Title :
A Novel Fuzzy Clustering Based on Particle Swarm Optimization
Author :
Li, Lili ; Liu, Xiyu ; Xu, Mingming
Author_Institution :
Shandong Normal Univ., Jinan
Abstract :
In order to overcome the shortcomings of fuzzy C-means algorithm such as the local optima and sensitivity to initialization, a new PSO-based fuzzy algorithm is discussed in this paper. The new algorithm uses the capacity of global search in PSO algorithm, and solves the problems of FCM. The experiment shows that the algorithm avoids the local optima and increases the convergence speed.
Keywords :
fuzzy set theory; particle swarm optimisation; pattern clustering; search problems; PSO-based fuzzy algorithm; fuzzy C-means algorithm; global search; novel fuzzy clustering; particle swarm optimization; Clustering algorithms; Convergence; Engineering management; Evolutionary computation; Information science; Iterative algorithms; Particle swarm optimization; Partitioning algorithms; Stochastic processes; Unsupervised learning; Cluster analysis; Fuzzy C-means algorithm; Global optimization; Particle swarm optimization;
Conference_Titel :
Information Technologies and Applications in Education, 2007. ISITAE '07. First IEEE International Symposium on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-1386-7
Electronic_ISBN :
978-1-4244-1386-7
DOI :
10.1109/ISITAE.2007.4409243
