Generalized picture distance measure and applications to picture fuzzy clustering



Picture fuzzy set (PFS), which is a generalization of traditional fuzzy set and intuitionistic fuzzy set, shows great promises of better adaptation to many practical problems in pattern recognition, artificial life, robotic, expert and knowledge-based systems than existing types of fuzzy sets.
An emerging research trend in PFS is development of clustering algorithms which can exploit and investigate hidden knowledge from a mass of datasets. Distance measure is one of the most important tools in clustering that determine the degree of relationship between two objects.
In this paper, we propose a generalized picture distance measure and integrate it to a novel hierarchical picture fuzzy clustering method called Hierarchical Picture Clustering (HPC). Experimental results show that the clustering quality of the proposed algorithm is better than those of the relevant ones

Title: 


Generalized picture distance measure and applications to picture fuzzy clustering
Authors: Le, Hoang Son
Keywords: Clustering quality
Hierarchical fuzzy clustering
Intuitionistic fuzzy sets
Picture distance measure
Issue Date: 2016
Publisher: H. : ĐHQGHN
Citation: ISIKNOWLEDGE
Abstract: Picture fuzzy set (PFS), which is a generalization of traditional fuzzy set and intuitionistic fuzzy set, shows great promises of better adaptation to many practical problems in pattern recognition, artificial life, robotic, expert and knowledge-based systems than existing types of fuzzy sets. An emerging research trend in PFS is development of clustering algorithms which can exploit and investigate hidden knowledge from a mass of datasets. Distance measure is one of the most important tools in clustering that determine the degree of relationship between two objects. In this paper, we propose a generalized picture distance measure and integrate it to a novel hierarchical picture fuzzy clustering method called Hierarchical Picture Clustering (HPC). Experimental results show that the clustering quality of the proposed algorithm is better than those of the relevant ones
Description: APPLIED SOFT COMPUTING Volume: 46 Pages: 284-295 ; TNS06392
URI: http://repository.vnu.edu.vn/handle/VNU_123/26844
Appears in Collections:Bài báo của ĐHQGHN trong Web of Science


Nhận xét

Bài đăng phổ biến