Article ID Journal Published Year Pages File Type
6905290 Applied Soft Computing 2015 17 Pages PDF
Abstract

- We proposed an improved binary artificial bee colony algorithm (IDisABC).
- We examined the proposed algorithm on dynamic clustering.
- Data and image clustering benchmark problems are chosen for experiments.
- The obtained results are compared with K-means, FCM, GA, DisABC, DCPSO.
Keywords
Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
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Dynamic clustering with improved binary artificial bee colony algorithm
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