fuzzy self-organizing clustering
Catchment classification by runoff behaviour with self organizing maps (SOM)
... hierarchical clustering algorithm to define homogeneous regions for catchment re- ...and fuzzy c-means, which are straightforward in application and were found to iden- tify broadly similar ...
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Weight Optimize by Automatic Unsupervised Clustering using Computation Intelligence
... unsupervised clustering algorithm must apply the weight value with input pattern to process the outcome, for instance, Kohonen’s Winner-Take- All’s network,Kohonen self-organizing feature maps and ...
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Clustering Web Usage Data using Concept Hierarchy and Self Organizing Map
... of clustering algorithms such as partition based, distance based, density based, grid based, hierarchical and fuzzy clustering algorithms are used to find clusters from Web usage ...data.These ...
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Incremental clustering of sonar images using self-organizing maps combined with fuzzy adaptive resonance theory
... In this work, a new approach for unsupervised segmentation of sidescan sonar images is proposed. Our approach is based on the mixture of two neural network algorithms: the SOM and ART algorithms. The SOM algorithm is a ...
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A Survey on Economic Load Dispatch Problem Using Particle Swarm Optimization Technique
... (IPSO), self-organizing particle swarm optimization (SOH-PSO), fuzzy clustering-based particle swarm optimization (FCPSO), quantum-inspired particle swarm optimization (QPSO), modified ...
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An Application of Partitive Clustering Algorithm for Landslide Hazard Zonation
... [8], fuzzy logic [9], geographic information system [9][10], self-organizing map [12] and artificial neural network models ...Kohonen self-organizing maps (SOM) as part of the ...
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NGTSOM: A Novel Data Clustering Algorithm Based on Game Theoretic and Self- Organizing Map
... The Fuzzy C-means (FCM) algorithm [6], [7] puts forward a concept called partial ...a fuzzy clustering ...the clustering. In this method, the K-means clustering algorithm was used as a ...
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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
... the self-organizing map is carried out in such a way that units with similar weight vectors have similar colors, using a naive contraction model based on the U-matrix according to the algorithm proposed by ...
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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, ...
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A Comparison among Data Mining Algorithms for Outlier Detection using Flow Pattern Experiments
... hierarchical clustering, LSC-mine, self-organizing map, fuzzy C-means clustering, and voting are the methods employed in this ...
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Energy Based Clustering Self Organizing Map Protocol For Wireless Sensor Networks
... Low Energy Adaptive Clustering Hierarchy (LEACH) by Heinzelman et al., (2000) is the most famous clustering protocol which had been a basis for many further clustering protocols. The most important ...
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SERA: A Circular Path Clustering Approach For Wireless Sensor Network
... parameters. Clustering in wireless ad hoc networks is used to organize a network since the dynamic and mobile nature of the ...a self-organizing based clustering method using zone-based group ...
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Efficient Survivable Self Organization for Prolonged Lifetime in Wireless Sensor Networks
... dual-homed clustering) provides robustness for WSNs without relying on the redundancy of dedicated sensors and node ...the clustering process to determine backup routes from sources to observers, thus ...
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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 ...
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Kohonen Self Organizing Map with Modified K-means clustering For High Dimensional Data Set
... data clustering in the field of data ...data clustering purposes but none can be as fast and accurate as the K-Means ...to clustering high dimensional data set because its complexity tends to make ...
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A modified kohonen self-organizing map (KSOM) clustering for four categorical data
... The KSOM algorithm has succeeded in clustering and solving complex problems in many areas, especially when they involve high dimensional data. However, this KSOM algorithm is incapable of handling the feature ...
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Using self-organizing maps for visualization and interpretation of cytometry data
... The FlowSOM package provides new visualization opportunities for cytometry data. A four-step algorithm is provided: first, the data is read and preprocessed, then a self-organizing map is trained and a ...
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SELF ORGANIZING MAP BASED CLUSTERING MODEL BY ANALYZING EIGEN SYSTEM OF PCA
... in clustering of the SOM ...means clustering algorithm,other clustering techniques can be used to cluster eigenvalues and eigenvectors of the covariance matrix and also to produce final clusters from ...
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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 ...
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A REVIEW ON SELF-ORGANIZING CLUSTERING METHODS FOR ENERGY-EFFICIENT DATA GATHERING IN SENSOR NETWORKS
... Unequal Clustering Mechanism For Wireless Sensor Networks(EEUC) [7] This method of unequal clustering wisely cluster the network into unequal size ...
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