Like k-means and Gaussian mixture model (GMM), fuzzy c-means (FCM) with soft partition has also become a popular clustering algorithm still is extensively studied. However, these algorithms their variants suffer from some difficulties such as determination of the optimal number clusters which key factor for quality. A common approach overcoming this difficulty to use trial-and-validation strate...

In this paper, we propose a Context-based Gustafson-Kessel (CGK) clustering that builds Information Granulation (IG) in the form of fuzzy set. The fundamental idea of this clustering is based on Conditional Fuzzy C-Means (CFCM) clustering introduced by Pedrycz. The proposed clustering develops clusters preserving homogeneity of the clustered patterns associated with the input and output space. ...

Due to its inferior characteristics, an observed (noisy) image's direct use gives rise poor segmentation results. Intuitively, using noise-free image can favorably impact segmentation. Hence, the accurate estimation of residual between and images is important task. To do so, we elaborate on residual-driven Fuzzy C-Means (FCM) for segmentation, which first approach that realizes leads participat...

This study proposes a new single-solution based metaheuristic, namely the Vortex Search algorithm (VS), for fuzzy clustering of ECG beats. The newly proposed metaheuristic is quite simple and highly competitive when compared to the population-based metaheuristics. In order to study the performance of the proposed method a number of experiments are performed over a dataset which is created by us...