Results 21 to 30 of about 376,662 (290)
On Fuzzy c-Means for Data with Tolerance
Journal of Advanced Computational Intelligence and Intelligent Informatics, 2006 This paper presents two new clustering algorithms which are based on the entropy regularized fuzzyc-means and can treat data with some errors. First, the tolerance is formulated and introduce into optimization problems of clustering. Next, the problems are solved using Kuhn-Tucker conditions. Last, the algorithms are constructed based on the results of
Ryuichi Murata +3 more
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A comparison of fuzzy approaches to e-commerce review rating prediction [PDF]
, 2015 This paper presents a comparative analysis of the performance of fuzzy approaches on the task of predicting customer review ratings using a computational intelligence framework based on a genetic algorithm for data dimensionality reduction.
Acampora, G, Cosma, G
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Intuitionistic Fuzzy Possibilistic C Means Clustering Algorithms
Advances in Fuzzy Systems, 2015 Intuitionistic fuzzy sets (IFSs) provide mathematical framework based on fuzzy sets to describe vagueness in data. It finds interesting and promising applications in different domains. Here, we develop an intuitionistic fuzzy possibilistic C means (IFPCM)
Arindam Chaudhuri
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Fuzzy image segmentation of generic shaped clusters [PDF]
, 2005 The segmentation performance of any clustering algorithm is very sensitive to the features in an image, which ultimately restricts their generalisation capability.
Ali, M. A. +2 more
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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
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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
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BarekengCluster analysis involves the methodical categorization of data based on the degree of similarity within each group to group data with similar characteristics. This study focuses on classifying poverty data across Indonesian provinces.
Dian Kurniasari +4 more
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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
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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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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
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