基于改进的K-means聚类算法的汽车市场竞争情报分析
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摘要
应用AHP(analytic hierarchy process)和EWM(entropy weight method),对中国A级轿车市场数据进行了分析量化处理,设计了竞争威胁数据指标,基于改进的K-means聚类算法对该市场进行了社会网络分析;通过品牌间竞争矩阵构建了中间中心度及凝聚子群,分析了产品性能指标偏重程度和企业所在该市场的竞争地位。数值实验表明:改进的K-means聚类算法对于文中样本对象,得到了更为精确的聚类效果,对中国A级轿车市场的社会网络分析准确有效。
Analytic hierarchy process(AHP)and entropy weight method(EWM)were used to analyze and quantify the data of China's A-level auto market and a data index of competition threat was designed.Social network analysis of the market was carried out based on the improved K-means cluster algorithm.Between-centrality and cohesivesubgroup were constructed through competition matrix among brands.An analysis was made of the degree of product performance index and competition status of the enterprise's relevant market.The numerical experiment shows the improved K-means cluster algorithm is comparatively effective to social network analysis of China's A-level auto market.
Analytic hierarchy process(AHP)and entropy weight method(EWM)were used to analyze and quantify the data of China's A-level auto market and a data index of competition threat was designed.Social network analysis of the market was carried out based on the improved K-means cluster algorithm.Between-centrality and cohesivesubgroup were constructed through competition matrix among brands.An analysis was made of the degree of product performance index and competition status of the enterprise's relevant market.The numerical experiment shows the improved K-means cluster algorithm is comparatively effective to social network analysis of China's A-level auto market.
引文
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[4]裴雷,马费成.社会网络分析在情报学中的应用和发展[J].图书馆论坛,2006(6):40-45.PEI Lei,MA Feicheng.The application and development of social network analysis in information science[J].Library Forum,2006(6):40-45.
[5]徐振宇.社会网络分析在经济学领域的应用进展[J].经济学动态,2013(10):61-72.XU Zhenyu.The application progress of social network analysis in economics field[J].Economic Perspectives,2013(10):61-72.
[6]唐晓波,雍菲.基于聚类分析的企业竞争对手社会网络分析[J].图书情报工作,2012,56(4):75-79.TANG Xiaobo,YONG Fei.Social network analysis of enterprise competitors based on cluster analysis[J].Library and Information Work,2012,56(4):75-79.
[7]王生昌,陈娟娟,田晓雪,等.基于层次分析法的汽车制动性能主观评价指标权重研究[J].公路交通科技,2015,32(8):138-142.WANG Shengchang,CHEN Juanjuan,TIAN Xiaoxue,et al.Research on subjective evaluation index weight of vehicle braking performance based on AHP[J].Road Traffic Science and Technology,2015,32(8):138-142.
[8]廖红强,邱勇,杨侠,等.对应用层次分析法确定权重系数的探讨[J].机械工程师,2012(6):22-25.LIAO Hongqiang,QIU Yong,YANG Xia,et al.The application of analytic hierarchy process(AHP)to determine the weight coefficient is discussed[J].Mechanical Engineer,2012(6):22-25.
[9]黄韬,刘胜辉,谭艳娜.基于k-means聚类算法的研究[J].计算机技术与发展,2011,21(7):54-57.HUANG Tao,LIU Shenghui,TAN Yanna.Research on K-means clustering algorithm[J].Computer Technology and Development,2011,21(7):54-57.
[10]仝雪姣,孟凡荣,王志晓.对k-means初始聚类中心的优化[J].计算机工程与设计,2011,32(8):2721-2723.TONG Xuejiao,MENG Fanrong,WANG Zhixiao.The optimization of initial cluster center for k-means[J].Computer Engineering and Design,2011,32(8):2721-2723.
[11]张靖,段富.优化初始聚类中心的改进K-means算法[J].计算机工程与计,2013,34(5):1691-1694.ZHANG Jing,DUAN Fu.An improved K-means algorithm for optimizing initial cluster centers[J].Computer Engineering and Computation,2013,34(5):1691-1694.
[12]韩凌波,王强,蒋正锋,等.一种改进的K-means初始聚类中心选取算法[J].计算机工程与应用,2016,46(17):150-152.HAN Lingbo,WANG Qiang,JIANG Zhengfeng,et al.An improved K-means initial clustering center selection algorithm[J].Computer Engineering and Application,2010,46(17):150-152.
[13]吴德浩,陈茂银,周东华.基于改进K均值算法的滚动轴承故障诊断[J].山东科技大学学报(自然科学版),2017,36(4):1-8.WU Dehao,CHEN Maoyin,ZHOU Donghua.Roller bearing fault diagnosis based on improved K-means algorithm[J]Journal of Shandong University of Science and Technology(Natural Science),2017,36(4):1-8.
[14]杨善林,李永森,胡笑旋,等.K-means算法中的k值优化问题研究[J].系统工程理论与实践,2006,26(2):97-101.YANG Shanlin,LI Yongsen,HU Xiaoxuan,et al.The k optimization problem in K-means algorithm is studied[J].System Engineering Theory and Practice,2006,26(2):97-101.
[15]陈光平,王文鹏,黄俊.一种改进初始聚类中心选择的K-means算法[J].小型微型计算机系统,2012,33(6):170-173.CHEN Guangping,WANG Wenpeng,HUANG Jun.An improved K-means algorithm for initial clustering center selection[J].Minitype Microcomputer System,2012,33(6):170-173.
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