This work addresses the problem of detecting clusters in a weighted, undirected, graph by
using kernel-based clustering methods, directly partitioning the graph according to a well …

In order to further improve the convergence performance of data clustering algorithms, a
dynamic shuffled differential evolution algorithm, DSDE for short, is presented in this paper …

Historical and recent developments in the field of robust clustering and their applications are
reviewed. The discussion focuses on different strategies that have been developed to …

This paper presents a robust fuzzy c-means (FCM) for an automatic effective segmentation
of breast and brain magnetic resonance images (MRI). This paper obtains novel objective …

This paper presents a new algorithm for fuzzy c-regression model clustering. The proposed
methodology is based on adding a second regularization term in the objective function of a …

Artificial intelligence is the study of how computer systems can simulate intelligent processes
such as learning, reasoning, and understanding symbolic information in context. Axiomatic …

The semiconductor industry is characterized by rapid change and ever-increasing
competition. To sustain the competitiveness and survive in such an environment …

Sensor data processing plays an important role on the development of the wireless sensor
networks in the big data era. Owning to the existence of a large number of incomplete data …

Generative Topographic Mapping (GTM) is an important technique for dimension reduction
which has been successfully applied to many fields. However the usual Expectation …

The main purpose of this paper is to achieve improvement in thespeed of Fuzzy Joint Points
(FJP) algorithm. Since FJP approach is a basisfor fuzzy neighborhood based clustering …