我国体育产业的发展与理论研究

对体育产业的概念,体育市场主体的确定,培养,规范等问题进行分析和论述。     

Saturation Effects in Mode competition Effects of a Two mode Laser with Multiplicative Noise

１ＩｎｔｒｏｄｕｃｔｉｏｎＴｗｏｍｏｄｅｌａｓｅｒｓ（ＴＭＬ）ｈａｖｅｂｅｎｔｈｅｓｕｂｊｅｃｔｏｆｅｘｔｅｎｓｉｖｅｉｎｔｅｒｅｓｔｉｎｒｅｃｅｎｔｙｅａｒｓ．Ｍｏｄｅｃｏｍｐｏｔｉｔｉｏｎｅｆｅｃｔｉｓｏｎｅｏｆｔｈｅｉｍｐｏｒｔａｎｔｐｒｏ...     

INTRODUCTION TO THE 7TH TEACHING COMPETITION OF YOUTH FACULTY OF FUNDAMENTAL MECHANICS COURSES

阐述了教育部高等学校力学基础课程教学指导分委员会举办的全国高校第七届基础力学青年教师讲课比赛的基本情况、本届讲课比赛的特点、讲课比赛中反映出的问题及其改进的建议。希望通过本文的介绍,让国内各高校教师了解本届讲课比赛以及比赛中反映出的问题,为进一步办好讲课比赛、提高我国基础力学课程的教学水平和质量提供参考。     

Learning Competitive Swarm Optimization

Particle swarm optimization (PSO) is a popular method widely used in solving different optimization problems. Unfortunately, in the case of complex multidimensional problems, PSO encounters some troubles associated with the excessive loss of population diversity and exploration ability. This leads to a deterioration in the effectiveness of the method and premature convergence. In order to prevent these inconveniences, in this paper, a learning competitive swarm optimization algorithm (LCSO) based on the particle swarm optimization method and the competition mechanism is proposed. In the first phase of LCSO, the swarm is divided into sub-swarms, each of which can work in parallel. In each sub-swarm, particles participate in the tournament. The participants of the tournament update their knowledge by learning from their competitors. In the second phase, information is exchanged between sub-swarms. The new algorithm was examined on a set of test functions. To evaluate the effectiveness of the proposed LCSO, the test results were compared with those achieved through the competitive swarm optimizer (CSO), comprehensive particle swarm optimizer (CLPSO), PSO, fully informed particle swarm (FIPS), covariance matrix adaptation evolution strategy (CMA-ES) and heterogeneous comprehensive learning particle swarm optimization (HCLPSO). The experimental results indicate that the proposed approach enhances the entropy of the particle swarm and improves the search process. Moreover, the LCSO algorithm is statistically and significantly more efficient than the other tested methods.     

Traveling wave solutions for a two-species competitive Keller–Segel chemotaxis system

In this paper, the traveling wave problem for a two-species competition reaction–diffusion–chemotaxis Lotka–Volterra system is investigated. Upper and lower solutions method and fixed point theory are employed to show the existence of traveling wave solutions connecting the coexistence constant steady state with zero state for all large enough wave speed $c$, and conversely, when $c$ is small, we prove there is no traveling wave solution.     

Dynamic Analysis of an Impulsive Chemostat Model with Microbial Competition and Nonlinear Perturbation

In this paper, we propose an impulsive chemostat model with microbial competition and nonlinear perturbation. First, thresholds for the extinction of both microoganisms are given. Second, we investigate the persistence in mean and boundedness of the chemostat system by constructing Lyapunov function. Moreover, we obtain the sufficient condition for the existence of an ergodic stationary distribution of the system. At last, numerical simulations are presented, and the results show that the competition between two species tends to make one species disappear from their common habitat, especially when the competition is concentrated in a single resource.     

Stability and Bifurcation Analysis in a Nonlocal Diffusive Predator-prey Model with Hunting Cooperation

In this paper, we propose a diffusive predator-prey model with hunting cooperation and nonlocal competition. Under a rather general selection of the kernel function, we first study the stability of the positive equilibrium of the model. Then, we obtain the conditions which Hopf bifurcation and Turing bifurcation occur. Our results show that nonlocal competition plays an important role in determining the dynamics of the model.