This paper studies the long time behavior of solutions to the Navier-Stokes equations with linear damping on R^2. The authors prove the existence of L^2-global attractor and Hi-global attractor by showing that the cor...This paper studies the long time behavior of solutions to the Navier-Stokes equations with linear damping on R^2. The authors prove the existence of L^2-global attractor and Hi-global attractor by showing that the corresponding semigroup is asymptotically compact. Thereafter, they establish that the two attractors are the same and thus reveal the asymptotic smoothing effect of the solutions.展开更多
This paper studies the long time behavior of the following Cauchy problem δu/δt＋σδ^4u/δx^4＋ru＋uδu/δx=f,x∈R,t〉0,The authors prove the existence of global attractor by showing the corresponding operator semi...This paper studies the long time behavior of the following Cauchy problem δu/δt＋σδ^4u/δx^4＋ru＋uδu/δx=f,x∈R,t〉0,The authors prove the existence of global attractor by showing the corresponding operator semigroup is asymptotically compact.展开更多
Traditionally, the optimization algorithm based on physics principles has some shortcomings such as low population diversity and susceptibility to local extrema. A new optimization algorithm based on kinetic-molecular...Traditionally, the optimization algorithm based on physics principles has some shortcomings such as low population diversity and susceptibility to local extrema. A new optimization algorithm based on kinetic-molecular theory(KMTOA) is proposed. In the KMTOA three operators are designed: attraction, repulsion and wave. The attraction operator simulates the molecular attraction, with the molecules moving towards the optimal ones, which makes possible the optimization. The repulsion operator simulates the molecular repulsion, with the molecules diverging from the optimal ones. The wave operator simulates the thermal molecules moving irregularly, which enlarges the searching spaces and increases the population diversity and global searching ability. Experimental results indicate that KMTOA prevails over other algorithms in the robustness, solution quality, population diversity and convergence speed.展开更多
基金Supported by Natural Science Foundation of China(1077107410771139)+1 种基金Supported by the NSF of Wenzhou University(2007L024)Supported by the NSF of Zhejiang Province(Y6080077)
文摘This paper studies the long time behavior of solutions to the Navier-Stokes equations with linear damping on R^2. The authors prove the existence of L^2-global attractor and Hi-global attractor by showing that the corresponding semigroup is asymptotically compact. Thereafter, they establish that the two attractors are the same and thus reveal the asymptotic smoothing effect of the solutions.
基金Supported by the Natural Science Foundation of China(10001013)Supported by the NSF Zhejiang Province(M103043)Supported by NSF of Wenzhou Normal College NSF(2003Y16)
文摘This paper studies the long time behavior of the following Cauchy problem δu/δt＋σδ^4u/δx^4＋ru＋uδu/δx=f,x∈R,t〉0,The authors prove the existence of global attractor by showing the corresponding operator semigroup is asymptotically compact.
基金Project(61174140)supported by the National Natural Science Foundation of ChinaProject(13JJA002)supported by Hunan Provincial Natural Science Foundation,ChinaProject(20110161110035)supported by the Doctoral Fund of Ministry of Education of China
文摘Traditionally, the optimization algorithm based on physics principles has some shortcomings such as low population diversity and susceptibility to local extrema. A new optimization algorithm based on kinetic-molecular theory(KMTOA) is proposed. In the KMTOA three operators are designed: attraction, repulsion and wave. The attraction operator simulates the molecular attraction, with the molecules moving towards the optimal ones, which makes possible the optimization. The repulsion operator simulates the molecular repulsion, with the molecules diverging from the optimal ones. The wave operator simulates the thermal molecules moving irregularly, which enlarges the searching spaces and increases the population diversity and global searching ability. Experimental results indicate that KMTOA prevails over other algorithms in the robustness, solution quality, population diversity and convergence speed.
