Summary
International Symposium on Nonlinear Theory and its Applications
2017
Session Number:C0L-C
Session:
Number:C0L-C-1
K-Means Clustering with Modifying Firefly Algorithm
Masaki Takeuchi, Thomas Ott, Haruna Matsushita, Yoko Uwate, Yoshifumi Nishio,
pp.576-579
Publication Date:2017/12/4
Online ISSN:2188-5079
Summary:
Senthilnath et al. [1] proposed an algorithm that used the firefly algorithm for K-means clustering (KMFA). In this paper, we propose a new clustering algorithm that combines K-means clustering and improved firefly algorithm (KMIFA). In our proposed algorithm, at the beginning of the search, all fireflies move with a relatively strong random influence. As the number of iterations increases, the firefly tends to converge. These experiments indicate that our algorithm is more efficient than the other algorithms.