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Research article Special Issues

Multi-objective Boolean grey wolf optimization based decomposition algorithm for high-frequency and high-utility itemset mining

  • Received: 18 January 2023 Revised: 14 April 2023 Accepted: 26 April 2023 Published: 25 May 2023
  • MSC : 05C85, 78M50

  • In itemset mining, the two vital goals that must be resolved from a multi-objective perspective are frequency and utility. To effectively address the issue, researchers have placed a great deal of emphasis on achieving both objectives without sacrificing the quality of the solution. In this work, an effective itemset mining method was formulated for high-frequency and high-utility itemset mining (HFUI) in a transaction database. The problem of HFUI is modeled mathematically as a multi-objective issue to handle it with the aid of a modified bio-inspired multi-objective algorithm, namely, the multi-objective Boolean grey wolf optimization based decomposition algorithm. This algorithm is an enhanced version of the Boolean grey wolf optimization algorithm (BGWO) for handling multi-objective itemset mining problem using decomposition factor. In the further part of this paper decomposition factor will be mentioned as decomposition. Different population initialization strategies were used to test the impact of the proposed algorithm. The system was evaluated with 12 different real-time datasets, and the results were compared with seven different recent existing multi-objective models. Statistical analysis, namely, the Wilcoxon signed rank test, was also utilized to prove the impact of the proposed algorithm. The outcome shows the impact of the formulated technique model over other standard techniques.

    Citation: N. Pazhaniraja, Shakila Basheer, Kalaipriyan Thirugnanasambandam, Rajakumar Ramalingam, Mamoon Rashid, J. Kalaivani. Multi-objective Boolean grey wolf optimization based decomposition algorithm for high-frequency and high-utility itemset mining[J]. AIMS Mathematics, 2023, 8(8): 18111-18140. doi: 10.3934/math.2023920

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  • In itemset mining, the two vital goals that must be resolved from a multi-objective perspective are frequency and utility. To effectively address the issue, researchers have placed a great deal of emphasis on achieving both objectives without sacrificing the quality of the solution. In this work, an effective itemset mining method was formulated for high-frequency and high-utility itemset mining (HFUI) in a transaction database. The problem of HFUI is modeled mathematically as a multi-objective issue to handle it with the aid of a modified bio-inspired multi-objective algorithm, namely, the multi-objective Boolean grey wolf optimization based decomposition algorithm. This algorithm is an enhanced version of the Boolean grey wolf optimization algorithm (BGWO) for handling multi-objective itemset mining problem using decomposition factor. In the further part of this paper decomposition factor will be mentioned as decomposition. Different population initialization strategies were used to test the impact of the proposed algorithm. The system was evaluated with 12 different real-time datasets, and the results were compared with seven different recent existing multi-objective models. Statistical analysis, namely, the Wilcoxon signed rank test, was also utilized to prove the impact of the proposed algorithm. The outcome shows the impact of the formulated technique model over other standard techniques.



    1. Introduction and main result

    This paper is concerned with the regularity criterion of the 3D Boussinesq equations with the incompressibility condition :

    {tu+uuΔu+π=θe3,tθ+uθΔθ=0,u=0,(u,θ)(x,0)=(u0,θ0)(x),xR3, (1.1)

    where u=u(x,t) and θ=θ(x,t) denote the unknown velocity vector field and the scalar function temperature, while u0, θ0 with u0=0 in the sense of distribution are given initial data. e3=(0,0,1)T. π=π(x,t) the pressure of fluid at the point (x,t)R3×(0,). The Boussinesq equation is one of important subjects for researches in nonlinear sciences [14]. There are a huge literatures on the incompressible Boussinesq equations such as [1,2,3,4,6,8,9,10,17,19,20,21,22] and the references therein.

    When θ=0, (1.1) reduces to the well-known incompressible Navier-Stokes equations and many results are available. Besides their physical applications, the Navier-Stokes equations are also mathematically significant. From that time on, much effort has been devoted to establish the global existence and uniqueness of smooth solutions to the Navier-Stokes equations.

    However, similar to the classic Navier-Stokes equations, the question of global regularity of the weak solutions of the 3D Boussinesq equations still remains a big open problem and the system (1.1) has received many studies. Based on some analysis technique, some regularity criteria via the velocity of weak solutions in the Lebesgue spaces, multiplier spaces and Besov spaces have been obtained in [5,17,19,20,22,23].

    More recently, the authors of the present paper [7] showed that the weak solution becomes regular if

    T0u(,t)21r.Br,+θ(,t)21r.Br,1+log(e+u(,t)Hs+θ(,t)Hs)dt< for some 0r<1 and s12, (1.2)

    where .Br, denotes the homogeneous Besov space. Definitions and basic properties of the Sobolev spaces and the Besov spaces can be find in [18]. For concision, we omit them here.

    The purpose of this paper is to improve the regularity criterion (1.2) in the following form.

    Theorem 1.1. Let (u,θ) be a smooth solution to (1.1) in [0,T) with the initial data (u0,θ0)H3(R3)×H3(R3) with divu0=0 in R3. Suppose that the solution (u,θ) satisfies

    T0u(,t)21r.Br,log(e+u(,t).Br,)dt< for some r with 0r<1. (1.3)

    Then it holds

    sup0tT(u(,t)2H3+θ(,t)2H3)<.

    That is, the solution (u,θ) can be smoothly extended after time t=T. In other word, if T is the maximal time existence of the solution, then

    T0u(,t)21r.Br,log(e+u(,t).Br,)dt<.

    Then the solution can be smoothly extended after t=T.

    Remark 1.1. The condition (1.3) can be regarded as a logarithmically improved version of the assumption

    T0u(,t)21r.Br,dt< for some r with 0r<1.

    For the case r=1, we have the following result.

    Theorem 1.2. Let (u,θ) be a smooth solution to (1.1) in [0,T) with the initial data (u0,θ0)H3(R3)×H3(R3) with divu0=0 in R3. Suppose that there exists a small positive constant η such that

    u(,t)L(0,T;.B1,(R3))η, (1.4)

    then solution (u,θ) can be smoothly extended after time t=T.

    Remark 1.2. Theorem 1.2 can be regarded as improvements and limiting cases of those in [7]. It is worth to point out all conditions are valid for the usual Navier-Stokes equations. We refer to a recent work [7] and references therein.

    Remark 1.3. For the case r=0, see [23].


    2. Proof of Theorem 1.1

    In this section, we will prove Theorem 1.1 by the standard energy method.

    Let T>0 be a given fixed time. The existence and uniqueness of local smooth solutions can be obtained as in the case of the Navier-Stokes equations. Hence, for all T>0 we assume that (u,θ) is a smooth solution to (1.1) on [0,T) and we will establish a priori bounds that will allow us to extend (u,θ) beyond time T under the condition (1.3).

    Owing to (1.3) holds, one can deduce that for any small ϵ>0, there exists T0=T0(ϵ)<T such that

    TT0u(,t)21r.Br,log(e+u(,t).Br,) dtϵ<<1. (2.1)

    Thanks to the divergence-free condition u=0, from (1.1)2, we get immediately the global a priori bound for θ in any Lebesgue space

    θ(,t)LqCθ0Lq for all q[2,] and all t[0,T].

    Now, multiplying (1.1)2 by θ and using integration by parts, we get

    12ddtθ2L2+θ2L2=0.

    Hence, we obtain

    θL(0,T;L2(R3))L2(0,T;H1(R3)). (2.2)

    Next, multiplying (1.1)1 by u, we have after integration by part,

    12ddtu2L2+u2L2=R3(θe3)udxθL2uL2CuL2,

    which yields

    uL(0,T;L2(R3))L2(0,T;H1(R3)), (2.3)

    where we used (2.2) and

    R3(uu)udx=12R3(u)u2dx=12R3(u)u2dx=0

    by incompressibility of u, that is, u=0.

    Now, apply operator to the equation of (1.1)1 and (1.1)2, then taking the inner product with u and θ, respectively and using integration by parts, we get

    12ddt(u2L2+θ2L2)+Δu2L2+Δθ2L2=R3(u)uudx+R3(θe3)udxR3(u)θθdx=I1+I2+I3. (2.4)

    Employing the Hölder and Young inequalities, we derive the estimation of the first term I1 as

    I1=R3(u)uΔudx(uu)L2ΔuL2Cu.Br,uHrΔuL2Cu.Br,u1rL2Δu1+rL212Δu2L2+Cu21r.Br,u2L212Δu2L2+Cu21r.Br,(u2L2+θ2L2),

    where we have used the inequality due to [16] :

    uuH1Cu.Br,uHr

    and the interpolation inequality

    w.Hs=|ξ|sˆwL2w1sL2wsL2 for all 0s1.

    The term I3 can be estimated as

    I3CuL2θ2L4CuL2θ.B1,ΔθL2CuL2θ.B0,ΔθL212Δθ2L2+Cθ2Lu2L212Δθ2L2+Cθ2L(u2L2+θ2L2),

    where we have used

    θ.B1,Cθ.B0,CθL.

    The term I2 can be estimated as

    I2uL2θL212(u2L2+θ2L2).

    Plugging all the estimates into (2.4) yields that

    ddt(u2L2+θ2L2)+Δu2L2+Δθ2L2C(12+u21r.Br,+θ2L)(u2L2+θ2L2).

    Hence, we obtain

    ddt(u(,t)2L2+θ(,t)2L2)+Δu2L2+Δθ2L2C[12+u21r.Br,+θ2Llog(e+u.Br,)](u2L2+θ2L2)log(e+u.Br,)C[12+u21r.Br,+θ2Llog(e+u.Br,)](u2L2+θ2L2)log(e+uH3+θH3)C[12+u21r.Br,+θ2Llog(e+u.Br,)](u2L2+θ2L2)log(e+κ(t))

    where κ(t) is defined by

    κ(t)=supT0τt(u(,τ)H3+θ(,τ)H3)forallT0<t<T.

    It should be noted that the function κ(t) is nondecreasing. Moreover, we have used the following fact :

    u.Br,CuH3.

    Integrating the above inequality over [T0,t] and applying Gronwall's inequality, we have

    u(,t)2L2+θ(,t)2L2+tTΔu(,τ)2L2+Δθ(,τ)2L2dτ(u(,T0)2L2+θ(,T0)2L2)×exp(CtT0u21r.Br,log(e+u(,τ).Br,)log(e+κ(τ))dτ)(u(,T0)2L2+θ(,T0)2L2)×exp(Clog(e+κ(t))tT0u21r.Br,log(e+u(,τ).Br,)dτ)˜Cexp(Cϵlog(e+κ(t)))=˜C(e+κ(t))Cϵ (2.5)

    where ˜C is a positive constant depending on u(,T0)2L2, θ(,T0)2L2, T0, T and θ0.

    H3norm. Next, we start to obtain the H3estimates under the above estimate (2.5). Applying Λ3=(Δ)32 to (1.1)1, then taking L2 inner product of the resulting equation with Λ3u, and using integration by parts, we obtain

    12ddtΛ3u(,t)2L2+Λ4u(,t)2L2=R3Λ3(uu)Λ3udx+R3Λ3(θe3)Λ3udx (2.6)

    Similarly, applying Λ3=(Δ)32 to (1.1)2, then taking L2 inner product of the resulting equation with Λ3θ, and using integration by parts, we obtain

    12ddtΛ3θ(,t)2L2+Λ4θ(,t)2L2=R3Λ3(uθ)Λ3θdx, (2.7)

    Using u=0, we deduce that

    12ddt(Λ3u(,t)2L2+Λ3θ(,t)2L2)+Λ4u(,t)2L2+Λ4θ(,t)2L2=R3[Λ3(uu)uΛ3u]Λ3udx+R3Λ3(θe3)Λ3udx3R3[Λ3(uθ)uΛ3θ]Λ3θdx=Π1+Π2+Π3. (2.8)

    To bound Π1, we recall the following commutator estimate due to [12]:

    Λα(fg)fΛαgLpC(Λα1gLq1fLp1+ΛαfLp2gLq2), (2.9)

    for α>1, and 1p=1p1+1q1=1p2+1q2. Hence Π1 can be estimated as

    Π1CuL3Λ3u2L3Cu34L2Λ3u14L2u13L2Λ4u53L216Λ4u2L2+Cu132L2Λ3u32L2, (2.10)

    where we used (2.9) with α=3,p=32, p1=q1=p2=q2=3, and the following Gagliardo-Nirenberg inequalities

    {uL3Cu34L2Λ3u14L2,Λ3uL3Cu16L2Λ4u56L2. (2.11)

    If we use the existing estimate (2.1) for T0t<T, (2.10) reduces to

    Π112Λ4u2L2+˜C(e+κ(t))32+132Cϵ. (2.12)

    Using (2.11) again, we get

    Π3C(uL3Λ3θL3+θL3Λ3uL3)Λ3θL3C(uL3+θL3)(Λ3u2L3+Λ3θ2L3)16(Λ4u2L2+Λ4θ2L2)+˜C(e+κ(t))32+132Cϵ.

    For Π2, we have

    Π212(Λ3u2L2+Λ3θ2L2)˜C(e+κ(t))2.

    Inserting all the inequalities into (2.8) and absorbing the dissipative terms, one finds

    ddt(Λ3u(,t)2L2+Λ3θ(,t)2L2)˜C(e+κ(t))32+132Cϵ+˜C(e+κ(t))2, (2.13)

    with together with the basic energy (2.2)-([2.3]) yields

    ddt(u(,t)2H3+θ(,t)2H3)˜C(e+κ(t))32+132Cϵ+˜C(e+κ(t))2, (2.14)

    Choosing ϵ sufficiently small provided that 132Cϵ<12 and applying the Gronwall inequality to (2.14), we derive that

    supT0τt(u(,τ)2H3+θ(,τ)2H3)˜C<, (2.15)

    where ˜C depends on u(,T0)2L2 and θ(,T0)2L2.

    Noting that the right-hand side of (2.15) is independent of t for , we know that (u(,T),θ(,T))H3(R3)×H3(R3). Consequently, (u,θ) can be extended smoothly beyond t=T. This completes the proof of Theorem 1.1.


    3. Proof of Theorem 1.2

    In order to prove Theorem 1.2, we first recall the following local existence theorem of the three-dimensional Boussinesq equations.

    Lemma 3.1. Suppose (u,θ)Lα(R3), for some α3 and u=0. Then, there exists T0>0 and a unique solution of (1.1) on [0,T0) such that

    (u,θ)BC([0,T0);Lα(R3))Ls([0,T0);Lr(R3)),t1suBC([0,T0);Lα(R3)) (3.1)

    Moreover, let (0,T) be the maximal interval such that (u,θ) solves (1.1) in C((0,T);Lα(R3)), α>3. Then for any t(0,T)

    u(,t)LαC(Tt)α32α and θ(,t)LαC(Tt)α32α,

    with the constant C independent of T and α.

    Let (u,θ) be a strong solution satisfying

    (u,θ)Lα((0,T);Lβ(R3)) for 2α+3β=1 and β>3.

    Then (u,θ) belongs to C(R3×(0,T)).

    Proof. For all T>0, we assume that (u,θ) is a smooth solution to (1.1) on [0,T) and we will establish a priori bounds that will allow us to extend (u,θ) beyond time T under the condition (1.4).

    Similar to the proof of Theorem 1.1, we can show that

    (u,θ)L(0,T;L2(R3))L2(0,T;H1(R3)). (3.2)

    The proof of Theorem 1.2 is divided into steps.

    Step Ⅰ. H1estimation. In order to get the H1estimates, we apply operator to the equation of (1.1)1 and (1.1)2, multiply by u and θ, respectively to obtain

    12ddt(u(,t)2L2+θ(,t)2L2)+Δu(,t)2L2+Δθ(,t)2L2=R3(u)uudx+R3(θe3)udxR3(u)θθdx=I1+I2+I3. (3.3)

    Next we estimate I1,I2 and I3 in another way. Hence,

    I1u3L3Cu.B2,Δu2L2Cu.B1,Δu2L2,

    where we have used the following interpolation inequality due to [16] :

    wL3Cw23L2w13.B2,.

    By means of the Hölder and Young inequalities, the term I3 can be estimated as

    I3CuL2θ2L4CuL2θ.B1,ΔθL2Cθ2.B0,Δθ2L2+Cu2L2Cθ2LΔθ2L2+Cu2L2,

    where we have used the following interpolation inequality due to [16] :

    θ2L4Cθ.B1,ΔθL2.

    The term I2 can be estimated as

    I2uL2θL212(u2L2+θ2L2).

    Plugging all the estimates into (3.3) yields that

    12ddt(u(,t)2L2+θ(,t)2L2)+Δu(,t)2L2+Δθ(,t)2L2Cu.B1,Δu2L2+Cθ2LΔθ2L2+C(u2L2+θ2L2).

    Under the assumption (1.4), we choose η small enough so that

    Cu.B1,12 .

    Hence, we find that

    ddt(u2L2+θ2L2)+Δu2L2+Δθ2L2C(u2L2+θ2L2).

    Integrating in time and applying the Gronwall inequality, we infer that

    u(,t)2L2+θ(,t)2L2+T0(Δu(,τ)2L2+Δθ(,τ)2L2)dτC. (3.4)

    Step Ⅱ. H2estimation. Next, we start to obtain the H2estimates under the above estimate (3.4). Applying Δ to (1.1)1, then taking L2 inner product of the resulting equation with Δu, and using integration by parts, we obtain

    12ddtΔu(,t)2L2+Λ3u(,t)2L2=R3Δ(uu)Δudx+R3Δ(θe3)Δudx (3.5)

    Similarly, applying Δ to (1.1)2, then taking L2 inner product of the resulting equation with Δθ, and using integration by parts, we obtain

    12ddtΔθ(,t)2L2+Λ3θ(,t)2L2=R3Δ(uθ)Δθdx. (3.6)

    Adding (3.5) and (3.6), we deduce that

    12ddt(Δu(,t)2L2+Δθ(,t)2L2)+Λ3u(,t)2L2+Λ3θ(,t)2L2=R3Δ(uu)Δudx+R3Δ(θe3)ΔudxR3Δ(uθ)Δθdx=K1+K2+K3. (3.7)

    Using Hölder's inequality and Young's inequality, K1 can be estimated as

    K1=R3Δ(uu)ΔudxΔ(uu)L2ΔuL2CuLΔuL2Λ3uL212Λ3u2L2+Cu2LΔu2L2.

    Here we have used the bilinear estimates due to Kato-Ponce [12] and Kenig-Ponce-Vega [13]:

    Λα(fg)LpC(ΛαgLq1fLp1+ΛαfLp2gLq2),

    for α>0, and 1p=1p1+1q1=1+1q2.

    From the incompressibility condition, Hölder's inequality and Young's inequality, one has

    K3=R3Δ(uθ)ΔθdxΔ(uθ)L2ΔθL2C(uLΔθL2+θLΔuL2)Λ3θL212Λ3θ2L2+C(u2L+θ2L)(Δu2L2+Δθ2L2).

    For K2, we have

    K212(Δu2L2+Δθ2L2)

    Inserting all the inequalities into (3.7) and absorbing the dissipative terms, one finds

    ddt(Δu(,t)2L2+Δθ(,t)2L2)+Λ3u(,t)2L2+Λ3θ(,t)2L2C(u2L+θ2L)(Δu2L2+Δθ2L2). (3.8)

    Using the following interpolation inequality

    fLCf14L2Δf34L2,

    together with the key estimate (3.4) yield that

    T0(u(,τ)2L+θ(,τ)2L)dτC<.

    Applying the Gronwall inequality to (3.8), we derive that

    Δu(,t)2L2+Δθ(,t)2L2+T0(Λ3u(,t)2L2+Λ3θ(,t)2L2)dtC. (3.9)

    By estimates (3.4) and (3.9) as well as the following Gagliardo-Nirenberg's inequality

    fL6Cf12L2Δf12L2,

    it is easy to see that

    (u,θ)L4(0,T;L6(R3)),

    from which and Lemma 3.1 the smoothness of (u,θ) follows immediately. This completes the proof of Theorem 1.2.


    Acknowledgments

    Part of the work was carried out while the first author was long term visitor at University of Catania. The hospitality and support of Catania University are graciously acknowledged.

    All authors would like to thank Professor Bo-Qing Dong for helpful discussion and constant encouragement. They also would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the quality of the paper.


    Conflict of Interest

    All authors declare no conflicts of interest in this paper.




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