Clustering Algorithm for Intuitionistic Fuzzy Graphs

被引：26
|
作者：
Karunambigai, M. G. [1 ]
Akram, Muhammad [2 ]
Sivasankar, S. [3 ]
Palanivel, K. [4 ]
机构：
[1] Sri Vasavi Coll, Dept Math, Erode 638016, Tamil Nadu, India
[2] Univ Punjab, Dept Math, New Campus,POB 54590, Lahore, Pakistan
[3] PES Univ, Dept Sci & Humanities, Bangalore 560085, Karnataka, India
[4] Oxford Coll Engn, Dept Math, Bangalore 560068, Karnataka, India
来源：
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS | 2017年 / 25卷 / 03期
关键词：
Intuitionistic fuzzy graph; density; balanced; slicing; parameters; clustering algorithm; GROUP DECISION-MAKING; SETS;
D O I：
10.1142/S0218488517500155
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
' In this paper, we present certain algorithms for clustering the vertices of fuzzy graphs(FGs) and intuitionistic fuzzy graphs(IFGs). These algorithms are based on the edge density of the given graph. We apply the algorithms to practical problems to derive the most prominent cluster among them. We also introduce parameters for intuitionistic fuzzy graphs.
引用
收藏
页码：367 / 383
页数：17
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