A fuzzy c-means bi-sonar-based Metaheuristic Optimization Algorithm

TitleA fuzzy c-means bi-sonar-based Metaheuristic Optimization Algorithm
Publication TypeJournal Article
Year of Publication2012
AuthorsKhan, K., and A. Sahai
JournalInternational Journal of Interactive Multimedia and Artificial Intelligence
IssueRegular Issue
Date Published12/2012

Fuzzy clustering is an important problem which is the subject of active research in several real world applications. Fuzzy c-means (FCM) algorithm is one of the most popular fuzzy clustering techniques because it is efficient, straightforward, and easy to implement. Fuzzy clustering methods allow the objects to belong to several clusters simultaneously, with different degrees of membership. Objects on the boundaries between several classes are not forced to fully belong to one of the classes, but rather are assigned membership degrees between 0 and 1 indicating their partial membership. However FCM is sensitive to initialization and is easily trapped in local optima. Bi-sonar optimization (BSO) is a stochastic global Metaheuristic optimization tool and is a relatively new algorithm. In this paper a hybrid fuzzy clustering method FCB based on FCM and BSO is proposed which makes use of the merits of both algorithms. Experimental results show that this proposed method is efficient and reveals encouraging results.

KeywordsBi-sonar, Clustering, Fuzzy, Metaheuristic, Optimization
IJIMAI20121_7_3.pdf479.72 KB