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weight-based distributed clustering algorithm

Comparative Study of Weighted Clustering Algorithms for Mobile Ad Hoc Networks

Comparative Study of Weighted Clustering Algorithms for Mobile Ad Hoc Networks

... The weight-based distributed clustering algorithm (WCA) [4] takes into consideration, the ideal degree, transmission power, mobility, and battery power of mobile ...is based on ...

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EFFICIENCY ENHANCEMENT OF CLUSTER STABILITY AND ENERGY CONSUMPTION IN THE CLUSTERING ALGORITHMS

EFFICIENCY ENHANCEMENT OF CLUSTER STABILITY AND ENERGY CONSUMPTION IN THE CLUSTERING ALGORITHMS

... a weight based distributed clustering algorithm (WCA) is presented which can dynamically adapt itself with the ever changing topology of ad hoc networks is ...for clustering a ...

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A Hybrid Weight Based Clustering Algorithm for Wireless Sensor Networks

A Hybrid Weight Based Clustering Algorithm for Wireless Sensor Networks

... a distributed clustering algorithm which combines a hybrid metric composed by one hop neighborhood, consumed energy and distance from base ...time based on value of the hybrid metric to ...

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An intelligent routing protocol based on 
		artificial neural network for wireless sensor networks

An intelligent routing protocol based on artificial neural network for wireless sensor networks

... [15], Distributed Weight-based Energy-efficient Hierarchical Clustering protocol (DWEHC) [16], Position- based Aggregator Node Election protocol (PANEL) [17, 18], Two-Level Hierarchy ...

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Vol 5, No 1 (2013)

Vol 5, No 1 (2013)

... Unequal Clustering mechanism (EEUC), was anticipated for uniform energy consumption within the ...sizes. Based on nodes’ residual energy, connectivity and a unique node identifier, the cluster head ...

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A Survey of Cluster formation Protocols in Wireless Sensor Networks

A Survey of Cluster formation Protocols in Wireless Sensor Networks

... a Distributed Weight-based Energy-Efficient Hierarchical Clustering protocol ...iterations algorithm ends. It defines a weight factor for CH election ...process. Weight of ...

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Stable and Flexible Weight based Clustering Algorithm in Mobile Ad hoc Networks

Stable and Flexible Weight based Clustering Algorithm in Mobile Ad hoc Networks

... namely distributed clustering algorithm (DCA) and distributed mobility adaptive clustering algorithm (DMAC), proposed by Basagni et ...0) based on that a node may be a CH ...

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CLUSTERING WITH SIDE INFORMATION FOR MINING TEXT DATA

CLUSTERING WITH SIDE INFORMATION FOR MINING TEXT DATA

... Text mining, also referred to as text data mining, roughly equivalent to text analytics, refers to the process of deriving high-quality information from text. High-quality information is typically derived through the ...

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A Study on Clustering Algorithms for Large Datasets

A Study on Clustering Algorithms for Large Datasets

... pattern clustering methods from a statistical pattern recognition perspective, with a goal of providing useful advice and references to fundamental concepts accessible to the broad community of clustering ...

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Clustering algorithm for audio signals based on the sequential Psim matrix and Tabu Search

Clustering algorithm for audio signals based on the sequential Psim matrix and Tabu Search

... Traditional similarity measurement methods (e.g., the Eu- clidean distance, Jaccard coefficient [12], and Pearson co- efficient [12]) fail in high-dimensional space because in these methods, equidistance is a common ...

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Neural Network based LEACH Clustering Algorithm
in WSN

Neural Network based LEACH Clustering Algorithm in WSN

... This paper concluded a survey of the most important application of neural network. The main purpose of the study is to select the cluster head which aggregates the data and send it to the sink by the use of neural ...

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An energy efficient distributed clustering algorithm for heterogeneous WSNs

An energy efficient distributed clustering algorithm for heterogeneous WSNs

... existing clustering schemes are geared towards homogeneous ...developed distributed energy-efficient clustering (EDDEEC) scheme for heterogeneous ...and clustering-based routing ...is ...

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DYNAMIC DATA CLUSTERING UNDER DISTRIBUTED ENVIRONMENT

DYNAMIC DATA CLUSTERING UNDER DISTRIBUTED ENVIRONMENT

... centroid-based clustering, clusters are represented by a central vector, which may not necessarily be a member of the data ...K-means clustering gives a formal definition as an optimization problem: ...

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IJCSMC, Vol. 4, Issue. 5, May 2015, pg.135 – 147 RESEARCH ARTICLE An Efficient Approach Generating Optimized Clusters for Theoretic Clustering Using Data Mining

IJCSMC, Vol. 4, Issue. 5, May 2015, pg.135 – 147 RESEARCH ARTICLE An Efficient Approach Generating Optimized Clusters for Theoretic Clustering Using Data Mining

... Theoretic Clustering is an important task in data analysis and data mining ...theoretic clustering has been proposed, which is both memory and time efficient, while maintaining good level of ...

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Selection of Weighting Factors in Weighted Clustering Algorithm in MANET

Selection of Weighting Factors in Weighted Clustering Algorithm in MANET

... weighted clustering algorithm like MWCA(Modified Weighted Clustering algorithm), TRBC(Transmission Range based Clustering Algorithm), MPWCA (Mobility Prediction- ...

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Feature Subset Selection for High Dimensional Data Using Clustering Techniques

Feature Subset Selection for High Dimensional Data Using Clustering Techniques

... is based on the property that entropy tends to be low for data that contain tight ...Subspace clustering is an extension to attribute subset selection that has shown its strength at high- dimensional ...is ...

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Document Clustering In Distributed Environment

Document Clustering In Distributed Environment

... in distributed environments is known as DDM, and sometimes as Distributed Knowledge Discovery ...are distributed over a number of sites and that it is desirable to derive, through data mining ...

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OUTLIER DETECTION USING ENHANCED K-MEANS CLUSTERING ALGORITHM AND WEIGHT BASED CENTER APPROACH

OUTLIER DETECTION USING ENHANCED K-MEANS CLUSTERING ALGORITHM AND WEIGHT BASED CENTER APPROACH

... K-means clustering algorithm due to its certain ...K-means clustering algorithm is selection of initial centroid points ...proposed algorithm deals with this problem and improves the ...

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Adaptive E-Learning System Based On Learning Interactivity

Adaptive E-Learning System Based On Learning Interactivity

... Adaptive Web-based Educational systems (AWBES), a recognized class of adaptive Web systems [15] work against the "one size fits all" approach to E-Learning. After almost 8 years of research on adaptive ...

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Multimodel Document Summarization K-SVM Algorithm

Multimodel Document Summarization K-SVM Algorithm

... document clustering, retrieval of its related queries from past document clustering history has been done and learning the aspects by clustering the past queries and the associated click-through ...

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