The combination of fuzzy systems with clustering algorithms has great acceptance in the scientific community mainly due to its adherence to the advantage balance principle of computational intelligence, in which different ...

This paper presents a network anomaly detection method based on fuzzy clustering. Computer security has become an increasingly vital field in computer science in response to the proliferation of private sensitive information. ...

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 ...

Clustering data is a very important task in data mining, image processing and pattern recognition problems. One of the most popular clustering algorithms is the Fuzzy C-Means (FCM). This thesis proposes to implement a new ...

System flexibility means the ability of a system to manage imprecise and/or uncertain information. A lot of commercially available Information Retrieval Systems (IRS) address this issue at the level of query formulation. ...

Clustering is one of the most widely used approaches in data mining with real life applications in virtually any domain. The huge interest in clustering has led to a possibly three-digit number of algorithms with the ...

The construction of the knowledge base of fuzzy systems has been beneficited intensively from automatic methods that extract the necessary knowledge from data sets which represent examples of the problem. The evolutionary ...

Purpose – Pre-screening of skin lesion for malignancy is highly demanded as melanoma being a life-threatening skin cancer due to unpaired DNA damage. In this paper, lesion segmentation based on Fuzzy C-Means clustering ...

There are some variants of the widely used Fuzzy C-Means (FCM) algorithm that support clustering data distributed across different sites. Those methods have been studied under different names, like collaborative and parallel ...