[PDF] Top 20 Self-Organizing and Clustering Methods in VANETs
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Self-Organizing and Clustering Methods in VANETs
... The number of vehicles rapidly increased in several countries, the rate of growth of new roads is much lower than that of vehicles. For these reasons number of accidents will increase and also traffic congestion. It ... See full document
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A REVIEW ON SELF-ORGANIZING CLUSTERING METHODS FOR ENERGY-EFFICIENT DATA GATHERING IN SENSOR NETWORKS
... overhead. clustering exploit data aggregation which reduces the amount of data for transmission and consequently increases the lifetime of the ...of clustering algorithms have been devised and some are ... See full document
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Improvement of self-organizing time divison multiple access in vehicular ad-hoc networks
... The medium Access Control (MAC) protocols are used in order to provide real-time and reliable communications (Katrin et al., 2009). MAC protocols for VANETs proposed in literature can be divided into two main ... See full document
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Semi-supervised consensus clustering for gene expression data analysis
... final clustering. The consensus clustering algorithms differ in chosen algo- rithms for basic clustering, consensus function and final ...hierarchical clustering(HC) or ... See full document
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Kohonen Self Organizing Map with Modified K-means clustering For High Dimensional Data Set
... One of the simplest and widely used partitioning based, nonhierarchical clustering methods is the K-Means. For any given set of numeric dataset X and an integer number k, the K-means algorithm searches for ... See full document
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SELF ORGANIZING MAP BASED CLUSTERING MODEL BY ANALYZING EIGEN SYSTEM OF PCA
... To implement the proposed algorithms,at first covariance matrix is generated from normalized data. The eigenvalues and eigenvectors of this covariance matrix are also computed which are thenindividually clustered by ... See full document
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Student behavior analysis using self organizing map clustering technique
... E-learning is the resulting product from the evolution of internet technology. It acts as a medium of learning virtually without limitation of time and space and the need for teachers to be present physically. Currently, ... See full document
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Catchment classification by runoff behaviour with self organizing maps (SOM)
... structures, clustering, visualizing results via plots and describing ...quality, clustering ecologic items or remote sensing methods to cluster soil ... See full document
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Big Data Clustering Using Heuristic Data Intensive Computing and Self Organizing Maps
... • The other packages contained in the “base” system include utils, stats, datasets, graphics, gr Devices, grid, methods, tools, parallel, compiler, splines, tcltk, stats4. There are also “Recommended” packages: ... See full document
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A modified kohonen self-organizing map (KSOM) clustering for four categorical data
... other methods, algorithms or filtering techniques to solve complex problems, such as signal and image ...conventional clustering techniques and being implemented in various ... See full document
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Clustering Web Usage Data using Concept Hierarchy and Self Organizing Map
... mining methods have been have been used to generate models of usage ...rules, clustering algorithms, sequential analysis and Markov models have been used for discovering the knowledge from Web usage ... See full document
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SOMSN: An Effective Self Organizing Map for Clustering of Social Networks
... of clustering algorithms have been proposed for data classification based on centrality ...divisive methods [5], [6] and in case they begin with a node they use agglomerative methods ...new ... See full document
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Hybrid Self-Organization Based Facility Layout Planning
... by methods such as lean production [1] or the implementation of cellular manufacturing systems ...formation methods have been proposed [3] to [6], and promising results have been reported by using a ... See full document
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Self Organized Mapping based Map Reduce technique in big data analytics: A Neural Nnetwork approach
... (i.e., organizing and managing the ...data, clustering has become a crucial part in identifying the similarities based on many parameters in a given data set that influences in decision ...this ... See full document
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Neural Network based Clustering using Visual Features of Characters‟ Shape in Image
... -- Clustering gathers similar ...Kohonen Self Organizing Map is used for clustering with four different topologies of sizes 6x5, 8x7, 9x8, and ...Kohonen Self Organizing Map ... See full document
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Self-organizin map clustering method for the analysis of e-learning activities
... SOM clustering technique to obtain clusters of students who have similar was of interacting with the e-learning environment, and analyze the effects of their behaviors on their learning ... See full document
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A Comparative Study of Brain Tumour Detection Using K- Harmonic Means, Expectation Maximization and Hierarchical Clustering Algorithms
... means clustering, Fuzzy C means, Hierarchical, Watershed Algorithms, and Self Organizing Maps are widely implemented depending on which methodology is required as it can be Region growing, frequency ... See full document
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Exploratory data analysis and clustering of multivariate spatial hydrogeological data by means of GEO3DSOM, a variant of Kohonen's Self Organizing Map
... Abstract. The use of unsupervised artificial neural network techniques like the self-organizing map (SOM) algorithm has proven to be a useful tool in exploratory data analysis and clustering of ... See full document
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Weight Optimize by Automatic Unsupervised Clustering using Computation Intelligence
... unsupervised clustering using computation intelligent (AUCCI) is useful to adjust the incremental weight learning by applying the first layer of radial basis function and membership function regarding AUCCI’s ... See full document
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An Application of Partitive Clustering Algorithm for Landslide Hazard Zonation
... The universal application of a self-organizing map (SOM) of Kohonen is for mapping n-dimensional input vectors to two-dimensional neurons or maps. This map describes the variations in the information of the ... See full document
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