Improved Self-Adaptive ACS Algorithm to Determine the Optimal Number of Clusters

Volume: 11, Issue: 3, Pages: 1092 - 1092
Published: Jun 21, 2021
Abstract

A fundamental problem in data clustering is how to determine the correct number of clusters. The k-adaptive medoid set ant colony optimization (ACO) clustering (METACOC-K) algorithm is superior in solving clustering problems. However, METACOC-K does not guarantee in finding the best number of clusters. It assumed the number of clusters based on an adaptive parameter strategy that lacks...

Paper Details
Title
Improved Self-Adaptive ACS Algorithm to Determine the Optimal Number of Clusters
Published Date
Jun 21, 2021
Volume
11
Issue
3
Pages
1092 - 1092
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