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 ...

Proton‐exchange membrane fuel cells have been established as a really promising technology, specially due to their high efficiency and scalability features, additionally to their low pollution emissions. In a typical ...

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 ...

Data clustering is applied to various fields such as data mining, image processing and pattern recognition technique. Clustering algorithms splits a data set into clusters such that elements within the same cluster have a ...

Shotgun metagenomic studies attempt to reconstruct population genome sequences from complex microbial communities. In some traditional genome demarcation approaches, high-dimensional sequence data are embedded into ...

Data clustering consists of grouping similar objects according to some characteristic. In literature, there are several clustering algorithms, among which stands out the Fuzzy CMeans (FCM), one of the most discussed ...

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 ...

The development of strategies for structural health monitoring (SHM) has become increasingly important because of the necessity of preventing undesirable damage. This paper describes an approach to this problem using ...