蚁群算法求解连续空间优化问题的一种方法

针对蚁群算法不太适合求解连续性优化问题的缺陷,提出用蚁群算法求解连续空间优化问题的一种方法.该方法将解空间划分成若干子域,在蚁群算法的每一次迭代中,首先根据信息量求出解所在的子域,然后在该子域内已有的解中确定解的具体值.以非线性规划问题为例所进行的计算结果表明,该方法比使用模拟退火算法、遗传算法具有更好的收敛速度.     

Construction of Shapes Arising from the Minkowski Problem Using a Level Set Approach

The Minkowski problem asks a fundamental question in differential geometry whose answer is not only important in that field but has real world applications as well. We endeavor to construct the shapes that arise from the Minkowski problem by forming a PDE that flows an initial implicitly defined hypersurface to an approximation of the shape under the level set framework. Tools and ideas found in the various applications of level set methods are gathered to generate this PDE. Numerically, its solution is determined by incorporating high order finite difference schemes over the uniform grid available in the framework. Finally, we use our approach in various test cases to generate various shapes arising from different given data in the Minkowski problem.     

Shared-Memory Parallel Vector Implementation of the Immersed Boundary Method for the Computation of Blood Flow in the Beating Mammalian Heart

This paper describes the parallel implementation of the immersed boundary method on a shared-memory machine such as the Cray C-90 computer. In this implementation, outer loops are parallelized and inner loops are vectorized. The sustained computation rates achieved are 0.258 Gflops with a single processor, 1.89 Gflops with 8 processors, and 2.50 Gflops with 16 processors. An application to the computer simulation of blood flow in the heart is presented.     

利用有限差分法计算真实头模型脑电正问题

脑电研究领域的两个关键问题是脑电正问题和脑电逆问题,脑电正问题是脑电逆问题的基础.由于复杂、非规则真实头模型中的脑电正问题不存在解析解,因此脑电源分析依赖于正问题数值算法的精度和效率.文章首先详细推导了有限差分算法求解三维各向同性脑电正问题的数学模型,然后在三层同心球模型上通过与解析解比较验证了该算法的精度和效率,最后将该算法应用于真实头模型.仿真结果表明,有限差分法可以有效地处理任意形状几何体的电位场分布问题,是模拟计算真实头模型中脑电正问题的有力工具.