基于布谷鸟搜索算法的多传感器数据融合

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英文篇名：Multisensor Data Fusion Based on Cuckoo Search Algorithm 作者：孙凯明 ; 胡晓工 ; 王刚 英文作者：SUN Kai-ming;HU Xiao-gong;WANG Gang;The Institute of Advanced Technology of Heilongjiang Academy of Sciences;The Institute of Automation of Heilongjiang Academy of Sciences;Research and Design Institute of CITIC Machinery Manufacturing Inc; 关键词：布谷鸟搜索算法 ; 多传感器 ; 数据融合 英文关键词：cuckoo search;;multisensor;;data fusion 中文刊名：ZDHJ 英文刊名：Techniques of Automation and Applications 机构：黑龙江省科学院高技术研究院;黑龙江省科学院自动化所;中信机电制造公司科研设计院; 出版日期：2018-07-25 出版单位：自动化技术与应用 年：2018 期：v.37;No.277 语种：中文; 页：ZDHJ201807003 页数：3 CN：07 ISSN：23-1474/TP 分类号：17-19

摘要

布谷鸟搜索算法具有高效并行性和收敛快、不易陷于局部最优的特点,有较强的寻优能力,故能较好地解决多参数优化问题。本文针对多传感器数据融合中的加权因子的数据融合方法 ,尝试性地把它运用到多传感器融合的领域,并取取得了不错的效果。
        Cuckoo search algorithm has the characteristics of efficient parallelism and fast convergence, and is not easy to fall into the local optimum. It has strong optimization ability, so it can solve multi parameter optimization problem well. Aiming at the data fusion method of weighting factor in multisensor data fusion, this paper tries to apply it to the field of multisensor fusion, and achieves good results.

引文

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