Genetic Based Interval Type-2 Fuzzy C-Means Clustering

Dzung Nguyen; Long Ngo; Long Pham

Context-Aware Systems and Applications. First International Conference, ICCASA 2012, Ho Chi Minh City, Vietnam, November 26-27, 2012, Revised Selected Papers

Research Article

Genetic Based Interval Type-2 Fuzzy C-Means Clustering

Download

550 downloads

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1007/978-3-642-36642-0_24,
    author={Dzung Nguyen and Long Ngo and Long Pham},
    title={Genetic Based Interval Type-2 Fuzzy C-Means Clustering},
    proceedings={Context-Aware Systems and Applications. First International Conference, ICCASA 2012, Ho Chi Minh City, Vietnam, November 26-27, 2012, Revised Selected Papers},
    proceedings_a={ICCASA},
    year={2013},
    month={2},
    keywords={fuzzy clustering interval type-2 fuzzy c-means genetic algorithm},
    doi={10.1007/978-3-642-36642-0_24}
}

Dzung Nguyen
Long Ngo
Long Pham
Year: 2013
Genetic Based Interval Type-2 Fuzzy C-Means Clustering
ICCASA
Springer
DOI: 10.1007/978-3-642-36642-0_24

Dzung Nguyen¹^,*, Long Ngo¹^,*, Long Pham¹

1: Le Quy Don Technical University

*Contact email: dinhdung1082@gmail.com, ngotlong@gmail.com

Abstract

This paper deals with a genetic-based interval type 2 fuzzy c-means clustering (GIT2FCM), which automatically find the optimal number of clusters. A heuristic method based on a genetic algorithm (GA) is adopted to automatically determine the number of cluster based on the validity index. The proposed algorithm contains two main steps: initialize randomly the population of the GA and use the GA to adjust the cluster centroids based on the validity index which is computed by interval type 2 fuzzy c-means clustering (IT2FCM). The experiments are done based on datasets with the statistics show that the algorithm generates good quality of clusters.

Keywords: fuzzy clustering interval type-2 fuzzy c-means genetic algorithm

Published: 2013-02-04

: http://dx.doi.org/10.1007/978-3-642-36642-0_24