Novel Fuzzy Clustering Algorithm Based on Fireflies
Dan Li, Ke Luo, Zhen Hong Sun · Advances in engineering research/Advances in Engineering Research · 2015
Aiming at the existence of fuzzy C-means algorithm was sensitive to the initial clustering center and its shortcoming of easily plunged into local optimum ,this paper proposed a novel fuzzy clustering algorithm based on fireflies .The algorithm employed the chaos initialization individuals as the initial population .Then it utilized the improved fireflies as the accurately clustering center and received a new clustering center as the initial clustering center of fuzzy C-means .Thus it can overcome the fuzzy C-means' sensitivity to the initial clustering center and solve the deficiency of easily falling into local optimum.Simulation experiment results based on UCI standard data sets show that the algorithm can avoid falling into local optimum and precocious, it also gets better performance and results compared with other algorithms.