| 一种基于改进混合蛙跳的聚类算法 |
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| 引用本文： | 韩晓慧,王联国.一种基于改进混合蛙跳的聚类算法[J].传感器与微系统,2012,31(4):137-139. |
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| 作者姓名： | 韩晓慧 王联国 |
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| 作者单位： | 1. 甘肃农业大学工学院,甘肃兰州,730070
2. 甘肃农业大学信息科学技术学院,甘肃兰州,730070 |
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| 基金项目： | 国家自然科学基金资助项目(61063028) |
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| 摘 要： | 聚类分析是一种无监督的模式识别方式,它是数据挖掘中的重要技术之一。给出了一种基于改进混合蛙跳算法的聚类分析方法,该方法结合了K—均值算法和改进混合蛙跳算法各自的优点,引入了K—均值操作,再用改进混合蛙跳算法进行优化,很大程度上提高了该算法的局部搜索能力和收敛速度。通过仿真对基于改进混合蛙跳的聚类方法与其他已有的聚类方法进行了比较,验证了所提出算法的优越性。
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| 关 键 词： | 混合蛙跳算法 K—均值算法 聚类分析 |
A clustering algorithm based on modified shuffled frog leaping |
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| HAN Xiao-hui
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WANG Lian-guo.A clustering algorithm based on modified shuffled frog leaping[J].Transducer and Microsystem Technology,2012,31(4):137-139. |
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| Authors: | HAN Xiao-hui WANG Lian-guo |
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| Affiliation: | 1.School of Engineering,Gansu Agricultural University,Lanzhou 730070,China; 2.School of Information Science Technology,Gansu Agricultural University,Lanzhou 730070,China) |
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| Abstract: | Clustering analysis is an unsupervised mode of pattern recognition and is one of primary techniques in the filed of data mining.A clustering analysis method based on a modified shuffled frog leaping algorithm(MSFLA)is proposed.The new approach integrates the advantages of the MSFLA and the K-means algorithms,which introduces the K-means operation and utilizes the MSFLA for optimization,improves the locally searching capability and convergence speed of the clustering algorithm based on MSFLA.Simulations are performed to compare the performance of the clustering algorithm based on modified MSFLA and other clustering algorithm,which validates the effectiveness of the proposed algorithm. |
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| Keywords: | shuffled frog-leaping algorithm K-means algorithm clustering analysis |
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