Title :
Multi-central general fuzzy clustering model
Author :
Mohamadi Golsefid, Samira Malek ; Zarandi, Mohammad Fazel
Author_Institution :
Dept. of Ind. Eng., Amirkabir Univ. of Technol., Tehran, Iran
Abstract :
This paper presents a new model for general fuzzy type-2 clustering called Multi Central General Fuzzy Type-2 Clustering that is an extension of possibilistic c-means (PCM). We mainly focus on uncertainty associated with the cluster centers and define a set of points as the center for each cluster. In our model the degree of belonging is defined as general type-2 fuzzy and there is not any type reduction or defuzzification in the new clustering algorithm. Numerical examples demonstrate the proposed model performance.
Keywords :
fuzzy set theory; pattern clustering; possibility theory; PCM; multicentral general fuzzy type-2 clustering; possibilistic c-means; Clustering algorithms; Educational institutions; Fuzzy sets; Industrial engineering; Pattern recognition; Phase change materials; Uncertainty;
Conference_Titel :
Norbert Wiener in the 21st Century (21CW), 2014 IEEE Conference on
Conference_Location :
Boston, MA
DOI :
10.1109/NORBERT.2014.6893905