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Expert systems with applications, ISSN 0957-4174, 2015, Volume 42, Issue 21, pp. 7541 - 7548
.... Fuzzy C-means has been utilized successfully in a wide range of applications, extending the clustering capability of the K-means to datasets that are uncertain, vague and otherwise hard to cluster... 
Cluster analysis | Initialization | Fuzzy C-means clustering | Computer science | Analysis | Algorithms | Fuzzy sets | Nucleation | Data sets | Clusters | Fuzzy | Standards | Convergence
Journal Article
Bioinformatics, ISSN 1367-4803, 11/2010, Volume 26, Issue 22, pp. 2841 - 2848
Motivation: Fuzzy c-means clustering is widely used to identify cluster structures in high-dimensional datasets, such as those obtained in DNA microarray and quantitative proteomics experiments... 
BIOTECHNOLOGY & APPLIED MICROBIOLOGY | BIOCHEMICAL RESEARCH METHODS | MATHEMATICAL & COMPUTATIONAL BIOLOGY | PATTERNS | EXPRESSION | MICROARRAY DATA | SIGNALING NETWORKS | Oligonucleotide Array Sequence Analysis - methods | Fuzzy Logic | Pattern Recognition, Automated - methods | Proteomics | Cluster Analysis
Journal Article
Applied soft computing, ISSN 1568-4946, 2018, Volume 67, pp. 299 - 308
.... Cluster analysis is a very useful data mining approach. Although many clustering algorithms have been proposed, it is very difficult to find a clustering method which is suitable for all types of datasets... 
Cluster analysis | Kernel function | Intuitionistic fuzzy set | Metaheuristics | Genetic algorithm | Artificial bee colony algorithm | Particle swarm optimization | Fuzzy c-means | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | Fuzzy c-meansa | OPTIMIZATION | SEPARATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Case studies | Algorithms | Stores | Data mining | Mathematical optimization
Journal Article
Journal of Small Business and Enterprise Development, ISSN 1462-6004, 10/2018, Volume 25, Issue 5, pp. 769 - 790
...’ resources and capabilities in explaining the probability to export. Design/methodology/approach The study employs the nascent fuzzy c-means clustering technique to analyse a sample of 208 Algerian SMEs... 
Cluster analysis Fuzzy c-means | Resources and capabilities | Algeria | SMEs | Export propensity | Studies | Cluster analysis | Entrepreneurship | Pricing policies | Principal components analysis | Small & medium sized enterprises-SME | Production capacity | Multivariate analysis | Exports | Marketing
Journal Article
中国科学:信息科学(英文版), ISSN 1674-733X, 2014, Volume 57, Issue 11, pp. 1 - 8
Fuzzy c-means (FCM) algorithm is an important clustering method in pattern recognition, while the fuzziness parameter, m, in FCM algorithm is a key parameter that can significantly affect the result of clustering... 
聚类结果 | 群集 | 有效性指数 | 聚类方法 | 验证 | FCM算法 | 模糊c均值 | 参数选择 | fuzziness parameter | cluster validation | Computer Science | cluster validity index | Information Systems and Communication Service | clustering | fuzzy c-means (FCM) | FCM | NUMBER | DENSITIES | ALGORITHM | COMPUTER SCIENCE, INFORMATION SYSTEMS | VALIDITY INDEXES | DIFFERENT SIZES | Decision-making | Analysis | Algorithms | Fuzzy logic | Data sets | Clusters | Fuzzy set theory | Fuzzy | Clustering | Optimization
Journal Article
Expert systems with applications, ISSN 0957-4174, 2016, Volume 58, pp. 76 - 82
.... Cluster analysis is a useful tool used commonly in data analysis. The purpose of cluster analysis is to separate data sets into subsets according to their similarities and dissimilarities... 
Fuzzy c-means algorithm | Clustering algorithm | Directional data | Angular difference | MIXTURES | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Algorithms | Cluster analysis | Analogies | Approximation | Consistency | Fuzzy | Clustering | Expert systems
Journal Article
Mathematical problems in engineering, ISSN 1024-123X, 8/2016, Volume 2016
.... Together with the theoretical analysis, a new fuzzy c -means (FCM) clustering algorithm with random projection has been presented... 
MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | ENGINEERING, MULTIDISCIPLINARY | ALGORITHMS | Analysis | Big data | Algorithms | Datasets | Economic models | Data analysis | Laboratories | Efficiency | Colleges & universities | Big Data | Random variables | Clustering | Methods | Data management | Preserves | Clusters | Projection | Robustness | Fuzzy
Journal Article
Journal Article
Expert systems with applications, ISSN 0957-4174, 2009, Volume 36, Issue 9, pp. 11772 - 11781
...) and fuzzy C-means method (FCM) for strategic grouping. Findings reveal that traditional cluster analysis methods cannot disclose the overlapping strategic group structure and position of companies within the same strategic group. It is concluded that SOM and FCM can reveal the typology of the strategic groups better than traditional cluster analysis and they are more likely to provide useful information about the real strategic group structure. 
Fuzzy C-means | Strategic groups | Self-organizing map | Traditional cluster analysis techniques | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | MANAGEMENT | SEGMENTATION | NEURAL-NETWORK | ALGORITHMS | VALIDITY | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
Pattern recognition, ISSN 0031-3203, 2012, Volume 45, Issue 1, pp. 407 - 415
The weighting exponent m is called the fuzzifier that can influence the performance of fuzzy c-means (FCM... 
Cluster core | Fuzzy clustering | Fuzzy c-means | CLUSTERING ALGORITHMS | MODEL | QUANTIZATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Analysis | Algorithms
Journal Article
Sadhana (Bangalore), ISSN 0973-7677, 2019, Volume 44, Issue 8, pp. 1 - 7
Fuzzy c-mean (FCM) is one of the widely used data clustering methods. FCM method not only divides a data set into several clusters but also determines the potential belongingness of each data in different clusters... 
equal size clustering | Engineering | size constraint | customized clustering | data mining | Engineering, general | Fuzzy c -mean | ENGINEERING, MULTIDISCIPLINARY | ALGORITHM | Fuzzy c-mean | Data mining | Analysis | Algorithms
Journal Article
Computational intelligence and neuroscience, ISSN 1687-5265, 11/2016, Volume 2016, p. 2647389
For the shortcoming of fuzzy c-means algorithm (FCM) needing to know the number of clusters in advance, this paper proposed a new self-adaptive method to determine the optimal number of clusters... 
VALIDITY INDEX | NEUROSCIENCES | MATHEMATICAL & COMPUTATIONAL BIOLOGY | Algorithms | Datasets as Topic | Pattern Recognition, Automated | Fuzzy Logic | Humans | Cluster Analysis | Fuzzy logic | Cluster analysis | Mathematical research | Fuzzy algorithms | Research | Fuzzy systems | Datasets | Studies | Fuzzy sets | Validity | Quality | Science | Euclidean space | Data mining | Clustering | Data sets | Clusters | Centroids | Fuzzy | Iterative methods | Optimization
Journal Article
The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, 5/2012, Volume 60, Issue 5, pp. 463 - 472
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