一种区间型数据的自适应模糊c均值聚类算法OACSCDCSTPCD
Self-adapting fuzzy c means clustering algorithm for interval data
针对区间型数据的聚类问题,提出一种自适应模糊c均值聚类算法.该算法一方面基于区间数的中点和半宽度,通过引入区间宽度的影响因子以控制区间大小对聚类结果的影响；另一方面通过引入一个自适应系数,以减少区间型数据的数据结构对聚类效果的影响.通过仿真数据和Fish真实数据验证了该算法的有效性,并对聚类结果进行比较和分析.
A self-adapting fuzzy c means clustering algorithm is proposed for clustering problems with interval data. On the one hand, based on the mid-point and half-width of interval value, the impact factor of interval width is introduced to control the influence on the clustering results by the length of the interval data. On the other hand, the impact on the clustering results by the data structure of the interval data can also be reduced by introducing a self-ada…查看全部>>
谢志伟;王志明
东莞职业技术学院计算机工程系,广东东莞523808东莞职业技术学院信息技术中心,广东东莞523808
信息技术与安全科学
区间型数据模糊c均值聚类自适应系数自适应模糊c均值聚类
interval data fuzzy c means clustering self-adapting coefficient self-adapting fuzzy c means clustering
《计算机工程与应用》 2012 (17)
193-198,237,7
国家社科基金重大项目(No.09&ZD014).
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