摘要
通过特征正交分解法降低二维大气污染模型的经典差分格式的自由度,建立了一种降维差分迭代算法,分析了精确解与降维数值解之间最大模误差估计.对于相同的时间和空间步长,通过数值算例对比原始差分格式和降维格式的计算精度和时间,验证了降维算法的有效性和可行性.
By using the proper orthogonal decomposition method, the degree of freedom of the classical finite difference scheme for the two-dimensional air pollution model is reduced and a dimensionality reduction finite difference iteration algorithm is established. The maximum norm error estimate between the exact solution and the dimensionality reduction numerical solution is analyzed. For the same time and space step size, the computational accuracy and cost for the original and the dimensionality reduction finite difference algorithms are compared by numerical examples to verify the effectiveness and feasibility of the dimensionality reduction algorithm.
作者
澈力木格
何斯日古楞
李宏
Chelimuge;He Siriguleng;Li Hong(Inner Mongolia Normal University,Hohhot 010022,China;School of Mathematical Sciences,Inner Mongolia University,Hohhot 010021,China)
出处
《数值计算与计算机应用》
2018年第3期172-182,共11页
Journal on Numerical Methods and Computer Applications
基金
国家自然科学基金(11501311,11761053)
内蒙古自然科学基金(2014BS0101,2017MS0107)资助项目
关键词
有限差分方法
特征正交分解方法
二维大气污染模型
finite difference method
proper orthogonal decomposition method
the air pollution model
