved the L2-norm estimate of dω0 provided that the assumptions of Lemma 1.1 hold.

    Lemma 3.1. ([19]) Assume that all the assumptions of Lemma 1.1 hold. Then, the solution of (3.1) satisfies

    dω02L2+t0(dω0)2L2d0ω02L2. (3.2)

    In the following, we prove the decay estimates of strong solutions for system (1.8). The case s[0,12] was shown in Lemma 1.2, one only need to consider the case s(12,32). We first derive the evolution of the negative Sobolev norms of the solution.

    Lemma 3.2. Under the assumptions of Lemma 1.1, if s(12,32), we have

    ddtR3(γ|Λsϱ|2+|Λsu|2+|Λsd|2)dx+CR3(|Λsu|2+|Λs2d|2)dxCd2H1(ΛsuL2+ΛsϱL2+ΛsdL2)+(ϱL2+uL2+dL2)s12(ϱH1+uH1+2dH1)52s×(ΛsuL2+ΛsϱL2+ΛsdL2). (3.3)

    Proof. Applying Λs to (1.8)1, (1.8)2, Λs to (1.8)3, multiplying the resulting identities by γΛsϱ, Λsu and Λsd respectively, summing up and integrating over R3 by parts, we arrive at

    12ddtR3(γ|Λsϱ|2+|Λsu|2+|Λsd|2)dx+R3(ˉμ|Λsu|2+(ˉμ|Λsu|2+(ˉμ+ˉλ)|Λsu|2+|Λs2d|2)dx=R3γΛs(ϱuuϱ)ΛsϱΛs[uu+h(ϱ)(ˉμΔu+(ˉμ+ˉλ)u)+g(ϱ)ϱ+ϕ(Δdd)]ΛsuΛs(ud+f(d))Λsddx=K1+K2+K3+K4+K5+K6+K7+K8. (3.4)

    Note that s(12,32), it is easy to see that 12+s3<1 and 3s(2,6). For the terms K1, by using Lemmas 2.2 and 2.4, Hölder's inequality, Young's inequality together with the estimates established in Lemma 1.1, we deduce that

    K1=R3γΛs(ϱu)ΛsϱdxCΛs(ϱu)L2ΛsϱL2CϱuL112+s3ΛsϱL2CϱL3suL2ΛsϱL2Cϱs12L2ϱ32sL2uL2ΛsϱL2, (3.5)

    similarly, for K2K6, we have

    K2=R3γΛs(uϱ)ΛsϱdxCΛs(uϱ)L2ΛsϱL2CuϱL112+s3ΛsϱL2CuL3sϱL2ΛsϱL2Cus12L2u32sL2ϱL2ΛsϱL2, (3.6)
    K3=R3γΛs(uu)ΛsϱdxCΛs(uu)L2ΛsϱL2CuuL112+s3ΛsϱL2CuL3suL2ΛsϱL2Cus12L2u32sL2uL2ΛsϱL2, (3.7)
    K4=R3Λs[h(ϱ)(ˉμΔu+(ˉμ+ˉλ)u)]ΛsϱdxΛs[h(ϱ)(ˉμΔu+(ˉμ+ˉλ)u)]L2ΛsϱL2Ch(ϱ)(ˉμΔu+(ˉμ+ˉλ)u)L112+s3ΛsϱL2Ch(ϱ)L3s2uL2ΛsϱL2CϱL3s2uL2ΛsϱL2Cϱs12L2ϱ32sL22uL2ΛsϱL2, (3.8)
    K5=R3Λs[g(ϱ)ϱ]ΛsϱdxΛs[g(ϱ)ϱ]L2ΛsϱL2Cg(ϱ)ϱL112+s3ΛsϱL2Cg(ϱ)L3sϱL2ΛsϱL2CϱL3sϱL2ΛsϱL2Cϱs12L2ϱ32sL2ϱL2ΛsϱL2, (3.9)

    and

    K6=R3Λs(ϕ(ϱ)dΔd)ΛsudxCΛs(ϕ(ϱ)dΔd)L2ΛsuL2Cϕ(ϱ)dΔdL112+s3ΛsuL2Cϕ(ϱ)LdΔdL112+s3ΛsuL2CdΔdL112+s3ΛsuL2CdL3sΔdL2ΛsuL2Cds12L2Δd32sL2ΔdL2ΛsuL2, (3.10)

    where we have used the fact (1.9) in (3.8)–(3.10). Next, by using Lemmas 2.2–2.4, Hölder's inequality, Young's inequality together with Lemma 1.1 on the energy estimates of the solutions, it yields that

    K7=R3Λs(ud)ΛsddxCΛs(ud+u2d)L2ΛsdL2C(udL112+s3+u2dL112+s3)ΛsdL2C(dL3suL2+uL3s2dL2)ΛsdL2C(ds12L22d32sL2uL2+us12L2u32sL22dL2)ΛsdL2. (3.11)

    For K8, we first consider s(12,1). Thanks to Lemma 2.2, one easily obtain

    Λ2sdL2+Λ2s(dω0)L2+Λ2s(d+ω0)L2CdsL22d1sL2C(dL2+2dL2).

    Then, by Hölder's inequality, Young's inequality, the facts |d|<1, |ω0|=1 together with Lemmas 1.1, 2.2 and 2.3, we derive that

    K8=R3Λs[(d+ω0)(dω0)d]ΛsddxCΛs[(d+ω0)(dω0)d]L2ΛsdL2C[d+ω0L6dω0L6Λ1sdL6+d+ω0L6dL6Λ1s(dω0)L6+dω0L6dL6Λ1s(d+ω0)L6]ΛsdL2Cd2L2(Λ2sdL2+Λ2s(dω0)L2+Λ2s(d+ω0)L2)ΛsdL2CdL2(dL2+2dL2)ΛsdL2C(d2L2+2d2L2)ΛsdL2. (3.12)

    Moreover, if s(1,32), the following inequality holds:

    K8CΛs+1[(d+ω0)(dω0)d]L2ΛsdL2C(d+ω0)(dω0)dL112+s13ΛsdL2Cd+ω0Ldω0L2dL3s1ΛsdL2Cd12L22d12L2dω0L2d(s1)+12L22d12(s1)L2ΛsdL2CdsL22d2sL2ΛsdL2C(d2L2+2d2L2)ΛsdL2. (3.13)

    Combining (3.4)–(3.12) together, we obtain (3.3) and complete the proof.

    Now, we give the proof of our main results.

    Proof of Theorem 1.4. First of all, the sketch of proof for the decay estimate with s[0,12] will be derived in the following. Note that this part follows more or less the lines of [19], so that we do note claim originality here. Then, by using this proved estimate, one can obtain the decay results for s(12,32).

    Now, consider the decay for s[0,12]. We first establish the negative Sobolev norm estimates for the strong solutions, obtain one important inequality:

    ddt(γΛsϱ2L2+Λsu2L2+Λsd2L2)+C(Λsu2L2+Λs2d2L2)((ϱ,u)2H1+d2H2)(Λsϱ2L2+Λsu2L2+Λsd2L2).

    Then, define

    Es(t)=Λsϱ(t)2L2+Λsu(t)2L2+Λsd(t)2L2,

    we deduce from (3.2) and (3.3) that for s[0,12],

    Es(t)Es(0)+Ct0((ϱ,u)2H1+d2H2)Es(t)dτC(1+sup0τtEs(t)),

    which implies (1.12) for s[0,12], i.e.,

    Λsϱ(t)2L2+Λsu(t)2L2+Λsd(t)2L2C0. (3.14)

    Moreover, if l=1,2,,N1, we may use Lemma 2.4 to have

    l+1fL2CΛsf1l+sL2lf1+1l+sL2. (3.15)

    Then, by (3.14) and (3.15), it yields that

    l(ϱ,u,2d)2L2C(l(ϱ,u,d)2L2)1+1l+s.

    Hence, for l=1,2,,N1,

    l(ϱ,u,2d)2HNl1C(l(ϱ,u,d)2HNl)1+1l+s. (3.16)

    Thus, we deduce from (1.11) the following inequality

    ddt(lϱ2HNl+lu2HNl+l+1d2HNl)+C0(lϱ2HNl+lu2HNl+l+1d2HNl)1+1l+s0,forl=1,,N1.

    Solving this inequality directly gives

    lϱHNl+luHNl+l+1dHNlC(1+t)l+s2,forl=1,,N1. (3.17)

    Then, by (3.14), (3.17) and the interpolation, we obtain the following inequality holds for s[0,12]:

    lϱHNl+luHNl+l+1dHNlC(1+t)l+s2,forl=0,1,,N1. (3.18)

    Second, we consider the decay estimate for s(12,32). Notice that the arguments for s[0,12] can not be applied to this case. However, observing that we have ϱ0,u0,d0˙H12 hold since ˙HsL2˙Hs for any s[0,s], we can deduce from (3.18) for (1.10) and (1.11) with s=12 that the following estimate holds:

    lϱ2HNl+lu2HNl+ld2HNlC0(1+t)12l,forl=0,1,,N1. (3.19)

    Therefore, we deduce from (3.3) and (3.2) that for s(12,32),

    Es(t)Es(0)+Ct0d2H1Es(τ)dτ+Ct0(ϱL2+uL2+dL2)s12(ϱH1+uH1+2dH1)52sEs(τ)dτC0+Csupτ[0,t]Es(τ)+Ct0(1+τ)74+s2dτsupτ[0,t]Es(τ)C0+Csupτ[0,t]Es(τ), (3.20)

    which implies that (1.12) holds for s(12,32), i.e.,

    Λsϱ(t)2L2+Λsu(t)2L2+Λsd(t)2L2C0. (3.21)

    Moreover, thanks to (1.11) and (3.16), we can also obtain the following inequality for s(12,32):

    ddt(lϱ2HNl+lu2HNl+l+1d2HNl)+C0(lϱ2HNl+lu2HNl+l+1d2HNl)1+1l+s0,forl=1,,N1,

    which implies

    lϱHNl+luHNl+l+1dHNlC(1+t)l+s2,forl=1,,N1. (3.22)

    Next, using (3.21), (3.22), and Lemma 2.5, we easily obtain

    (ϱ,u,d)L2C((ϱ,u,d)L2)s1+s(Λs(ϱ,u,d)11+sL2C((ϱ,u,d)L2)s1+sC[(1+t)1+s2]s1+s=C(1+t)s2. (3.23)

    It then follows from (3.22) and (3.23) that

    ϱHNl+uHNl+dHNlC(1+t)s2.

    Hence, we obtain (1.15) for s(12,32) and complete the proof.

    In this paper, we consider the optimal decay estimates for the higher order derivatives of strong solutions for three-dimensional nematic liquid crystal system. We use the pure energy method, negative Sobolev norm estimates together with the classical Kato-Ponce inequality, Gagliardo-Nirenberg inequality, overcome the difficulties caused by the Ginzburg-Landau approximation and the coupling between the compressible Navier-Stokes equations and the direction equations, obtain the decay estimates. Since the result (1.16) is same to the decay of the heat equation, it is optimal. We remark that our results may attract the attentions of the researchers in the nematic liquid crystals filed.

    The author would like to thank the anonymous referees and Dr. Xiaopeng Zhao for their helpful suggestions. This paper was supported by the Fundamental Research Funds of Heilongjiang Province (grant No. 145109131).

    The author declares no conflict of interest.



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