摘要
提出了两种基于进化策略求任意函数数值积分的新方法,其中方法一是基于混合基函数进化策略的数值积分算法;方法二是基于不等距点分割的进化策略数值积分算法.两种算法都采用适用于高维优化问题的单基因突变进化策略,使得该算法不但能计算通常意义下任意函数的定积分,而且能计算奇异函数积分和振荡函数积分.最后给出几个数值积分算例,并与传统数值积分方法作了比较,仿真结果分析表明,两种算法十分有效,能够快速有效地获得任意函数的数值积分值.
In this paper, two new kinds of calculating numerical integration methods based on evolution strategy algorithm are proposed. One of which is based on mixing basis function evolution strategies for solving numerical integration, and the other is based on inequality point＇s segmentation for solving numerical integration. Both of these two algorithms adopt single-gene mutation evolution strategies that suit for high dimensional optimization, which can not only compute usual definite integral for any functions, but also compute singular integral and oscillatory integral. Finally, several experimental results show that the two proposed numerical integration methods are more efficient and feasible in computing the arbitrary functions numerical integration compared with traditional numerical integration methods.
出处
《计算机学报》
EI
CSCD
北大核心
2008年第2期196-206,共11页
Chinese Journal of Computers
基金
国家自然科学基金(60461001)
广西自然科学基金项目(0542048)资助
关键词
混合基函数
不等距点分割
适应度
进化策略
单基因突变
数值积分
hybrid basis functions inequality point＇s segmentation
fitness evolution strategies single-gene mutation numerical integration
