Research Article
Genetic Based Interval Type-2 Fuzzy C-Means Clustering
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@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
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.
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