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题名A direct search algorithm based on kernel density estimator for nonlinear optimization
作者
发表日期2014
会议录名称2014 10th International Conference on Natural Computation, ICNC 2014
页码297-302
摘要In this paper, we propose a direct search algorithm based on kernel density estimator for the nonlinear optimization problems. It estimates the objective function by the kernel density estimator with the local samples only, and then approximates the ascent direction of the objective function with the one of the estimator. The proposed optimization approach features the derivative-free with much likely generating an ascent direction. We not only theoretically show that the search direction, which is used in the proposed algorithm towards maximizing the objective function, is the ascent direction of the objective function, but also empirically investigate the effectiveness of the search direction.
DOI10.1109/ICNC.2014.6975851
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语种英语English
Scopus入藏号2-s2.0-84926640794
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被引频次[WOS]:0   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符https://repository.uic.edu.cn/handle/39GCC9TT/6509
专题北师香港浸会大学
作者单位
1.Department of Computer Science, Hong Kong Baptist University,China
2.BNU-HKBU, United International College,Zhuhai,China
第一作者单位北师香港浸会大学
推荐引用方式
GB/T 7714
Cheung,Yiu Ming,Gu,Fangqing. A direct search algorithm based on kernel density estimator for nonlinear optimization[C], 2014: 297-302.
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