[PDF] Top 20 A Fuzzy Graph-based Heuristic Algorithm of Possibilistic Clustering
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A Fuzzy Graph-based Heuristic Algorithm of Possibilistic Clustering
... the fuzzy objective function-based approach to clustering and values of the membership function of a possibilistic partition can be considered as typicality ...the possibilistic ... See full document
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Scalable Parallel Clustering Approach for Large Data using Possibilistic Fuzzy C Means Algorithm
... k-means clustering algorithm based on the message passing ...improved fuzzy clustering-text clustering method based on the fuzzy C-Means clustering ... See full document
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VALIDITY MEASURES FOR HEURISTIC POSSIBILISTIC CLUSTERING
... new heuristic method of fuzzy clustering was presented in [13], where concepts of fuzzy α -cluster and allotment among fuzzy α - clusters were introduced and a basic version of direct ... See full document
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Distances and Similarity Measures in Heuristic Possibilistic Clustering the Intuitionistic Fuzzy Data: A Comparative Study
... intuitionistic fuzzy sets for clustering the intuitionistic fuzzy data by using heuristic algorithms of possibilistic ...intuitionistic fuzzy set theory are described, in the ... See full document
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An Adaptive Fuzzy C Means Algorithm for Improving MRI Segmentation
... iterative algorithm to estimate spatially smooth member- ship ...the algorithm bias corrected FCM ...a fuzzy cluster method where the inhomogene- ity field was modeled by a B-spline ...enhanced ... See full document
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A graph clustering algorithm based on a clustering coefficient for weighted graphs
... our heuristic with the following graph clustering al- gorithms from the literature: a spin glass-based algorithm (Spinglass) [23], a fast greedy modularity-based algorithm ... See full document
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Title: Detection of WML in MRI Brain Images using Neuro-Fuzzy Inference System
... Geostatistical Fuzzy C-means clustering (GFCM) method is used for automatic detection of WMLs in brains of elderly ...of fuzzy clustering and possibilistic ,clustering algorithms ... See full document
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Enhanced Sentence-Level Text Clustering using Semantic Sentence Similarity from Different Aspects
... Sentence clustering plays a significant role in many textprocessing ...sentence clustering into extractive multidocument summarization useful to address issues of content overlap, leading to better ... See full document
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High Dimensional Data used in Consensus Neighbour Clustering with Fuzzy Based K-Means and Kernel Mapping
... consensus clustering methods, namely the K-means-based algorithm, the graph partitioning algorithm (GP), and the hierarchical algorithm (HCC), were employed for the comparison ... See full document
8
Clustering Optimal Algorithm- A Survey
... the clustering techniques. Clustering is the process of grouping the data according to some criteria that most similar data to form a ...in clustering. K-means clustering, Hierarchical ... See full document
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Intuitionistic Heuristic Prototype-based Algorithm of Possibilistic Clustering
... intuitionistic fuzzy-set clustering methods are also described by Xu in ...The heuristic approach to possibilistic clustering is generalized for a case of intuitionistic fuzzy ... See full document
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Selecting Parameters of the Fuzzy Possibilistic Clustering Algorithm
... The Fuzzy Possibilistic C-Means (FPCM) is one of the most popular clustering methods based on minimization of a criterion ...this algorithm requires a priori selection of some ... See full document
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Estimation of Bounds of the Set of Potential Number of Fuzzy Clusters in a Sought Clustering Structure
... A heuristic approach to possibilistic clustering is proposed in ...the heuristic approach to possibilistic clustering is that the sought clustering structure of the set of ... See full document
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Study on swarm optimization clustering algorithm
... FCM algorithm, the fuzzy kernel hierarchical clustering algorithm based on particle swarm algorithm is ...FCM algorithm, the new algorithm is guided by the ... See full document
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IMPLEMENT EFFICIENT AND EFFECTIVE FAST CLUSTERING-BASED FEATURE SELECTION ALGORITHM FOR HIGH-DIMENSIONAL DATA
... features. Based on some criteria, a fast clustering based feature selection algorithm is proposed and ...FAST algorithm works in two ...a graph theoretic approach and ... See full document
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Design and development of intelligent computational techniques for power quality data monitoring and management
... authority (Saudi Electricity Company, 2007) they too follow some standards defined by UAE Power distribution companies (Al Ain et al., 2005a, Al Ain et al., 2005b, Al Ain et al., 2005c). Most of the standards are made ... See full document
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Fuzzy clustering with volume prototypes and adaptive cluster merging
... When (4) is minimized by iterating between (6) and (8), the volume prototypes extend a distance from the cluster centers and the points within the volume prototypes are assigned a membership of one in the corresponding ... See full document
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Clustering based information retrieval with the aco and the k-means clustering algorithm
... data clustering and the feature selection ...searched based on two ...3) Clustering the database. Many algorithms use the query based models to retrieve the information from the ...database. ... See full document
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Müller, Nikola (2012): Finding correlations and independences in omics data. Dissertation, LMU München: Fakultät für Mathematik, Informatik und Statistik
... Parameter-freien Clustering Algorithmus entwickelt, der auf dem Konzept der Graph-Kom- pression beruht, um eng miteinander verbundene und ähnliche Proteine zu ... See full document
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An Efficient Automatic Clustering using Fuzzy Kernel Mapping with Density Clustering Algorithm
... classification, clustering gives an insight into the underlying structure of the ...different clustering procedures have been developed, ranging from simple heuristics suitable for a particular type of ... See full document
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