On similarities between two models of global optimization: statistical models and radial basis functions

被引：0
作者：
Antanas Žilinskas
机构：
[1] Institute of Mathematics and Informatics,
来源：
Journal of Global Optimization | 2010年 / 48卷
关键词：
Global optimization; Optimization in the presence of noise; Statistical models; Radial basis function;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Construction of global optimization algorithms using statistical models and radial basis function models is discussed. A new method of data smoothing using radial basis function and least squares approach is presented. It is shown that the P-algorithm for global optimization in the presence of noise based on a statistical model coincides with the corresponding radial basis algorithm.
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页码：173 / 182
页数：9
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