Results 31 to 40 of about 948,152 (383)
Median evidential c-means algorithm and its application to community detection [PDF]
, 2015 Median clustering is of great value for partitioning relational data. In this paper, a new prototype-based clustering method, called Median Evidential C-Means (MECM), which is an extension of median c-means and median fuzzy c-means on the theoretical ...
Liu, Zhun-Ga +3 more
core +4 more sources
Residual-driven Fuzzy C-Means Clustering for Image Segmentation [PDF]
IEEE/CAA Journal of Automatica Sinica, 2020 In this paper, we elaborate on residual-driven Fuzzy C-Means (FCM) for image segmentation, which is the first approach that realizes accurate residual (noise/outliers) estimation and enables noise-free image to participate in clustering.
Cong Wang +3 more
semanticscholar +1 more source
A Federated Fuzzy c-means Clustering Algorithm
Proceedings of WILF 2021, the 13th International Workshop on Fuzzy Logic and Applications (WILF 2021), 2021 Traditional clustering algorithms require data to be centralized on a single machine or in a datacenter. Due to privacy issues and traffic limitations, in several real applications data cannot be transferred, thus hampering the effectiveness of traditional clustering algorithms, which can operate only on locally stored data.
B��rcena, Jos�� Luis Corcuera +4 more
openaire +3 more sources
An improved fuzzy clustering image segmentation algorithm combining spatial information
Xi'an Gongcheng Daxue xuebao, 2021 In order to improve the ability of fuzzy C-means (FCM) clustering algorithm to suppress noise, an improved fuzzy clustering image segmentation algorithm was proposed.
Xudong LIU +4 more
doaj +1 more source
Probabilistic clustering algorithms for fuzzy rules decomposition [PDF]
, 2007 The fuzzy c-means (FCM) clustering algorithm is the best known and used method in fuzzy clustering and is generally applied to well defined set of data. In this paper a generalized Probabilistic fuzzy c-means (FCM) algorithm is proposed and applied to
Igrejas, Getúlio, Salgado, Paulo
core +1 more source
International Journal of Intelligent Systems, 2023 The problem of ordered clustering in the context of decision‐making with multiple criteria has garnered significant interest from researchers in the field of management science and operational research. In real‐world scenarios, the datasets often exhibit imprecision or uncertainty, which can lead to suboptimal ordered‐clustering outcomes.
Muhammad Adnan Bashir +2 more
openaire +1 more source
Superpixel-Based Fast Fuzzy C-Means Clustering for Color Image Segmentation
IEEE transactions on fuzzy systems, 2019 A great number of improved fuzzy c-means (FCM) clustering algorithms have been widely used for grayscale and color image segmentation. However, most of them are time-consuming and unable to provide desired segmentation results for color images due to two
Tao Lei +5 more
semanticscholar +1 more source
IEEE Access, 2020 Due to the rapid development of information technology and network technology, there is a lot of data, but the phenomenon of lack of knowledge is becoming more and more serious.
Yuan Huang +4 more
doaj +1 more source
Barekeng, 2023 Indonesia is a country that has a population density that is increasing every year, with the increase in population density, the crime rate in Indonesia is increasing. Criminal acts arise because they are supported by factors that cause crime. To improve
Bella Destia, Mujiati Dwi Kartikasari
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Turbid of Water By Using Fuzzy C- Means and Hard K- Means
مجلة بغداد للعلوم, 2020 In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected from the ...
Rand Muhaned Fawzi, Iden Hassan Alkanani
doaj +1 more source