广义神经传播方程的整体吸引子

使用Galerkin方法,结合Sobolev空间理论和不等式技巧,给出了广义神经传播方程解的存在唯一性定理,然后利用吸引子存在性定理,采用半群方法证明了方程整体吸引子的存在性.     

全球海洋潜水旅游目的地分布特征及其自然影响因素研究

以全球海洋潜水旅游目的地为研究对象, 借助地理信息系统(GIS), 运用基尼系数、层次分析法(AHP)等方法, 研究全球海洋潜水旅游目的地的分布特征及其自然影响因素. 结果显示: (1)全球海洋潜水旅游目的地的分布数量由低纬向高纬递减; 洲际分布呈现高度集中, 主要聚集区是东亚与东南亚、地中海-红海以及加勒比海沿岸, 太平洋、印度洋与大西洋为散点分布. (2)影响海洋潜水旅游目的地的自然因素主要为海洋地形、海水温度、陆地气温、洋流、潮汐、海水能见度、珊瑚礁等, 相关因素影响程度与广度因海域呈现地域综合导控, 使得海洋潜水旅游目的地主要聚集在热带海域等地.     

全局优化问题的一个新的无参数填充函数

求全局最优化问题的填充函数算法被提出以来，参数的选取和调整一直是制约算法有效性的因素。如何在实际的计算过程中选取合适的参数，直接影响和决定了运算速度和效率。因此，构造不含参数的填充函数就显得极为重要。提出一个新的无参数的填充函数，对其理论性质进行了分析，并给出相应的填充函数算法，数值计算验证了算法的有效性。     

A note on the finite fractal dimension of the global attractors for dissipative nonlinear Schrödinger‐type equations

In this article, we present, throughout two basic models of damped nonlinear Schrödinger (NLS)–type equations, a new idea to bound from above the fractal dimension of the global attractors for NLS‐type equations. This could answer the following open issue: consider, for instance, the classical one‐dimensional cubic nonlinear Schrödinger equation $$u_t+i{u}_{xx}+i|u{|}^{2}u+\gamma u=f,f\in {\mathrm{??}}^2(?).$$ “How can we bound the fractal dimension of the associate global attractor without the need to assume that the external forcing term f has some decay at infinity (that is belonging to some weighted Lebesgue space)?”     

Nonexistence of nontrivial global solutions for nonlocal in time differential inequalities

In this paper, some nonlocal in time differential inequalities of Sobolev type are considered. Using the nonlinear capacity method, sufficient conditions for the nonexistence of nontrivial global classical solutions are provided.     

Global strong solution of 3D tropical climate model with damping

We establish the global well-posedness of a strong solution to the 3D tropical climate model with damping. We prove that there exists the global and unique solution for α, β, γ satisfying one of the following three conditions: (1) \alpha ,\beta \ge \mathrm{4}; (2) ; (3) .     

Incompressible fluid flow simulations with flow rate as the sole information at synthetic inflow and outflow boundaries

In numerically simulating heat and mass transport processes in an unconfined domain involving synthetic open (inflow and/or outflow) boundaries, how to properly specify flow conditions at these boundaries can become a challenging issue. In this work, within the context of a pressure‐based finite volume method under an unstructured grid, a solution procedure without the need for explicit specification of flow profiles at any of these boundaries when simulating incompressible fluid flow is proposed and numerically examined. Within this methodology, the flow at any open boundary is not necessarily assumed to be unidirectional or fully developed; indeed, the sole information required is the mass flow rate crossing the boundary. As a result, one can select the specific region of interest to perform simulations, rather than having to artificially increase the flow domain so as to invoke fully developed flow at all open boundaries. This not only greatly reduces computational costs (both in terms of memory requirements and simulation run‐time) but provides the means to engage with flow problems, which otherwise cannot be solved with currently available methods for handling the flow conditions at open boundaries. The proposed methodology is demonstrated by simulating laminar flow of an incompressible fluid in a two‐dimensional planar channel with a 90° T‐branch, a known inflow rate, and flow splits for the two outflow channels. The results obtained by placing the entrance and the two exits at different locations show that the flow behavior predicted is completely unaffected by using a highly truncated domain. Copyright © 2015 John Wiley & Sons, Ltd.     

基于正弦控制因子的Lateral变异鲨鱼优化算法

针对传统鲨鱼优化算法在求解高维目标函数时,易早熟收敛,陷入局部最优的缺陷.提出一种基于正弦控制因子的Lateral变异鲨鱼优化算法.通过正弦曲线的特性和自适应惯性权重,改善了传统鲨鱼优化算法中由于随机选取控制因子数值大小可能导致算法在迭代后期全局搜索能力降低的问题,提高了算法在迭代后期的全局收敛能力,并对最佳鲨鱼位置引入Lateral变异策略,加强了算法跳出局部最优的可能性.改进后的算法对多个shifted单峰,多峰以及固定维测试函数进行求解,实验结果表明,对比多种不同优化算法而言,本文所提LSSO算法具有更高的收敛精度和搜索速度.