Abstract
This paper presents a Memetic Algorithm (MA) based Fuzzy C-Means (FCM) clustering algorithm. Traditional FCM algorithm suffers from the problem of local optimal, whereas the proposed MA-based FCM algorithm is able to overcome this problem and produce good performance in various ways. Experimental results showed that the proposed clustering algorithm outperforms traditional fuzzy clustering algorithms significantly on a wide variety of datasets with overlapping class boundaries and spread data distributions.
| Original language | English |
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| Title of host publication | 2007 IEEE Congress on Evolutionary Computation, CEC 2007 |
| Pages | 2398-2404 |
| Number of pages | 7 |
| DOIs | |
| Publication status | Published - 2007 |
| Externally published | Yes |
| Event | 2007 IEEE Congress on Evolutionary Computation, CEC 2007 - , Singapore Duration: 25 Sept 2007 → 28 Sept 2007 |
Publication series
| Name | 2007 IEEE Congress on Evolutionary Computation, CEC 2007 |
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Conference
| Conference | 2007 IEEE Congress on Evolutionary Computation, CEC 2007 |
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| Country/Territory | Singapore |
| Period | 25/09/07 → 28/09/07 |
ASJC Scopus subject areas
- Artificial Intelligence
- Software
- Theoretical Computer Science
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Do, A. D., & Cho, S. Y. (2007). Memetic algorithm based fuzzy clustering. In 2007 IEEE Congress on Evolutionary Computation, CEC 2007 (pp. 2398-2404). Article 4424771 (2007 IEEE Congress on Evolutionary Computation, CEC 2007). https://doi.org/10.1109/CEC.2007.4424771