# [1]陆建江,徐宝文.区间数据的并行模糊聚类算法[J].东南大学学报(自然科学版),2003,33(4):406-409.[doi:10.3969/j.issn.1001-0505.2003.04.007] 　Lu Jianjiang,Xu Baowen.Parallel fuzzy clustering algorithm for interval data[J].Journal of Southeast University (Natural Science Edition),2003,33(4):406-409.[doi:10.3969/j.issn.1001-0505.2003.04.007] 点击复制 区间数据的并行模糊聚类算法() 分享到： var jiathis_config = { data_track_clickback: true };

33

2003年第4期

406-409

2003-07-20

## 文章信息/Info

Title:
Parallel fuzzy clustering algorithm for interval data

1 东南大学计算机科学与工程系, 南京 210096; 2 解放军理工大学理学院, 南京 210007; 3 江苏省软件质量研究所, 南京 210096; 4 国防科学技术大学计算机学院, 长沙 410073
Author(s):
1 Department of Computer Science and Engineering, Southeast University, Nanjing 210096, China
2 School of Science, PLA University of Science and Technology, Nanjing 210007, China
3 Jiangsu Institute of Software Quality, Nanjing 210096, China
4 School of Computer Science, National University of Defense Technology, Changsha 410073, China

Keywords:

TP18
DOI:
10.3969/j.issn.1001-0505.2003.04.007

Abstract:
Fuzzy clustering algorithms for interval data are presented. The principle and steps of the fuzzy c-means algorithm are studied, meanwhile it is improved for clustering interval data by defining the distance and operation between interval data. Then, parallel fuzzy c-means algorithm is discussed for clustering interval data. Finally the parallel clustering algorithm is implemented on distributed linked PC/workstation. The experiment results show that the parallel clustering algorithm has fine scaleup, sizeup and speedup.

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