CAJ | 학술논문

通过分析投票模型中中立者的思想倾向,对区间值数据进行二次特征提取.给出了一种区间值数据的Gauss函数表示法,利用这种方法对区间值数据进行相似度量,从而导出一种新的区间值数据的距离度量公式.将该距离度量公式运用于区间值数据的模糊c均值聚类算法(FCM)中,得出一种新的基于Gauss分布函数的区问值数据的模糊聚类算法,试验表明该方法比传统的区间值数据的模糊聚类算法能获得更好的分类效果.
통과분석투표모형중중립자적사상경향,대구간치수거진행이차특정제취.급출료일충구간치수거적Gauss함수표시법,이용저충방법대구간치수거진행상사도량,종이도출일충신적구간치수거적거리도량공식.장해거리도량공식운용우구간치수거적모호c균치취류산법(FCM)중,득출일충신적기우Gauss분포함수적구문치수거적모호취류산법,시험표명해방법비전통적구간치수거적모호취류산법능획득경호적분류효과.
According to analyzing the tendency of neutrals in a vote model,a new kind of similarity measure between interval-valued data based on Gauss distribution functions is proposed and the distance between two interval-valued data is given,andthen,a novel fuzzy clustering algorithm for interval-valued data is presented. Examples show that this algorithm can get better performance than other existing methods.