Research article Special Issues

Asymptotic flocking for the three-zone model

  • Received: 06 July 2020 Accepted: 15 October 2020 Published: 05 November 2020
  • We prove the asymptotic flocking behavior of a general model of swarming dynamics. The model describing interacting particles encompasses three types of behavior: repulsion, alignment and attraction. We refer to this dynamics as the three-zone model. Our result expands the analysis of the so-called Cucker-Smale model where only alignment rule is taken into account. Whereas in the Cucker-Smale model, the alignment should be strong enough at long distance to ensure flocking behavior, here we only require that the attraction is described by a confinement potential. The key for the proof is to use that the dynamics is dissipative thanks to the alignment term which plays the role of a friction term. Several numerical examples illustrate the result and we also extend the proof for the kinetic equation associated with the three-zone dynamics.

    Citation: Fei Cao, Sebastien Motsch, Alexander Reamy, Ryan Theisen. Asymptotic flocking for the three-zone model[J]. Mathematical Biosciences and Engineering, 2020, 17(6): 7692-7707. doi: 10.3934/mbe.2020391

    Related Papers:

    [1] Awatif Nadia, Abdul Hasib Chowdhury, Esheta Mahfuj, Md. Sanwar Hossain, Khondoker Ziaul Islam, Md. Istianatur Rahman . Determination of transmission reliability margin using AC load flow. AIMS Energy, 2020, 8(4): 701-720. doi: 10.3934/energy.2020.4.701
    [2] Malhar Padhee, Rajesh Karki . Bulk system reliability impacts of forced wind energy curtailment. AIMS Energy, 2018, 6(3): 505-520. doi: 10.3934/energy.2018.3.505
    [3] Awatif Nadia, Md. Sanwar Hossain, Md. Mehedi Hasan, Sinthia Afrin, Md Shafiullah, Md. Biplob Hossain, Khondoker Ziaul Islam . Determination of transmission reliability margin for brownout. AIMS Energy, 2021, 9(5): 1009-1026. doi: 10.3934/energy.2021046
    [4] Armando L. Figueroa-Acevedo, Michael S. Czahor, David E. Jahn . A comparison of the technological, economic, public policy, and environmental factors of HVDC and HVAC interregional transmission. AIMS Energy, 2015, 3(1): 144-161. doi: 10.3934/energy.2015.1.144
    [5] Li Bin, Muhammad Shahzad, Qi Bing, Muhammad Ahsan, Muhammad U Shoukat, Hafiz MA Khan, Nabeel AM Fahal . The probabilistic load flow analysis by considering uncertainty with correlated loads and photovoltaic generation using Copula theory. AIMS Energy, 2018, 6(3): 414-435. doi: 10.3934/energy.2018.3.414
    [6] Gul Ahmad Ludin, Mohammad Amin Amin, Ahmad Shah Irshad, Soichiro Ueda, Zakirhussain Farhad, M. H. Elkholy, Tomonobu Senjyu . Power transmission in Afghanistan: Challenges, opportunities and proposals. AIMS Energy, 2024, 12(4): 840-871. doi: 10.3934/energy.2024040
    [7] Baseem Khan, Hassan Haes Alhelou, Fsaha Mebrahtu . A holistic analysis of distribution system reliability assessment methods with conventional and renewable energy sources. AIMS Energy, 2019, 7(4): 413-429. doi: 10.3934/energy.2019.4.413
    [8] Albert K. Awopone, Ahmed F. Zobaa . Analyses of optimum generation scenarios for sustainable power generation in Ghana. AIMS Energy, 2017, 5(2): 193-208. doi: 10.3934/energy.2017.2.193
    [9] Arben Gjukaj, Rexhep Shaqiri, Qamil Kabashi, Vezir Rexhepi . Renewable energy integration and distributed generation in Kosovo: Challenges and solutions for enhanced energy quality. AIMS Energy, 2024, 12(3): 686-705. doi: 10.3934/energy.2024032
    [10] Gerardo Guerra, Juan A. Martinez-Velasco . A review of tools, models and techniques for long-term assessment of distribution systems using OpenDSS and parallel computing. AIMS Energy, 2018, 6(5): 764-800. doi: 10.3934/energy.2018.5.764
  • We prove the asymptotic flocking behavior of a general model of swarming dynamics. The model describing interacting particles encompasses three types of behavior: repulsion, alignment and attraction. We refer to this dynamics as the three-zone model. Our result expands the analysis of the so-called Cucker-Smale model where only alignment rule is taken into account. Whereas in the Cucker-Smale model, the alignment should be strong enough at long distance to ensure flocking behavior, here we only require that the attraction is described by a confinement potential. The key for the proof is to use that the dynamics is dissipative thanks to the alignment term which plays the role of a friction term. Several numerical examples illustrate the result and we also extend the proof for the kinetic equation associated with the three-zone dynamics.


    The classical beta function

    B(δ1,δ2)=0tδ11(1t)δ21dt,((δ1)>0,(δ2)>0) (1.1)

    and its relation with well known gamma function is given by

    B(δ1,δ2)=Γ(δ1)Γ(δ2)Γ(δ1+δ2),(δ1)>0,(δ2)>0.

    The Gauss hypergeometric, confluent hypergeometric and Appell's functions which are respectively defined by(see [27])

    2F1(δ1,δ2;δ3;z)=n=0(δ1)n(δ2)n(δ3)nznn!,(|z|<1),    (δ1,δ2,δ3C  and  δ30,1,2,3,), (1.2)

    and

    1Φ1(δ2;δ3;z)=n=0(δ2)n(δ3)nznn!,(|z|<1),    (δ2,δ3C  and  δ30,1,2,3,). (1.3)

    The Appell's series or bivariate hypergeometric series is defined by

    F1(δ1,δ2,δ3;δ4;x,y)=m,n=0(δ1)m+n(δ2)m(δ3)nxmyn(δ4)m+nm!n!; (1.4)

    for all δ1,δ2,δ3,δ4C,δ40,1,2,3,,|x|,|y|<1<1.

    The integral representation of hypergeometric, confluent hypergeometric and Appell's functions are respectively defined by

    2F1(δ1,δ2;δ3;z)=Γ(δ3)Γ(δ2)Γ(δ3δ2)10tδ21(1t)δ3δ21(1zt)δ1dt, (1.5)
    ((δ3)>(δ2)>0,|arg(1z)|<π),

    and

    1Φ1(δ2;δ3;z)=Γ(δ3)Γ(δ2)Γ(δ3δ2)10tδ21(1t)δ3δ21eztdt, (1.6)
    ((δ3)>(δ2)>0).
    F1(δ1,δ2,δ3;δ4;x,y)=Γ(δ4)Γ(δ1)Γ(δ4δ1)10tδ11(1t)δ4δ11(1xt)δ2(1yt)δ3dt. (1.7)

    The k-gamma function, k-beta function and the k-Pochhammer symbol introduced and studied by Diaz and Pariguan [5]. The integral representation of k-gamma function and k-beta function respectively given by

    Γk(z)=kzk1Γ(zk)=0tz1ezkkdt,(z)>0,k>0 (1.8)
    Bk(x,y)=1k10txk1(1t)yk1dt,(x)>0,(y)>0. (1.9)

    Here, we recall the following relations (see [5]).

    Bk(x,y)=Γk(x)Γk(y)Γk(x+y), (1.10)
    (z)n,k=Γk(z+nk)Γk(z), (1.11)

    where (z)n,k=(z)(z+k)(z+2k)(z+(n1)k);(z)0,k=1 and k>0

    and

    n=0(α)n,kznn!=(1kz)αk. (1.12)

    These studies were followed by Mansour [16], Kokologiannaki [13], Krasniqi [14] and Merovci [17]. In 2012, Mubeen and Habibullah [18] defined the k-hypergeometric function as

    2F1,k(δ1,δ2;δ3;z)=n=0(δ1)n,k(δ2)n,k(δ3)n,kznn!, (1.13)

    where δ1,δ2,δ3C and δ30,1,2, and its integral representation is given by

    2F1,k(δ1,δ2;δ3;z)=1kBk(δ2,δ3δ2)×10tδ2k1(1t)δ3δ2k1(1ktz)δ1kdt. (1.14)

    The k-Riemann-Liouville (R-L) fractional integral using k-gamma function introduced in [19]:

    (Iαkf(t))(x)=1kΓk(α)x0f(t)(xt)αk1dt,k,αR+. (1.15)

    Later on Mubeen and Iqbal [11] established the improved version of Gruss type inequalities by utilizing k-fractional integrals. In [1], Agarwal et al. presented certain Hermite-Hadamard type inequalities for generalized k-fractional integrals. Set et al. [29] presented an integral identity and generalized Hermite–Hadamard type inequalities for Riemann–Liouville fractional integral. Mubeen et al. [24] established integral inequalities of Ostrowski type for k-fractional Riemann–Liouville integrals. Recently, many researchers have introduced generalized version of k-fractional integrals and investigated a large bulk of various inequalities via the said fractional integrals. The interesting readers are referred to see the work of [9,10,26,30]. Farid et al. [7] introduced Hadamard k-fractional integrals. In [8] introduced Hadamard-type inequalities for k-fractional Riemann-Liouville integrals. In [12,31], the authors established certain inequalities by utilizing Hadamard-type inequalities for k-fractional Riemann-Liouville integrals. In [25], Nisar et al. established certain Gronwall type inequalities associated with Riemann-Liouville k- and Hadamard k-fractional derivatives and their applications. In [25], they presented dependence solutions of certain k-fractional differential equations of arbitrary real order with initial conditions. Recently, Samraiz et al. [28] defined an extension of Hadamard k-fractional derivative and proved its various properties.

    The solution of some integral equations involving confluent k-hypergeometric functions and k-analogue of Kummer's first formula are given in [22,23]. While the k-hypergeometric and confluent k-hypergeometric differential equations are introduced in [20]. In 2015, Mubeen et al. [21] introduced k-Appell hypergeometric function as

    F1,k(δ1,δ2,δ3;δ4;z1,z2)=m,n=0(δ1)m+n,k(δ2)m,k(δ3)m,k(δ4)m+n,kzm1zn2m!n! (1.16)

    for all δ1,δ2,δ3,δ4C,δ40,1,2,3,,max{|z1|,|z2|}<1k and k>0. Also, Mubeen et al. defined its integral representation as

    F1,k(δ1,δ2,δ3;δ4;z1,z2)=1kBk(δ1,δ4δ1)10tδ1k1(1t)δ4δ1k1(1kz1t)δ2k(1kz2t)δ3kdt, (1.17)
    ((δ4)>(δ1)>0).

    In this section, we recall the following definition of fractional derivatives from and give a new extension called Riemann-Liouville k-fractional derivative.

    Definition 2.1. The well-known R-L fractional derivative of order μ is defined by

    Dμx{f(x)}=1Γ(μ)x0f(t)(xt)μ1dt,(μ)<0. (2.1)

    For the case m1<(μ)<m where m=1,2,, it follows

    Dμx{f(x)}=dmdxmDμmx{f(x)}=dmdxm{1Γ(μ+m)x0f(t)(xt)μ+m1dt}. (2.2)

    For further study and applications, we refer the readers to the work of [2,3,4,15,32]. In the following, we define Riemann-Liouville k-fractional derivative of order μ as

    Definition 2.2.

    kDμx{f(x)}=1kΓk(μ)x0f(t)(xt)μk1dt,(μ)<0,kR+. (2.3)

    For the case m1<(μ)<m where m=1,2,, it follows

    kDμx{f(x)}=dmdxmkDμmkx{f(x)}=dmdxm{1kΓk(μ+mk)x0f(t)(xt)μk+m1dt}. (2.4)

    Note that for k=1, definition 2.2 reduces to the classical R-L fractional derivative operator given in definition 2.1.

    Now, we are ready to prove some theorems by using the new definition 2.2.

    Theorem 1. The following formula holds true,

    kDμz{zηk}=zημkΓk(μ)Bk(η+k,μ),(μ)<0. (2.5)

    Proof. From (2.3), we have

    kDμz{zηk}=1kΓk(μ)z0tηk(zt)μk1dt. (2.6)

    Substituting t=uz in (2.6), we get

    kDμz{zηk}=1kΓk(μ)10(uz)ηk(zuz)μk1zdu=zημkkΓk(μ)10uηk(1u)μk1du.

    Applying definition (1.9) to the above equation, we get the desired result.

    Theorem 2. Let (μ)>0 and suppose that the function f(z) is analytic at the origin with its Maclaurin expansion given by f(z)=n=0anzn where |z|<ρ for some ρR+. Then

    kDμz{f(z)}=n=0ankDμz{zn}. (2.7)

    Proof. Using the series expansion of the function f(z) in (2.3) gives

    kDμz{f(z)}=1kΓk(μ)z0n=0antn(zt)μk1dt.

    As the series is uniformly convergent on any closed disk centered at the origin with its radius smaller then ρ, therefore the series so does on the line segment from 0 to a fixed z for |z|<ρ. Thus it guarantee terms by terms integration as follows

    kDμz{f(z)}=n=0an{1kΓk(μ)z0tn(zt)μk1dt=n=0ankDμz{zn},

    which is the required proof.

    Theorem 3. The following result holds true:

    kDημz{zηk1(1kz)βk}=Γk(η)Γk(μ)zμk12F1,k(β,η;μ;z), (2.8)

    where (μ)>(η)>0 and |z|<1.

    Proof. By direct calculation, we have

    kDημz{zηk1(1kz)βk}=1kΓk(μη)z0tηk1(1kt)βk(zt)μηk1dt=zμηk1kΓk(μη)z0tηk1(1kt)βk(1tz)μηk1dt.

    Substituting t=zu in the above equation, we get

    kDημz{zηk1(1kz)βk}=zμk1kΓk(μη)10uηk1(1kuz)βk(1u)μηk1zdu.

    Applying (1.14) and after simplification we get the required proof.

    Theorem 4. The following result holds true:

    kDημz{zηk1(1kaz)αk(1kbz)βk}=Γk(η)Γk(μ)zμk1F1,k(η,α,β;μ;az,bz), (2.9)

    where (μ)>(η)>0, (α)>0, (β)>0, max{|az|,|bz|}<1k.

    Proof. To prove (2.9), we use the power series expansion

    (1kaz)αk(1kbz)βk=m=0n=0(α)m,k(β)n,k(az)mm!(bz)nn!.

    Now, applying Theorem 1, we obtain

    kDημz{zηk1(1kaz)αk(1kbz)βk}=m=0n=0(α)m,k(β)n,k(a)mm!(b)nn!kDημz{zηk+m+n1}=m=0n=0(α)m,k(β)n,k(a)mm!(b)nn!βk(η+mk+nk,μη)Γk(μη)zμk+m+n1=m=0n=0(α)m,k(β)n,k(a)mm!(b)nn!Γk(η+mk+nk)Γk(μ+mk+nk)zμk+m+n1.

    In view of (1.16), we get

    kDημz{zηk1(1kaz)αk(1kbz)βk}=Γk(η)Γk(μ)zμk1F1,k(η,α,β;μ;az,bz).

    Theorem 5. The following Mellin transform formula holds true:

    M{exkDμz(zηk);s}=Γ(s)Γk(μ)Bk(η+k,μ)zημk, (2.10)

    where (η)>1, (μ)<0, (s)>0.

    Proof. Applying the Mellin transform on definition (2.3), we have

    M{exkDμz(zηk);s}=0xs1exkDμz(zη);s}dx=1kΓk(μ)0xs1ex{z0tηk(zt)μk1dt}dx=zμk1kΓk(μ)0xs1ex{z0tηk(1tz)μk1dt}dx=zημkkΓk(μ)0xs1ex{10uηk(1u)μk1du}dx

    Interchanging the order of integrations in above equation, we get

    M{exkDμz(zηk);s}=zημkkΓk(μ)10uηk(1u)μk1(0xs1exdx)du.=zημkkΓk(μ)Γ(s)10uηk(1u)μk1du=Γ(s)Γk(μ)Bk(η+k,μ)zημk,

    which completes the proof.

    Theorem 6. The following Mellin transform formula holds true:

    M{exkDμz((1kz)αk);s}=zμkΓ(s)Γk(μ)Bk(k,μ)2F1,k(α,k;μ+k;z), (2.11)

    where (α)>0, (μ)<0, (s)>0, and |z|<1.

    Proof. Using the power series for (1kz)αk and applying Theorem 5 with η=nk, we can write

    M{exkDμz((1kz)αk);s}=n=0(α)n,kn!M{exkDμz(zn);s}=Γ(s)kΓk(μ)n=0(α)n,kn!Bk(nk+k,μ)znμk=Γ(s)zμkΓk(μ)n=0Bk(nk+k,μ)(α)n,kznn!=Γ(s)zμkn=0Γk(k+nk)Γk(μ+k+nk)(α)n,kznn!=Γ(s)Γk(μ+k)zμkn=0(k)n,k(μ+k)n,k(α)n,kznn!=Γ(s)zμkΓk(μ)Bk(k,μ)2F1,k(α,k;μ+k;z),

    which is the required proof.

    Theorem 7. The following result holds true:

    kDημz[zηk1Eμk,γ,δ(z)]=zμk1kΓk(μη)n=0(μ)n,kΓk(γn+δ)Bk(η+nk,μη)znn!, (2.12)

    where γ,δ,μC, (p)>0, (q)>0, (μ)>(η)>0 and Eμk,γ,δ(z) is k-Mittag-Leffler function (see [6]) defined as:

    Eμk,γ,δ(z)=n=0(μ)n,kΓk(γn+δ)znn!. (2.13)

    Proof. Using (2.13), the left-hand side of (2.12) can be written as

    kDημz[zηk1Eμk,γ,δ(z)]=kDημz[zηk1{n=0(μ)n,kΓk(γn+δ)znn!}].

    By Theorem 2, we have

    kDημz[zηk1Eμk,γ,δ(z)]=n=0(μ)n,kΓk(γn+δ){kDμz[zηk+n1]}.

    In view of Theorem 1, we get the required proof.

    Theorem 8. The following result holds true:

    kDημz{zηk1mΨn[(αi,Ai)1,m;|z(βj,Bj)1,n;]}=zμk1kΓk(μη)×n=0mi=1Γ(αi+Ain)nj=1Γ(βj+BjnBk(η+nk,μη)znn!, (2.14)

    where (p)>0, (q)>0, (μ)>(η)>0 and mΨn(z) is the Fox-Wright function defined by (see [15], pages 56–58)

    mΨn(z)=mΨn[(αi,Ai)1,m;|z(βj,Bj)1,n;]=n=0mi=1Γ(αi+Ain)nj=1Γ(βj+Bjnznn!. (2.15)

    Proof. Applying Theorem 1 and followed the same procedure used in Theorem 7, we get the desired result.

    Recently, many researchers have introduced various generalizations of fractional integrals and derivatives. In this line, we have established a k-fractional derivative and its various properties. If we letting k1 then all the results established in this paper will reduce to the results related to the classical Reimann-Liouville fractional derivative operator.

    The author K.S. Nisar thanks to Deanship of Scientific Research (DSR), Prince Sattam bin Abdulaziz University for providing facilities and support.

    The authors declare no conflict of interest.



    [1] I. Aoki, A Simulation Study on the Schooling Mechanism in Fish, Bulletin of the Japanese Society of Scientific Fisheries (Japan), 1982.
    [2] I. D. Couzin, J. Krause, R. James, G. D Ruxton, N. R. Franks, Collective memory and spatial sorting in animal groups, J. Theor. Biol., 218 (2002), 1-11. doi: 10.1006/jtbi.2002.3065
    [3] A. Huth, C. Wissel, The simulation of the movement of fish schools, J. Theor. Biol., 156 (1992), 365-385. doi: 10.1016/S0022-5193(05)80681-2
    [4] Y. X. Li, R. Lukeman, L. Edelstein-Keshet, Minimal mechanisms for school formation in self-propelled particles, Phys. D: Nonlinear Phenomena, 237 (2008), 699-720.
    [5] C. W. Reynolds, Flocks, herds and schools: A distributed behavioral model, in ACM SIGGRAPH Computer Graphics, (1987), 25-34.
    [6] F. Cucker, S. Smale, Emergent behavior in flocks, IEEE Trans. Automatic Control, 52 (2007), 852.
    [7] F. Cucker, S. Smale, On the mathematics of emergence, Jpn. J. Math., 2 (2007), 197-227. doi: 10.1007/s11537-007-0647-x
    [8] T. Vicsek, A. Czirók, E. Ben-Jacob, I. Cohen, O. Shochet, Novel type of phase transition in a system of self-driven particles, Phys. Rev. Lett., 75 (1995), 1226-1229. doi: 10.1103/PhysRevLett.75.1226
    [9] M. Agueh, R. Illner, A. Richardson, Analysis and simulations of a refined flocking and swarming model of Cucker-Smale type, Kinetic Related Models, 4 (2011), 1-16. doi: 10.3934/krm.2011.4.1
    [10] S. Motsch, E. Tadmor, A new model for self-organized dynamics and its flocking behavior, J. Stat. Phys., 144 (2011), 923-947. doi: 10.1007/s10955-011-0285-9
    [11] S. Motsch, E. Tadmor, Heterophilious dynamics enhances consensus, SIAM Rev., 56 (2014), 577-621. doi: 10.1137/120901866
    [12] J. A. Carrillo, M. Fornasier, J. Rosado, G. Toscani, Asymptotic flocking dynamics for the kinetic Cucker-Smale model, SIAM J. Math. Anal., 42 (2010), 218-236. doi: 10.1137/090757290
    [13] S. Y. Ha, J. G. Liu, A simple proof of the Cucker-Smale flocking dynamics and mean-field limit, Commun. Math. Sci., 7 (2009), 297-325. doi: 10.4310/CMS.2009.v7.n2.a2
    [14] S. Y. Ha, E. Tadmor, From particle to kinetic and hydrodynamic descriptions of flocking, Kinetic Related Models, 1 (2008), 415-435. doi: 10.3934/krm.2008.1.415
    [15] J. A. Carrillo, Y. P. Choi, S. Pérez, A review on attractive-repulsive hydrodynamics for consensus in collective behavior, preprint, arXiv: 1605.00232.
    [16] J. A. Carrillo, Y. Huang, S. Martin, Explicit flock solutions for Quasi-Morse potentials, Eur. J. Appl. Math., (2014), 1-26.
    [17] J. Von Brecht, D. Uminsky, T. Kolokolnikov, A. Bertozzi, Predicting pattern formation in particle interactions, Math. Models Methods Appl. Sci., 22 (2012).
    [18] D. Bakry, P. Cattiaux, A. Guillin, Rate of convergence for ergodic continuous Markov processes: Lyapunov versus Poincaré, J. Funct. Anal., 254 (2008), 727-759. doi: 10.1016/j.jfa.2007.11.002
    [19] C. Villani, Hypocoercivity, Memoirs of the American Mathematical Society, 2009.
    [20] P. E. Jabin, S. Motsch, Clustering and asymptotic behavior in opinion formation, J. Differ. Equations, 257 (2014), 4165-4187. doi: 10.1016/j.jde.2014.08.005
    [21] T. Karper, A. Mellet, K. Trivisa, On strong local alignment in the kinetic Cucker-Smale model, in Hyperbolic Conservation Laws and Related Analysis with Applications, Springer, (2014), 227-242.
    [22] J. Haskovec, Flocking dynamics and mean-field limit in the Cucker-Smale-type model with topological interactions, Phys. D: Nonlinear Phenomena, 261 (2013), 42-51. doi: 10.1016/j.physd.2013.06.006
    [23] M. Ballerini, N. Cabibbo, R. Candelier, A. Cavagna, E. Cisbani, I. Giardina, et al., Interaction ruling animal collective behavior depends on topological rather than metric distance: Evidence from a field study, Proceed. Natl. Acad. Sci., 105 (2008), 1232.
    [24] A. Blanchet, P. Degond, Topological interactions in a Boltzmann-type framework, J. Stat. Phys., 163 (2016), 41-60. doi: 10.1007/s10955-016-1471-6
    [25] J. A. Carrillo, Y. Huang, Explicit Equilibrium solutions for the aggregation equation with power-law potentials, preprint, arXiv: 1602.06615.
    [26] R. Fetecau, Y. Huang, T. Kolokolnikov, Swarm dynamics and equilibria for a nonlocal aggregation model, Nonlinearity, 24 (2011), 2681. doi: 10.1088/0951-7715/24/10/002
    [27] T. Kolokolnikov, H. Sun, D. Uminsky, A. Bertozzi, Stability of ring patterns arising from two-dimensional particle interactions, Phys. Rev. E, 84 (2011), 015203. doi: 10.1103/PhysRevE.84.015203
    [28] Y. Chuang, M. R. D'Orsogna, D. Marthaler, A. L. Bertozzi, L. S. Chayes, State transitions and the continuum limit for a 2d interacting, self-propelled particle system, Phys. D: Nonlinear Phenomena, 232 (2007), 33-47.
    [29] M. R. D'Orsogna, Y. L. Chuang, A. L. Bertozzi, L. S. Chayes, Self-propelled particles with soft-core interactions: Patterns, stability, and collapse, Phys. Rev. Lett., 96 (2006), 104302.
    [30] D. Ruelle, Statistical Mechanics: Rigorous Results. World Scientific, 1969.
    [31] D. Balagué, J. A. Carrillo, T. Laurent, G. Raoul, Dimensionality of local minimizers of the Interaction energy, Arch. Rational Mech. Anal., 209 (2013), 1055-1088. doi: 10.1007/s00205-013-0644-6
    [32] L. Desvillettes, C. Villani, On the trend to global equilibrium for spatially inhomogeneous kinetic systems: The Boltzmann equation, Inventiones Math., 159 (2005), 245-316. doi: 10.1007/s00222-004-0389-9
    [33] F. Filbet, On deterministic approximation of the Boltzmann equation in a bounded domain, Multiscale Modell. Simul., 10 (2012), 792-817. doi: 10.1137/11082419X
    [34] F. Bolley, J. A. Canizo, J. A. Carrillo, Stochastic mean-field limit: non-Lipschitz forces and swarming, Math. Models Methods. Appl. Sci., 21 (2011), 2179-2210. doi: 10.1142/S0218202511005702
    [35] J. Carrillo, Y. P. Choi, M. Hauray, The derivation of swarming models: mean-field limit and Wasserstein distances, in Collective Dynamics from Bacteria to Crowds, Springer, (2014), 1-46.
    [36] P. Degond, G. Dimarco, T. B. N. Mac, N. Wang, Macroscopic models of collective motion with repulsion, Commun. Math. Sci., 13 (2015), 1615-1638. doi: 10.4310/CMS.2015.v13.n6.a12
    [37] P. Degond, J. G. Liu, S. Motsch, V. Panferov, Hydrodynamic models of self-organized dynamics: derivation and existence theory, Methods Appl. Anal., 20 (2013), 89-114.
    [38] P. Degond, S. Motsch, Continuum limit of self-driven particles with orientation interaction, Math. Models Methods Appl. Sci., 18 (2008), 1193-1215. doi: 10.1142/S0218202508003005
    [39] P. E. Jabin, A review of the mean field limits for Vlasov equations, Kinetic Related Models, 7 (2014), 661-711. doi: 10.3934/krm.2014.7.661
    [40] H. Spohn, Large Scale Dynamics of Interacting Particles, Springer, 1991.
  • This article has been cited by:

    1. Hamza Abunima, Jiashen Teh, Ching-Ming Lai, Hussein Jabir, A Systematic Review of Reliability Studies on Composite Power Systems: A Coherent Taxonomy Motivations, Open Challenges, Recommendations, and New Research Directions, 2018, 11, 1996-1073, 2417, 10.3390/en11092417
    2. Wook-Won Kim, Jong-Keun Park, Yong-Tae Yoon, Mun-Kyeom Kim, Transmission Expansion Planning under Uncertainty for Investment Options with Various Lead-Times, 2018, 11, 1996-1073, 2429, 10.3390/en11092429
    3. O Kuzmin, N Stanasiuk, S Maiti, Relationship between сonflict management strategies and economic growth of organisation, 2020, 7, 23123435, 1, 10.23939/eem2020.02.001
    4. Panlong Jin, Zongchuan Zhou, Xue Feng, Zhiyuan Wang, Tengmu Li, Pierluigi Siano, Hazlie Mokhlis, 2024, Game study of power system reconstruction planning after extreme disaster, 9781510679795, 172, 10.1117/12.3024421
  • Reader Comments
  • © 2020 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(5388) PDF downloads(188) Cited by(7)

Figures and Tables

Figures(5)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog