学术
基于进化策略方法求任意函数的数值积分
周永权[1] 张明[2] 赵斌[3]
[1]广西民族大学数学与计算机科学学院,南宁530006 [2]大连水产学院理学院,辽宁大连116023 [3]中央民族大学理学院,北京100081
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。[著者文摘]
文章出处:
《计算机学报》-2008年31卷2期 -196-206页
栏目信息:
分 类 号:
Solving Numerical Integration Based on Evolution Strategy Method
ZHOU Yong-Quan ZHANG Ming ZHAO Bin （College of Mathematics and Computer Science, Guangxi University for Nationalities, Nanning 530006;School of Science, Dalian Fisheries University, Dalian, Liaoning 116023;School of Science, Central University for Nationalities, Beijing 100081）
Abstract:
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.[著者文摘]
Key words:
hybrid basis functions inequality point＇s segmentation; fitness evolution strategies single-gene mutation numerical integration
基金资助:
本课题得到国家自然科学基金（60461001）和广西自然科学基金项目（0542048）资助.
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