%0 Journal Article
%A CHAO Hao
%A GUO Cheng-yi
%A LIU Yong-li
%A WANG Heng-da
%T Incremental Fuzzy C-Ordered Means Clustering
%D 2018
%R 10.13190/j.jbupt.2018-026
%J Journal of Beijing University of Posts and Telecommunications
%P 29-36
%V 41
%N 4
%X Because traditional clustering algorithms are difficult to deal with large-scale data and sensitive to noise data, based on the Fuzzy C-ordered-means clustering (FCOM) algorithm, we propose a single-pass fuzzy C-ordered clustering algorithm, named SPFCOM, and an online fuzzy C-ordered clustering algorithm, named OFCOM, by combining single-pass and online incremental architectures respectively. These two algorithms weight the FCOM algorithm, and incrementally process the large-scale data chunk by chunk. Experimental results show that, compared with other similar prominent algorithms, the SPFCOM and OFCOM algorithms can achieve higher accuracy and better robustness.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2018-026