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 Semantic Scholar 喜欢 0 阅读量: 99 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 ...
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)...
There has been many clustering approaches applied to a variety of fuzzy systems. E.g., fuzzy c-Means has been used in [153] to generate hierarchical structured fuzzy rules, in [154] rule structure was initialized using the possibilistic clustering algorithm for NFS; subtractive clustering has ...
A convex semi-nonnegative matrix factorisation approach to fuzzy c-means clustering 机译:凸半负矩阵分解的模糊c均值聚类方法 Suleman Abdul, Fuzzy sets and systems 2015 原文传递 原文传递并翻译 示例 加入购物车 收藏 分享 5 Dynamic classifier aggregation using interaction-sensitive fuzzy measures ...
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...
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 ...
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...
This paper presents two new types of clustering algorithms by using tolerance vector called tolerant fuzzy c-means clustering and tolerant possibilistic clustering. In the proposed algorithms, the new concept of tolerance vector plays very important role. The original concept is developed to handle data...
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, ...