Fuzzy Artificial Bee Colony for Clustering

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Provided by: American Institute of Science (AIS)
Topic: Data Management
Format: PDF
In this paper, the authors propose, "Fuzzy Artificial Bee Algorithm (FABC)" for clustering data, this method is an algorithm derived from honeybees to find food in the global and local search to find the best centers in clusters. This algorithm in comparison with other well-known modern heuristic algorithms such as ABC, GA, TS, SA, ACO, K-means, FCM, and PSO improved significantly that fuzzy ABC algorithm had the best performance among other algorithms for the best, average and worst inter-cluster distances. Experiments on iris and wine datasets show that the new method is better.
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