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An optimistic firefly algorithm-based deep learning approach for sentiment analysis of COVID-19 tweets

  • The unprecedented rise in the number of COVID-19 cases has drawn global attention, as it has caused an adverse impact on the lives of people all over the world. As of December 31, 2021, more than 2, 86, 901, 222 people have been infected with COVID-19. The rise in the number of COVID-19 cases and deaths across the world has caused fear, anxiety and depression among individuals. Social media is the most dominant tool that disturbed human life during this pandemic. Among the social media platforms, Twitter is one of the most prominent and trusted social media platforms. To control and monitor the COVID-19 infection, it is necessary to analyze the sentiments of people expressed on their social media platforms. In this study, we proposed a deep learning approach known as a long short-term memory (LSTM) model for the analysis of tweets related to COVID-19 as positive or negative sentiments. In addition, the proposed approach makes use of the firefly algorithm to enhance the overall performance of the model. Further, the performance of the proposed model, along with other state-of-the-art ensemble and machine learning models, has been evaluated by using performance metrics such as accuracy, precision, recall, the AUC-ROC and the F1-score. The experimental results reveal that the proposed LSTM + Firefly approach obtained a better accuracy of 99.59% when compared with the other state-of-the-art models.

    Citation: H. Swapnarekha, Janmenjoy Nayak, H. S. Behera, Pandit Byomakesha Dash, Danilo Pelusi. An optimistic firefly algorithm-based deep learning approach for sentiment analysis of COVID-19 tweets[J]. Mathematical Biosciences and Engineering, 2023, 20(2): 2382-2407. doi: 10.3934/mbe.2023112

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  • The unprecedented rise in the number of COVID-19 cases has drawn global attention, as it has caused an adverse impact on the lives of people all over the world. As of December 31, 2021, more than 2, 86, 901, 222 people have been infected with COVID-19. The rise in the number of COVID-19 cases and deaths across the world has caused fear, anxiety and depression among individuals. Social media is the most dominant tool that disturbed human life during this pandemic. Among the social media platforms, Twitter is one of the most prominent and trusted social media platforms. To control and monitor the COVID-19 infection, it is necessary to analyze the sentiments of people expressed on their social media platforms. In this study, we proposed a deep learning approach known as a long short-term memory (LSTM) model for the analysis of tweets related to COVID-19 as positive or negative sentiments. In addition, the proposed approach makes use of the firefly algorithm to enhance the overall performance of the model. Further, the performance of the proposed model, along with other state-of-the-art ensemble and machine learning models, has been evaluated by using performance metrics such as accuracy, precision, recall, the AUC-ROC and the F1-score. The experimental results reveal that the proposed LSTM + Firefly approach obtained a better accuracy of 99.59% when compared with the other state-of-the-art models.



    In this paper we are concerned with the following problem

    {uttΔu+u+t0b(ts)Δu(s)ds+|ut|γ()2ut=uln|u|αinΩ×(0,+),u=uν=0,onΩ×(0,),u(x,0)=u0(x),ut(x,0)=u1(x),inΩ, (1.1)

    where Ω is a bounded domain of Rn with a smooth boundary Ω, ν is the unit outer normal to Ω, u0 and u1 are the given data, b is a relaxation function and γ(.) is a variable exponent.

    Problem (1.1) contains three class of problems:

    I. Viscoelasticity with wide class of relaxation functions.

    The importance of the viscoelastic properties of materials has been realized because of the rapid developments in rubber and plastics industry. Many advances in the studies of constitutive relations, failure theories and life prediction of viscoelastic materials and structures were reported and reviewed in the last two decades [1]. There is an extensive literature on the stabilization of viscoelastic wave equations and many results have been established. There are a lot of contributions to generalize the decay rates by allowing an extended class of relaxation functions and give general decay rates. In fact, the journey of generalization of relaxation functions passed through several steps, we mention here the following stages:

    1) As in [2], the relaxation function b satisfies, for two positive constants a1 and a2,

    a1b(t)b(t)a2b(t),t0.

    2)As in [3,4], the relaxation function b satisfies

    b(t)a(t)b(t), t0,

    where a:R+R+ is a nonincreasing differentiable function.

    3) As in [5], the relaxation function b satisfies

    b(t)χ(b(t)),

    where χ is a positive function, χ(0)=χ(0)=0, and χ is strictly increasing and strictly convex near the origin.

    4) As in [6], the relaxation function b satisfies

    b(t)a(t)bp(t), t0, 1p<32.

    5)As in [7], the relaxation function b satisfies

    b(t)a(t)B(b(t)), (1.2)

    where BC1(R), with B(0)=0 and B is linear or strictly increasing and strictly convex function C2 near the origin.

    II. Variable-exponent nonlinearity.

    With the advancement of sciences and technology, many physical and engineering models required more sophisticated mathematical functional spaces to be studied and well understood. For example, in fluid dynamics, the elecrtorheological fluids (smart fluids) have the property that the viscosity changes (often drastically) when exposed to an electrical field. The Lebesgue and Sobolev spaces with variable exponents proved to be efficient tools to study such problems as well as other models like fluids with temperature-dependent viscosity, nonlinear viscoelasticity, filtration processes through a porous media and image processing. More details on these problems can be found in [8,9]. For hyperbolic problems involving variable-exponent nonlinearities, we refer to [10,11,12,13,14,15]. For more results of other problems with the nonlinearity of power type, we refer the interested reader to see [16,17,18].

    III. Logarithmic source term.

    The logarithmic nonlinearity appears naturally in inflation cosmology and supersymmetric filed theories, quantum mechanics and nuclear physics [19,20]. Problems with logarithmic nonlinearity have a lot of applications in many branches of physics such as nuclear physics, optics and geophysics [21,22,23].

    In this paper, we consider problem (1.1) and prove the global existence of solutions, using the well-depth method. We then establish explicit and general decay results of the solution under suitable assumptions on the variable exponent γ(.) and very general assumption on the relaxation function. To the best of our knowledge, such a problem has not been discussed before in the context of nonlinearity with variable exponents.

    In addition to the introduction, this paper has four other sections. In Section 2, we present some preliminaries. The Existence is given in Section 3. In Section 4, we establish some technical lemmas needed for the proof of the main results. Our stability results and their proof are given in Section 5.

    In this section, we present some preliminaries about the logarithmic nonlinerity and the Lebesgue and Sobolev spaces with variable exponents (see [24,25,26,27]). Throughout this paper, c is used to denote a generic positive constant.

    Definition 2.1. Let β:Ω[1,] be a measurable function, where Ω is a bounded domain of Rn, then we have the following definitions:

    1) The Lebesgue space with a variable exponent β() is defined by

    Lβ()(Ω):={v:ΩR;measurable  inΩ:ϱβ()(kv)<,for  somek>0},

    where ϱβ()(v)=Ω1β(x)|v(x)|β(x)dx is a modular.

    2) The variable-exponent Sobolev space W1,β()(Ω) is:

    W1,β()(Ω)={vLβ()(Ω)such  thatvexistsand|v|Lβ()(Ω)}.

    3) W1,β()0(Ω) is the closure of C0(Ω) in W1,β()(Ω).

    Remark 2.2. [9]

    1) Lβ()(Ω) is a Banach space equipped with the following Luxembourg-type norm

    vβ():=inf{λ>0:Ω|v(x)λ|β(x)dx1},

    2) W1,β()(Ω) is a Banach space with respect to the norm

    vW1,β()(Ω)=vβ()+vβ().

    Definition 2.3. Let K be a convex function on (0,r], then the convex conjugate of K, in the sense of Young (see [32]), is defined as follows:

    K(s)=s(K)1(s)K[(K)1(s)],ifs(0,K(r)] (2.1)

    and K satisfies the following generalized Young inequality

    α1α2K(α1)+K(α2),ifα1(0,K(r)],α2(0,r]. (2.2)

    Let

    β1:=essinfxΩβ(x),β2:=esssupxΩβ(x).

    Lemma 2.4. [9] If β:Ω[1,) is a measurable function with β2<, then C0(Ω) is dense in Lβ()(Ω).

    Remark 2.5 (Log-Hölder continuity condition). The exponent p():Ω[1,] is said to be satisfying the log-Hölder continuity condition; if there exists a constant c>0 such that, for all δ with 0<δ<1,

    |p(x)p(y)|clog|xy|,for  allx,yΩ,with|xy|<δ. (2.3)

    Lemma 2.6. [9][Poincaré's Inequality] Let Ω be a bounded domain of Rn and p() satisfies (2.3), then

    vp()cvp(),for  allvW1,p()0(Ω).

    In particular, the space W1,p()0(Ω) has an equivalent norm given by vW1,p()0(Ω)=vp().

    Lemma 2.7. [9][Embedding Property] Let Ω be a bounded domain in Rn with a smooth boundary Ω. Assume that p,kC(¯Ω) such that

    1<p1p(x)p2<+,1<k1k(x)k2<+,x¯Ω,

    and k(x)<p(x) in ¯Ω with

    p(x)={np(x)np(x),if  p2<n;+,if  p2n,

    then we have continuous and compact embedding W1,p(.)(Ω)Lk(.)(Ω). So, there exists ce>0 such that

    vkcevW1,p(.),vW1,p(.)(Ω).

    Lemma 2.8. [27] Let ϵ(0,1). Then there exists βε>0 such that

    s|lns|s2+βϵs1ϵ,s>0. (2.4)

    We consider the following hypotheses:

    (A1) The relaxation function b:R+R+ is a C1 nonincreasing function satisfying

    b(0)>0,10b(s)ds=ˉb>0, (2.5)

    and there exists a C1 function B:(0,)(0,) which is strictly increasing and strictly convex C2 function on (0,r], rb(0), with B(0)=B(0)=0, such that

    b(t)a(t)B(b(t)),t0, (2.6)

    where a is a positive nonincreasing differentiable function.

    (A2) γ:¯Ω[1,) is a continuous function satisfies the log-Hölder continuity condition (Remark 2.5) such that

    γ1:=essinfxΩγ(x),γ2:=esssupxΩγ(x).

    and 1<γ1<γ(x)γ2, where

    {γ2<,n=1,2;γ22nn2,n3.

    (A3) The constant α in (1.1) satisfies 0<α<α0, where α0 is the positive real number satisfying

    2πˉbα0=e321α0 (2.7)

    where .2=.L2(Ω).

    Lemma 2.9. [28,29] (Logarithmic Sobolev inequality) Let u be any function in H10(Ω) and d be any positive real number. Then

    Ωu2ln|u|dx12u22lnu22+d22πu22(1+lnd)u22. (2.8)

    Lemma 2.10. There exists a unique α0>0 such that

    e321s<2πˉbs,s(0,α0). (2.9)

    Proof. Let g(s)=2πˉbse321s, then g is a continuous and decreasing function on (0,), with

    lims0+g(s)=andlimxg(x)=e32.

    Then, there exists a unique α0>0 such that g(α0)=0 and (2.9) holds

    Remark 2.11. Lemma 2.10 shows that the selection of α in (A3) is possible.

    Remark 2.12. Using the facts that B(0)=0 and B is strictly convex on (0,r], then

    B(θs)θB(s), 0θ1  and  s(0,r]. (2.10)

    Remark 2.13. [7] If B is a strictly increasing and strictly convex C2 function on (0,r], with B(0)=B(0)=0, then there is a strictly convex and strictly increasing C2 function ¯B:[0,+)[0,+) which is an extension of B. For simplicity, in the rest of this paper, we use B instead of ¯B.

    In this section, we state the local existence theorem whose proof can be established by combining the arguments of [10,30,31]. Also, we state and prove a global existence result under smallness conditions on the initial data (u0,u1).

    Theorem 3.1 (Local Existence). Suppose conditions (A1)-(A3) hold and (u0,u1)H10(Ω)×L2(Ω). Then, there exists T>0, such that problem (1.1) has a weak solution

    uL((0,T),H10(Ω)),utL((0,T),L2(Ω))Lγ(.)(Ω×(0,T)).

    Definition 3.2. We define the following functionals which are needed for establishing the global existence

    E(t)=12[ut22+(1t0b(s)ds)u22+(bu)(t)+α+22u22]12Ωu2ln|u|αdx (3.1)

    where for vL2loc(R+;L2(Ω)),

    (bv)(t):=t0b(ts)v(t)v(s)22ds.

    E(t) represents the modified energy functional associated to problem (1.1).

     I(u)=I(u(t))=(1t0b(s)ds)u22+u22+(bou)(t)Ωu2ln|u|αdx (3.2)
     J(u)=J(u(t))=12I(u(t))+α4u22, (3.3)

    then

    E(t)=12||ut(t)||22+J(u(t)). (3.4)

    Notation: We define

    ρ=e2D0αα,E1=12D0ρ2α4ρ2lnρ2

    and

    D0=α+22+α(1+lnd),

    where 0<d<2πˉbα.

    Lemma 3.3. Assume that (u0,u1)H10(Ω)×L2(Ω), (A1) holds,

    u02<ρ  and  0<E(0)<E1. (3.5)

    Then, I(u(t))0 for all t[0,T).

    Proof. First, we show that u2<ρ, t[0,T). By (2.5), (3.4) and (2.9), we obtain

    E(t)J(u(t))ˉb2u22+12u22+12(bou)(t)12Ωu2ln|u|αdx+α4u2212(ˉbαd22π)u22+12(α+22+α(1+lnd)α2lnu22)u22 (3.6)

    If we select d<2πˉbα, then (3.6) becomes

    E(t)Z(ρ)=12D0ρ2α4ρ2lnρ2 (3.7)

    where D0=α+22+α(1+lnd) and ρ=u2. Using (3.7), we can deduce that that Z is increasing on (0,ρ), decreasing on (ρ,+) and Z(ρ) as ρ+. Moreover,

    max0<ρ<+Z(ρ)=12D0ρ2α4ρ2lnρ2=Z(ρ)=E1.

    Suppose that u(x,t)2<ρ is not true in [0,T). Therefore, using the continuity of u(t), it follows that there exists 0<t0<T such that u(x,t0)2=ρ. From Eq (3.7), we can see that

    E(t0)Z(u(x,t0)2)=Z(ρ)=E1,

    which is a contradiction with E(t)E(0)<E1 for all t0. Recalling the definition of I(u(t)), and using (2.9) with d<2πˉbα, for all t[0,T), lead to

    I(u(t))ˉbu22Ωu2ln|u|αdx(ˉbαd22π)u22+(1+α(1+lnd)α2lnu22)u22(ˉbαd22π)u22+u220. (3.8)

    This completes the proof.

    Remark 3.4. We can see that if u02<ρ and E(0)<E1, then J(u(t))0 and consequently E(t)0 for all t[0,T). Therefore, from (3.8), for t[0,T) we have

    ut222E(t)2E(0),u222π2πˉbαd2I(t)4π2πˉbαd2E(t)4π2πˉbαd2E(0), (3.9)

    which shows that the soultion is global and bounded in time.

    In this section, we establish several lemmas needed for the proof of our main result.

    Lemma 4.1. The energy functional associated to problem (1.1) satisfies, for any t0,

    E(t)=12(bu)(t)12b(t)u22Ω|ut|γ(x)dx0. (4.1)

    Proof. Multiplying (1.1) by ut, integrating over Ω and using the boundary conditions, imply (4.1).

    Lemma 4.2. [31] Assume that b satisfies (A1). Then, for uH10(Ω),

    Ω(t0b(ts)(u(t)u(s))ds)2dxc(bou)(t),

    and

    Ω(t0b(ts)(u(t)u(s))ds)2dxc(bou)(t).

    Lemma 4.3. [7] Assume (A1) holds. Then, for any tt0,, we have

    a(t)t00b(s)u(t)u(ts)22dscE(t).

    Lemma 4.4. Assume that (A1)-(A3) and (3.5) hold, then the functional

    I1(t):=Ωuutdx

    satisfies, along with the solution of (1.1), the estimates:

    I1(t)||ut||22u22ˉb4||u(t)||22+c(bou)(t)+cΩ|ut|γ(x)dx+Ωu2ln|u|αdx,for  γ12 (4.2)

    and

    I1(t)||ut||22u22ˉb4||u(t)||22+c(bou)(t)+cΩ|ut|γ(x)dx+(Ω|ut|γ(x))γ11+Ωu2ln|u|αdx,for1<γ1<2. (4.3)

    Proof. Differentiate I1 and use the differential equation in (1.1), to get

    I1(t)=||ut||22u22(1t0b(s)ds)||u||22+Ωu(t)t0b(ts)(u(s)u(t))dsdxΩu|ut|γ(x)2utdx+Ωu2ln|u|αdx. (4.4)

    Young's inequality and (4.2) give

    Ωu.t0b(ts)(u(s)u(t))dsdxδ0Ω|u|2dx+c4δ0(bou)(t). (4.5)

    Estimation of the term Ωu|ut|γ(x)2utdx:

    We use Young's inequality with p(x)=γ(x)γ(x)1 and p(x)=γ(x) so, for all xΩ, we have

    |ut|γ(x)2utuδ|u|γ(x)+cδ(x)|ut|γ(x),

    where

    cδ(x)=δ1γ(x)(γ(x))γ(x)(γ(x)1)γ(x)1.

    Hence,

    Ωu|ut|γ(x)2utdxδΩ|u|γ(x)dx+Ωcδ(x)|ut|γ(x)dx. (4.6)

    Now, using (3.1), (4.1), (3.9) and Lemma 2.7, we obtain

    Ω|u|γ(x)dxΩ+|u|γ(x)dx+Ω|u|γ(x)dxΩ+|u|γ2dx+Ω|u|γ1dxΩ|u|γ2dx+Ω|u|γ1dx(cγ1e||u||γ12+cγ2e||u||γ22)(cγ1e||u||γ122+cγ2e||u||γ222)||u||22(cγ1e(4π2πˉbαd2E(0))γ12+cγ2e(4π2πˉbαd2E(0))γ22)||u||22c||u||22, (4.7)

    where

    Ω+={xΩ:|u(x,t)|1}andΩ={xΩ:|u(x,t)|<1},

    and

    c=(cγ1e(4π2πˉbαd2E(0))γ12+cγ2e(4π2πˉbαd2E(0))γ22).

    Then, (4.6) and (4.7) yield

    Ωu|ut|γ(x)utdxδc||u||22+Ωcδ(x)|ut|γ(x)dx. (4.8)

    Combining the above results with fixing δ0=ˉb2 and δ=ˉb4c completes the proof of (4.2).

    For the proof of (4.3), we re-estimate the fifth term in (4.4) as follows:

    First, we define

    Ω1={xΩ:γ(x)<2}andΩ2={xΩ:γ(x)2}.

    Then, we get

    Ωu|ut|γ(x)2utdx=Ω1u|ut|γ(x)2utdxΩ2u|ut|γ(x)2utdx. (4.9)

    Using the definition of Ω1, we have

    2γ(x)2<γ(x),and2γ(x)22γ12. (4.10)

    Therefore, using Young's and Poincaré's inequalities and (4.10), we obtain

    Ω1u|ut|γ(x)2utdxθΩ1|u|2dx+14θΩ1|ut|2γ(x)2dxθc2||u||22+c[Ω+1|ut|2γ(x)2dx+Ω1|ut|2γ(x)2dx]θc2||u||22+c[Ω+1|ut|γ(x)dx+Ω1|ut|2γ12dx]θc2||u||22+c[Ω|ut|γ(x)dx+(Ω1|ut|2dx)γ11]θc2||u||22+c[Ω|ut|γ(x)dx+(Ω1|ut|γ(x)dx)γ11]θc2||u||22+c[Ω|ut|γ(x)dx+(Ω|ut|γ(x)dx)γ11], (4.11)

    where

    Ω+1={xΩ1:|ut(x,t)|1}andΩ1={xΩ1:|ut(x,t)|<1}. (4.12)

    After setting θ=ˉb8c2, (4.11) becomes

    Ω1u|ut|γ(x)2utdxˉb8||u||22+c[Ω|ut|γ(x)dx+(Ω|ut|γ(x)dx)γ11]. (4.13)

    Next, for any δ we have, by the case γ(x)2,

    Ω2u|ut|γ(x)2utdxδc||u||22+Ωcδ(x)|ut|γ(x)dx. (4.14)

    Therefore, by combining (4.9)-(4.14), we arrive at

    I1(t)||ut||22(3ˉb8cδ)||u(t)||22+c(bou)(t)+c[Ω(1+cδ(x))|ut|γ(x)dx+(Ω|ut|γ(x))γ11]+Ωu2ln|u|αdx.

    By fixing δ=ˉb8c, cδ(x) remains bounded and, consequently, we obtain (4.3).

    Lemma 4.5. Assume that (A1)-(A3) and (3.5) hold, then for any δ>0, the functional

    I2(t):=Ωutt0b(ts)(u(t)u(s))dsdx

    satisfies, along the solution of (1.1), the estimates:

    I2(t)δu22(t0b(s)dsδ)ut22+Ωcδ(x)|ut|γ(x)dx+cδ(bou)(t)+cδ(bu)(t)+cϵ,δ(bou)11+ϵ(t),forγ12, (4.15)

    and for 1<γ1<2, we have the following estimate

    I2(t)δu22(t0b(s)dsδ)ut22+c(bu)(t)+cϵ,δ(bou)11+ϵ(t)+cδ(bou)(t)+cδ[Ω|ut|γ(x)dx+(Ω|ut|γ(x)dx)γ11] (4.16)

    Proof. Direct differentiation of I2, using (1.1), yields

    I2(t)=Ωut0b(ts)(u(t)u(s))dsdxΩut0b(ts)(u(t)u(s))dsdxΩ(t0b(ts)u(s)ds)(t0b(ts)(u(t)u(s))ds)dxΩutt0b(ts)(u(t)u(s))dsdx(t0b(s)ds)ut22+Ω|ut|γ(x)2utt0b(ts)(u(t)u(s))dsdxαΩuln|u|t0b(ts)(u(t)u(s))dsdx=(1t0b(s)ds)Ωut0b(ts)(u(t)u(s))dsdxΩut0b(ts)(u(t)u(s))dsdx+Ω(t0b(ts)(u(t)u(s))ds)2dxΩutt0b(ts)(u(t)u(s))dsdx(t0b(s)ds)ut22+Ω|ut|γ(x)2utt0b(ts)(u(t)u(s))dsdxαΩuln|u|t0b(ts)(u(t)u(s))dsdx. (4.17)

    Using Young's inequality and Lemma 4.2, we obtain

    (1t0b(s)ds)Ωu.t0b(ts)(u(t)u(s))dsdxcδu22+cδ(bou)(t). (4.18)

    The use of Lemma 4.2, Young's and Poincaré's inequalities leads to

    Ωut0b(ts)(u(t)u(s))dsdxcδ||u||22+cδ(bou)(t) (4.19)

    Exploiting Lemma (4.2) and Young's inequality, we obtain

    Ωutt0b(ts)(u(t)u(s))dsdxδut22+cδ(bou)(t). (4.20)

    Next, for almost every xΩ fixed, we have

    t0b(ts)|u(t)u(s)|ds(t0b(s)ds)γ(x)1γ(x)(t0b(ts)|u(t)u(s)|γ(x)ds)1γ(x)(1ˉb)γ(x)1γ(x)(t0b(ts)|u(t)u(s)|γ(x)ds)1γ(x). (4.21)

    Therefore, for almost every xΩ, we have

    |t0b(ts)|u(t)u(s)|ds|γ(x)(1ˉb)γ11t0b(ts)|u(t)u(s)|γ(x)ds. (4.22)

    By using Young's, Hölder's and Poincaré's inequalities and Lemma 4.2, we get

    Ω|ut|γ(x)2utt0b(ts)(u(t)u(s))dsdxδΩ|t0b(ts)(u(t)u(s))ds|γ(x)dx+Ωcδ(x)|ut|γ(x)dxδ(1ˉb)γ11Ωt0b(ts)|(u(t)u(s)|γ(x)dsdx+Ωcδ(x)|ut|γ(x)dx, (4.23)

    where

    cδ(x)=δ1γ(x)(γ(x))γ(x)(γ(x)1)γ(x)1.

    Similarly, we have

    Ωt0b(ts)|(u(t)u(s)|γ(x)dsdxΩ+t0b(ts)|(u(t)u(s)|γ2dsdx+Ωt0b(ts)|(u(t)u(s)|γ1dsdxt0b(ts)||(u(t)u(s)||γ2γ2ds+t0b(ts)||(u(t)u(s)||γ1γ1ds[cγ2e(4π2πˉbαd2E(0))γ222+cγ1e(4π2πˉbαd2E(0))γ122]t0b(ts)||(u(t)u(s)||22ds. (4.24)

    Therefore,

    Ω|ut|γ(x)2utt0b(ts)(u(t)u(s))dsdxcδ(1ˉb)γ11(bu)(t)+Ωcδ(x)|ut|γ(x)dx, (4.25)

    where c=[cγ2e(4π2πˉbαd2E(0))γ222+cγ1e(4π2πˉbαd2E(0))γ122].

    For the last term in (4.17), the use of (2.4), Young's, Cauchy-Schwarz' and Poincaré's inequalities, the embedding theorem and Lemma 4.2 leads to, for any δ>0,

    Ωuln|u|αt0b(ts)(u(t)u(s))dsdxαΩ(u2+βϵ|u|1ϵ)|t0b(ts)(u(t)u(s))dsdx|cΩ|u|2|t0b(ts)(u(t)u(s))ds|dx+δΩu2dx+cϵ,δΩ|t0b(ts)(u(t)u(s))ds|21+ϵdxcδ||u||22+cδΩ|t0b(ts)(u(t)u(s))ds|2dx+cϵ,δΩ|t0b(ts)(u(t)u(s))ds|21+ϵdxcδ||u||22+cδ(bou)(t)+cϵ,δ(bou)11+ϵ(t).

    Combining the above estimates with (4.17), we obtain (4.15).

    For the proof of (4.16), we re-estimate the fifth term in (4.17) as follows:

    Ω|ut|γ(x)2utt0b(ts)(u(t)u(s))dsdxδΩ|t0b(ts)(u(t)u(s))ds|2dx+cδΩ|ut|2γ(x)2dxδ(1ˉb)(bu)(t)+cδΩ|ut|2γ(x)2dxcδ(bu)(t)+cδΩ1|ut|2γ(x)2dx+cδΩ2|ut|2γ(x)2dxcδ(bu)(t)+cδ(Ω|ut|γ(x)dx+(Ω|ut|γ(x)dx)γ11). (4.26)

    Then (4.16) is established.

    Lemma 4.6. Given t0>0. Assume that (A1)-(A3) and (3.5) hold. Then,

    L(t):=N1E(t)+N2I1(t)+I2(t)

    satisfies, for a suitable choice of N1,N2>0 and for some positive constants λ0 and c, the estimates, for any tt0,

    L(t)λ0E(t)+c(bou)(t)+cϵ(bou)11+ϵ(t),forγ12, (4.27)

    and

    L(t)cE(t)+c(bu)(t)+cϵ(bou)11+ϵ(t)+c(E(t))γ11,for1<γ1<2. (4.28)

    Proof. Since b is positive and b(0)>0 then, for any t0>0, we have

    t0b(s)dst00b(s)ds=b0>0, tt0.

    By using (4.1), (4.2) and (4.15), then, for tt0 and any λ0>0, we have

    L(t)λ0E(t)(N2δˉb2+λ0(1b0)2)|| u||22(N2(b0δ)1λ02)||ut||22+c(bou)(t)+(12N14cN22)(bou)(t)+(1λ02)Ωu2ln|u|αdx+(1λ0(α+2)4)u22.

    Using the Logarithmic Sobolev inequality, for 0<λ0<12, we get

    L(t)λ0E(t)(N2δˉb2+λ0(1b0)2(1λ02)αd22π)|| u||22(N2(b0δ)1λ02)||ut||22+c(bou)(t)+(12N14cˉbN22)(bou)(t)(1α2(1λ02)lnu22+α(1+lnd)(1λ02)λ0(α+2)4)u22.

    At this point, we select λ0 and α so small that

    1α2(1λ02)lnu22+α(1+lnd)(1λ02)λ0(α+2)4>0.

    Then, we choose N2 large enough so that:

    N2δˉb2+λ0(1b0)2(1λ02)αd22π>0

    and

    N2(b0δ)1λ02>0,

    and then N1 large enough that

    N14cˉbN22>0.

    Therefore, we arrive at the desired result (4.27). On the other hand, we can choose N1 even larger (if needed) so that

    LE. (4.29)

    In this section, we establish our main decay results. For this purpose, we need the following remarks and lemma.

    Remark 5.1. Using (3.6) and (4.1), we get

    (bou)(t)=(bou)ϵ1+ϵ(t)(bou)11+ϵ(t)c(bou)11+ϵ(t). (5.1)

    Remark 5.2. In the case of B is linear and since a is nonincreasing, we have

    a(t)(bu)11+ϵ(t)=(aϵ(t)a(t)(bu)(t))11+ϵ(aϵ(0)a(t)(bu)(t))11+ϵc(a(t)(bu)(t))11+ϵc(E(t))11+ϵ. (5.2)

    Lemma 5.3. If (A1)-(A2) are satisfied, then we have the following estimate

    (bou)(t)tε0B1(ε0ψ(t)ta(t)),t>0, (5.3)

    where ε0 is small enough and the functional ψ is defined by

    ψ(t):=(bou)(t)cE(t), (5.4)

    Proof. To establish (5.3), let us define the following functional

    Λ(t):=ε0tt0||u(t)u(ts)||22ds,t>0. (5.5)

    Then, using (3.1), (4.1) and the dentition of Λ(t), we have

    Λ(t)2ε0t(t0||u(t)||22+t0||u(ts)||22ds).4ε0ˉbt(t0(E(t)+E(ts))ds)8ε0ˉbtt0E(s)ds8ε0ˉbtt0E(0)ds=8ε0ˉbE(0)<+. (5.6)

    Thus, ε0 can be chosen so small so that, for all t>0,

    Λ(t)<1. (5.7)

    Without loss of the generality, for all t>0, we assume that Λ(t)>0, otherwise we get an exponential decay from (4.27). The use of Jensen's inequality and using (5.4), (2.10) and (5.7) gives

    ψ(t)=1ε0Λ(t)t0Λ(t)(b(s))Ωε0|u(t)u(ts)|2dxds1ε0Λ(t)t0Λ(t)a(s)B(b(s))Ωε0|u(t)u(ts)|2dxdsa(t)ε0Λ(t)t0B(Λ(t)b(s))Ωε0|u(t)u(ts)|2dxdsta(t)ε0B(ε0tt0b(s)Ω|u(t)u(ts)|2dxds), (5.8)

    hence (5.3) is established.

    Theorem 5.4 (The case: γ12). Assume that (A1)-(A3) and (3.5) hold. Let (u0,u1)H10(Ω)×L2(Ω). Then, there exist positive constants c, t0 and t1 such that the solution of (1.1) satisfies,

    E(t)c(1+tt0a1+ϵ(s)ds)1ϵ,tt0,if  B  is  linear (5.9)

    and

    E(t)ct11+ϵB21(ct11+ϵtt1a(s)ds),tt1,if  B  is  nonlinear, (5.10)

    where B2(s)=sB(ε1s) and B(t)=([B1]11+ϵ)1(t).

    Proof. Case 1: B is linear

    We multiply (4.27) by a(t) and use (5.1) and (5.2) to get

    a(t)L(t)λ0a(t)E(t)+c(E(t))11+ϵ,tt0. (5.11)

    Multiply (5.11) by aϵ(t)Eϵ(t), and recall that a0, to obtain

    aϵ+1(t)Eϵ(t)L(t)λ0aϵ+1(t)Eϵ+1(t)+c(aE)ϵ(t)(E(t))1ϵ+1,tt0.

    Use of Young's inequality, with q=ϵ+1 and q=ϵ+1ϵ, gives, for any ε>0,

    aϵ+1(t)Eϵ(t)L(t)λ0aϵ+1(t)Eϵ+1(t)+c(εaϵ+1(t)Eϵ+1cεE(t))=(λ0εc)aϵ+1(t)Eϵ+1cE(t),tt0.

    We then choose 0<ε<λ0c and use that a0 and E0, to get, for c1=λ0εc,

    (aϵ+1EϵL)(t)aϵ+1(t)Eϵ(t)L1(t)c1aϵ+1(t)Eϵ+1(t)cE(t),tt0,

    which implies

    (aϵ+1EϵL+cE)(t)c1aϵ+1(t)Eϵ+1(t),tt0,

    where L1=aϵ+1EϵL+cE. Then L1E (thanks to (4.29)) and

    L1(t)caϵ+1(t)Lϵ+11(t), tt0.

    Integrating over (t0,t) and using the fact that L1E, we obtain (5.9).

    Case 2: B is non-linear.

    Using (4.27), (5.1) and (5.3), we obtain, tt0,

    L(t)λ0E(t)+ct11+ϵ[B1(ε0ψ(t)ta(t))]11+ϵ. (5.12)

    Combining the strictly increasing property of ¯B and the fact that 1t<1 whenever t>1, we obtain

    B1(ε0ψ(t)ta(t))B1(ε0ψ(t)t11+ϵa(t)) (5.13)

    then, (5.12) becomes, for tt1=max{t0,1},

    L(t)λ0E(t)+ct11+ϵ[B1(ε0ψ(t)t11+ϵa(t))]11+ϵ. (5.14)

    Set

    B(t)=([B1]11+ϵ)1(t),χ(t)=ε0ψ(t)t11+ϵa(t) (5.15)

    Using the facts that B>0 and B>0 on (o,r], (5.14) reduces to

    L(t)λ0E(t)+ct11+ϵB1(χ(t)),tt1 (5.16)

    Now, for ε1<r and using (5.16) and the fact that E0, B>0,B>0 on (0,r], we find that the functional L2, defined by

    L2(t):=B(ε1t11+ϵE(t)E(0))L(t),

    satisfies, for some c1,c2>0.

    c1L2(t)E(t)c2L2(t) (5.17)

    and, for all tt1,

    L2(t)λ0E(t)B(ε1t11+ϵE(t)E(0))+ct11+ϵB(ε1t11+ϵE(t)E(0))B1(χ(t)). (5.18)

    So, using (2.1) and (2.2) with α1=B(ε1t11+ϵE(t)E(0)) and α2=B1(χ(t)), we arrive at

    L2(t)λ0E(t)B(ε1t11+ϵE(t)E(0))+ct11+ϵ0B(G(ε1t11+ϵE(t)E(0)))+ct11+ϵχ(t)λ0E(t)B(ε1t11+ϵ0E(t)E(0))+cε1E(t)E(0)B(ε1t11+ϵ0E(t)E(0))+ct11+ϵ0χ(t). (5.19)

    Then, multiplying (5.19) by a(t) and using (5.4), (5.15), we get

    a(t)L2(t)λ0a(t)E(t)B(ε1t11+ϵ0E(t)E(0))+cε1a(t)E(t)E(0)B(ε1t11+ϵ0E(t)E(0))cE(t),tt1.

    Using the non-increasing property of a, we obtain, for all tt1,

    (aL2+cE)(t)λ0a(t)E(t)B(ε1t11+ϵE(t)E(0))+cε1a(t)E(t)E(0)B(ε1t11+ϵE(t)E(0))

    Therefore, by setting L3:=aL2+cEE, we conclude that

    L3(t)λ0a(t)E(t)B(ε1t11+ϵE(t)E(0))+cε1a(t)E(t)E(0)B(ε1t11+ϵE(t)E(0)).

    This gives, for a suitable choice of ε1,

    L3(t)ca(t)(E(t)E(0))B(ε1t11+ϵE(t)E(0)),tt1

    or

    c(E(t)E(0))B(ε1t11+ϵE(t)E(0))a(t)L3(t),tt1 (5.20)

    An integration of (5.20) yields

    tt1c(E(s)E(0))B(ε1s11+ϵE(s)E(0))a(s)dstt1L3(s)dsL3(t1). (5.21)

    Using the facts that B,B>0 and the non-increasing property of E, we deduce that the map tE(t)B(ε1t11+ϵE(t)E(0)) is non-increasing and consequently, we have

    c(E(t)E(0))B(ε1t11+ϵ0E(t)E(0))tt1a(s)dstt1c(E(s)E(0))B(ε1s11+ϵE(s)E(0))a(s)dsL3(t1),tt1 (5.22)

    Multiplying each side of (5.22) by 1t11+ϵ, we have

    (1t11+ϵE(t)E(0))B(ε1t11+ϵE(t)E(0))tt1a(s)dsct11+ϵ,tt1 (5.23)

    Next, we set B2(s)=sB(ε1s) which is strictly increasing, and consequently we obtain,

    B2(1t11+ϵE(t)E(0))tt1a(s)dsct11+ϵ,tt1 (5.24)

    Finally, we infer

    E(t)ct11+ϵB21(ct11+ϵtt1a(s)ds). (5.25)

    This finishes the proof.

    The following examples illustrate the results of Theorem 5.4:

    Example 1. Let b(t)=c1ec2(1+t), where c2>0 and c1>0 is small enough so that (A1) holds. Then b(t)=a(t)B(b(t)) where B(t)=t and a(t)=c. Therefore, we can use (5.9) to deduce

    E(t)c(1+t)1ϵ. (5.26)

    Example 2. Let b(t)=c1(1+t)q, where q>1+ϵ and c1 is chosen so that hypothesis (A1) is satisfied. Then

    b(t)=aB(b(t)),withB(s)=sq+1q,

    where a is a fixed constant. Then, (5.10) gives,

    E(t)ctq1ϵ(1+ϵ)2(q+1). (5.27)

    To establish the stability result in the case 1<γ1<2, we need the following lemma:

    Lemma 5.5. The energy functional E(t) satisfies the following estimate:

    [E(t)]11+ε+[E(t)]γ11c[E(t)]γε, (5.28)

    where γε=min{γ11,11+ε}.

    Proof. Using (2.5), (3.1), (3.3), (3.6) and Lemma 3.3, we have

    E(t)=J(t)+12ut(t)22J(t)ˉb2u(t)22,

    then, using (4.1),

    u(t)222ˉbE(t)2ˉbE(0). (5.29)

    So, from (4.1), (4.7) and using Young's inequality, we get

    |E(t)|=12b(t)u(t)2212(bou)(t)Ω|ut|γ(x)dx12b(t)u(t)22t0b(ts)(u(t)22+u(s)22)ds+cu222l(12b(t)+2b(0)2b(t)+c)E(0)cE(0). (5.30)

    Setting γε=min{γ11,11+ε} and using (5.30), we obtain

    [E(t)]11+ε+[E(t)]γ11[E(t)]γε[E(t)]11+εγε+[E(t)]γε[E(t)]γ11γε((cE(0))11+εγε+(cE(0))γ11γε)[E(t)]γε, (5.31)

    which completes the proof of Lemma 5.5.

    Theorem 5.6 (The case: 1<γ1<2). Assume that (A1)-(A3) and (3.5) hold. Let (u0,u1)H10(Ω)×L2(Ω). Then, there exist positive constants C, k2,k3 such that the energy functional associated to problem (1.1) satisfies

    E(t)C(tt0a1γε(s)ds)γε1γε,tt0,if  B  is  linear, (5.32)

    and, if B is nonlinear, we have

    E(t)k3t11+ϵB31(k2t11+ϵtt1a(s)ds),t>t1, (5.33)

    where γε=min{γ11,11+ε}, B3(s)=sB(ε3s)and B(s)=([B1]11+ϵ)1(s).

    Proof. Case B is linear.

    Multiplying (4.28) by a(t) and combining (2.6), (3.1), (5.2) and (5.28), we obtain, for some m1>0,

    a(t)L(t)m1a(t)E(t)+c[E(t)]11+ε+ca(t)[E(t)]γ11m1a(t)E(t)c+c[E(t)]γε,t>t0. (5.34)

    Let L:=aL+cEE, multiply both sides of the above estimate by aqEq, with q=1γε1 and apply Young's inequality, to get,

    aqEq(t)L(t)(m1ϵ2)aq+1(t)Eq+1(t)cE(t),tt0.

    Set L1:=aqEqL+cEE, take ϵ2 small enough and use the non-increasing property of E we obtain, for some m2,m3>0,

    L1(t)m2aq+1(t)Eq+1(t)m3aq+1(t)Lq+12(t),tt0.

    A simple integration over (t0,t) and using the equivalence LE, we obtain,

    E(t)C(tt0a1γε(s)ds)γε1γε,tt0.

    Case B is nonlinear.

    Using (4.27), (5.1) and (5.3), we obtain, tt0,

    L(t)λ0E(t)+ct11+ϵ[B1(ε0I(t)ta(t))]11+ϵ+c[E(t)]γ11. (5.35)

    Using (5.13)-(5.15), (5.35) reduces to

    L(t)λ0E(t)+ct11+ϵB1(χ(t))+c[E(t)]γ11,tt1 (5.36)

    Now, for ε3<r and using (5.16) and the fact that E0, H>0,H>0 on (0,r], we find that the functional F, defined by

    F(t):=B(ε3t11+ϵE(t)E(0))L(t),

    satisfies

    FE (5.37)

    and, for all tt1,

    F(t)λ0E(t)B(ε3t11+ϵE(t)E(0))+ct11+ϵB(ε3t11+ϵE(t)E(0))B1(χ(t))+cB(ε3t11+ϵE(t)E(0))[E(t)]γ11. (5.38)

    After applying with the generalized Young inequality

    we arrive at

    F(t)λ0E(t)B(ε3t11+ϵE(t)E(0))+ct11+ϵ0B(B(ε3t11+ϵE(t)E(0)))+cB(ε3t11+ϵE(t)E(0))[E(t)]γ11+ct11+ϵχ(t)λ0E(t)B(ε3t11+ϵE(t)E(0))+cε1E(t)E(0)B(ε3t11+ϵE(t)E(0))+ct11+ϵχ(t)cεE+ε[B]12γ1(ε3t11+ϵE(t)E(0)). (5.39)

    Using the facts that 12γ1>1 and B(ε3t11+ϵE(t)E(0)) is bounded, we have

    [B]12γ1(ε3t11+ϵE(t)E(0))cB(ε3t11+ϵE(t)E(0)). (5.40)

    Then, multiplying (5.39) by a(t), using (5.15), (5.40) and the fact that E(t)>0, we get

    a(t)F1(t)λ0a(t)E(t)B(ε3t11+ϵE(t)E(0))+cε5a(t)E(t)E(0)B(ε3t11+ϵE(t)E(0))+cεa(t)E(t)B(ε3t11+ϵE(t)E(0))cE(t),tt1.

    where F1=F+cεE. Using the non-increasing property of a, we obtain, for all tt1,

    (aF1+cE)(t)λ0a(t)E(t)H(ε3t11+ϵE(t)E(0))+cε5a(t)E(t)E(0)B(ε3t11+ϵE(t)E(0))+cεa(t)E(t)B(ε3t11+ϵE(t)E(0)).

    Therefore, by setting F2:=aF1+cEE, we conclude that

    F2(t)λ0a(t)E(t)B(ε3t11+ϵE(t)E(0))+cε3a(t)E(t)E(0)B(ε3t11+ϵE(t)E(0))+cεa(t)E(t)B(ε3t11+ϵE(t)E(0)).

    This gives, for a suitable choice of ε3 and ε,

    F2(t)ka(t)(E(t)E(0))B(ε3t11+ϵE(t)E(0)),tt1

    or

    k(E(t)E(0))B(ε3t11+ϵ0E(t)E(0))a(t)F2(t),tt1 (5.41)

    An integration of (5.41) yields

    tt1k(E(s)E(0))B(ε3s11+ϵE(s)E(0))a(s)dstt1F2(s)dsF2(t1). (5.42)

    Using the facts that B,B>0 and the non-increasing property of E, we deduce that the map tE(t)B(ε3t11+ϵE(t)E(0)) is non-increasing and consequently, we have

    k(E(t)E(0))B(ε3t11+ϵE(t)E(0))tt1a(s)dstt1k(E(s)E(0))B(ε3s11+ϵE(s)E(0))a(s)dsF2(t1),tt1 (5.43)

    Multiplying each side of (5.43) by 1t11+ϵ, we have

    (kt11+ϵE(t)E(0))B(ε3t11+ϵ0E(t)E(0))tt1a(s)dsk2t11+ϵ,tt1 (5.44)

    Using the fact that {\mathcal{B}_3}(s) = s \mathcal{B}^{\prime}(\varepsilon_{3}s) is strictly increasing, we obtain

    \begin{equation} k \mathcal{B}_{3} \left(\frac{1}{t^{\frac{1}{1+\epsilon}}} \cdot \frac{E(t)}{E(0)}\right) \int_{t_1}^{t} a(s) ds \leq \frac{k_2}{t^{\frac{1}{1+\epsilon}}}, \quad \forall t\ge t_1 \end{equation} (5.45)

    Finally, we infer

    \begin{equation} E(t) \leq k_3 t^{\frac{1}{1+\epsilon}} {\mathcal{B}_{3}}^{-1} \left( \frac{k_2}{t^{\frac{1}{1+\epsilon}}\int_{t_1}^{t}a(s) ds } \right). \end{equation} (5.46)

    This finishes the proof.

    The following examples illustrate the results of Theorem 5.6:

    Example 3. Let b(t) = c_1 e^{-c_2(1+t)}, where c_2 > 0 and c_1 > 0 is small enough so that (A1) holds. Then b^{\prime}(t) = -a(t) B(b(t)) where B(t) = t and a(t) = c . Therefore, (5.32) gives for t > t_0 and \epsilon \in (0, 1) ,

    \begin{equation} E(t) \leq c {(t-t_0)^\frac{\gamma_\epsilon-1}{\gamma_\epsilon}}. \end{equation} (5.47)

    Example 4. Let b(t) = \frac{c_1}{(1+t)^q} , where q > 1+\epsilon and c_1 is chosen so that hypothesis (A1) is satisfied. Then

    b^{\prime}(t) = -aB(b(t)), \quad {with} \quad B(s) = s^{\frac{q+1}{q}},

    where a is a fixed constant. Then, (5.33) gives, for t > t_1 and \epsilon \in (0, 1) ,

    \begin{equation} E(t)\leq \frac{c}{t^{\frac{q-1-\epsilon}{(1+\epsilon)^2 (q+1)}}}. \end{equation} (5.48)

    Remark 5.7. The classical power-type nonlinearity term in [33] provides a canonical description for the dynamics analysis of a quasi-wave propagation in a nonlinear process, therefore, the fast cumulative of such nonlinear interactions results in a significant effect to the solution under large spatial and temporal scales. However, the logarithmic nonlinearity in (1.1) only expresses slowly cumulative of nonlinear, thus giving another kind of description for dynamic process. Let us note here that though the logarithmic nonlinearity is somehow weaker than the polynomial nonlinearity, both the existence and stability result are not obtained by straightforward application of the method used for polynomial nonlinearity.

    The authors would like to express their profound gratitude to King Fahd University of Petroleum and Minerals (KFUPM)- Interdisciplinary Research Center (IRC) for Construction and Building Materials for their continuous supports. The authors also thank the referee for her/his very careful reading and valuable comments. This work is funded by KFUPM under Project #SB191037.

    The authors declare that there is no conflict of interest regarding the publication of this paper.



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