Ordered weighted averagingRobust methodsFuzzy clustering helps to find natural vague boundaries in data. The fuzzy c-means method is one of the most popular clustering methods based on minimization of a criterion function. However, one of the greatest disadvantages of this method is its sensitivity ...
Fuzzy C-Ordered-Means Clustering 来自 掌桥科研 喜欢 0 阅读量: 100 作者: JM Leski 摘要: Fuzzy clustering helps to find natural vague boundaries in data. The fuzzy c-means method is one of the most popular clustering methods based on minimization of a criterion function. However, one of the...
Besides, the clustering results are susceptible to the initial centroids and algorithm parameters. To overcome the influence of outliers on clustering results, this study combines the advantages of probability c-means and fuzzy c-ordered means to propose a fuzzy possibilistic c-ordered means (FPCOM)...
【24hr】Towards a robust fuzzy clustering 包量 机译 迈向鲁棒的模糊聚类 作者:Jacek Leski; 刊名:Fuzzy sets and systems 2003年第2期 摘要:Fuzzy clustering helps to find natural vague boundaries in data. The Fuzzy C-Means method (FCM) is one of the most popular clustering methods based on ...
Clustering algorithm This segment is devoted to put forward the MCGDM model on the basis of propounding theory. Let \({\mathcal {O}}=\left\{ {\mathcal {O}}_1,{\mathcal {O}}_2,...,{\mathcal {O}}_m \right\}\) be the alternatives set, \({\mathcal {C}}=\left\{ {\mat...
Among the most popular clustering methods is the fuzzy c-means one. Its generalization by application of hyperplane shaped prototypes of the clusters is known as theFuzzyC-RegressionModels (FCRM) method. Since this method is very sensitive to poor initialization and to the presence of noise and...
BRT fuzzy LOS criteria for the calm passenger group and the anxious passenger group, respectively, were proposed using fuzzy C-means clustering. The TCQSMs did not consider passengers’ heterogeneity and provided a set of general LOS criteria for bus transit. However, this research work examines ...
Wei D, Wang Z, Si L, Tan C, Lu X (2021) An image segmentation method based on a modified local-information weighted intuitionistic Fuzzy C-means clustering and Gold-panning Algorithm. Eng Appl Artif Intell. https://doi.org/10.1016/j.engappai.2021.104209 Article Google Scholar Wei D, ...
Fuzzy C-Means (FCM) is a widely used algorithm that assigns a degree of membership to each data sample for clustering purposes (JC 1973). Our approach involves an extension of FCM due to its advantages in facilitating time-window issues, achieving (local) optimal convergence, and minimizing th...
Fast and Robust Fuzzy C-Means Clustering Algorithms Incorporating Local Information for Image Segmentation 热度: Fuzzy c-means clustering with non local spatial information for noisy image segmentation 热度: O'Reilly - Making Things See- 3D vision with Kinect, Processing, Arduino, and MakerBot ...