Intending to achieve an algorithm characterized by the quick convergence of hard c-means (HCM) and finer partitions of fuzzy c-means (FCM), suppressed fuzzy c-means (s-FCM) clustering was designed to augment the gap between high and low values of the fuzzy membership functions. Suppression ...
algorithm is regarded as a bridge to connect the hard C-means clustering algorithm and the fuzzy C-means clustering algorithm.In this paper,the current research status of suppressed fuzzy C-means clustering is reviewed,and some further researches and applications of these type algorithms are ...
In order to improve the effectiveness of intrusion detection, an intrusion detection method of the Internet of Things (IoT) is proposed by suppressed fuzzy clustering (SFC) algorithm and principal component analysis (PCA) algorithm. In this method, the data are classified into high-risk data and...
RETRACTED: A robust kernelized intuitionistic fuzzy c-means clustering algorithm in segmentation of noisy medical image Soni, and Anjana Gosain, "A robust kernelized intuitionistic fuzzy c-means clustering algorithm in segmentation of noisy medical images," Pattern Recognition ... Prabhjot,Kaur,K A.,...
Experimental results show that the algorithm in this article can achieve better clustering and segmentation performance than several state-of-the-art fuzzy clustering methods for color images with imbalanced sizes and features and noise injection.Fuzzy Systems, IEEE Trans. on (T-FUZZ)Haiyan YuShuang ...
The possibilistic c-means (PCM) clustering algorithm always suffers from a coincident clustering problem since it relaxes the probabilistic constraint in the fuzzy c-means (FCM) clustering algorithm. In this paper, to overcome the shortcoming of the PCM, a novel suppressed possibilistic c-means (S...
"A Fixed Suppressed Rate Selection Method for Suppressed Fuzzy C- Means Clustering Algorithm" Applied Mathematics, 5: 1275-1283.FAN J, LI J. A fixed suppressed rate selection method for suppressed fuzzy C -means clustering algorithm [J]. Applied Mathe- matics, 2014, 5(8) - 1 355.Fan, ...
The possibilistic c-means (PCM) clustering algorithm always suffers from a coincident clustering problem since it relaxes the probabilistic constraint in the fuzzy c-means (FCM) clustering algorithm. In this paper, to overcome the shortcoming of the PCM, a novel suppressed possibilistic c-means (S...
Suppressed relative entropy fuzzy c-means clustering algorithmsuppression ratepartition entropy coefficientalternating modified partition coefficientadaptive parameter selectionThe relative entropy fuzzy c-means (REFCM) clustering algorithm improves the robustness of the fuzzy c-means (FCM) algorithm against ...
Fuzzy C-Means clustering(FCM) algorithm plays an important role in image segmentation, but it is sensitive to noise because of not taking into account the spatial information. Addressing this problem, this paper presents an improved suppressed FCM algorithm based on the pixels and the spatial ...