Aimed at the problem that the traditional suppressed fuzzy C-means clustering algorithms ignore the real needs of different objects, applying the same suppressed parameter for modifying membership degrees of all the objects, a novel partition region-based suppressed fuzzy C-means clustering algorithm ...
Thus, a new algorithm: suppressed fuzzy c-means clustering algorithm (S-FCM) is proposed. The new algorithm establishes more natural and more reasonable relationships between HCM clustering algorithm and FCM clustering algorithm. In addition, the algorithm is not sensitive to fuzzy factor. By ...
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...
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...
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 ...
"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, ...
Suppressed fuzzy c-means (s-FCM) clustering was introduced in [Fan, J. L., Zhen, W. Z., Xie, W. X.: Suppressed fuzzy c-means clustering algorithm. Patt. Recogn. Lett. 24, 1607鈥 1612 (2003)] with the intention of combining the higher speed of hard c-means (HCM) clustering ...
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 ...
Summary: Bias-corrected fuzzy c-means (BCFCM) algorithm with spatial information has been proven effective for image segmentation. It still lacks enough robustness to noise and outliers. Some kernel versions of FCM with spatial constraints, such as $KFCM\\_S_{1}, KFCM\\_S _{2}$ and GK...
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 ...