Search Results - (( _ distribution clustering algorithm ) OR ( based evaluation based algorithm ))
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…The k-means and the Gaussian mixture distribution were adopted as the clustering algorithms and each algorithm was tested on four datasets with four distinct clustering evaluation criteria: Calinski-Harabasz, Davies-Bouldin, Gap and Silhouette. …”
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Book Chapter -
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…One of the main issues in genetic k-means based algorithms is their sensitivity to outliers and unevenly distributed clusters due to the mean compromised computations. …”
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3
Spectrum aware clustering algorithm based on fuzzy logic for sensor based monitoring application / Noorhayati Mohamed Noor …[et al.]
Published 2020“…To evaluate the proposed clustering algorithm, the performance of sensor networks is compared with CogLEACH, LEACH and CHEF routing protocols. …”
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A Center-Based Stable Evolving Clustering Algorithm With Grid Partitioning And Extended Mobility Features For VANETs
Published 2020“…An improvement percentage of the efficiency in (CEC-GP) over the benchmarks Center based stable clustering (CBSC) and evolving data clustering algorithm (EDCA) is 65% and 394% respectively.…”
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Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering
Published 2024“…The fuzzy C-ordered-means clustering (FCOM) is a fuzzy clustering algorithm that enhances robustness and clustering accuracy through the ordered mechanism based on fuzzy C-means (FCM). …”
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Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm
Published 2020“…Existing approaches for this optimization problem have several drawbacks, including non-adaptive network configuration that may cause premature death of sensor nodes. Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control
Published 2017“…The simulation results show that FLCCA performs better than Distributed Fuzzy Score based Clustering Algorithm (DFSCA).…”
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A cluster-based hybrid replica control protocol for high availability in data grid
Published 2019“…Another proposed algorithm is replica placement algorithm which selects and places only one replica in each cluster. …”
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Adaptive System State Based Load Balancing For Web Application Server Cluster Of Heterogeneous Performance Nodes
Published 2013“…Finally, from the analyzed and evaluated performance results it can be deduced that the proposed ASS (Adaptive System State) DNS-based algorithms managed to improve the overall performance in term of execution time by 78.87%. …”
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10
Web cluster load balancing via genetic-fuzzy based algorithm
Published 2007“…In this genetic-fuzzy based Generalized Dimension Exchange (GDE) method is proposed to uniformly distribute the unprecedented Web cluster workload. …”
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Extreme learning machine classification of file clusters for evaluating content-based feature vectors
Published 2018“…The methods are Byte Frequency Distribution, Entropy, and Rate of Change. Consequently, an Extreme Learning Machine (ELM) neural network algorithm is used to evaluate the performance of the three methods in which it classifies the class label of the feature vectors to JPEG and Non-JPEG images for files in different file formats. …”
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A cluster analysis of population based cancer registry in Brunei Darussalam : an exploratory study
Published 2022“…Four clustering algorithms are explored in the cluster analysis of Brunei Darussalam Cancer Registry; Two-step, Partitional Around Medoid, Agglomerative Hierarchical and Model-based. …”
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An enhanced version of black hole algorithm via levy flight for optimization and data lustering problems
Published 2019“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems, in which it is a population-based metaheuristic that emulates the phenomenon of the black holes in the universe. …”
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An enhanced version of black hole algorithm via levy flight for optimization and data clustering problems
Published 2019“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems, in which it is a population-based metaheuristic that emulates the phenomenon of the black holes in the universe. …”
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Development of an effective clustering algorithm for older fallers
Published 2022“…The purpose of this study was, therefore, to develop a clustering-based algorithm to determine falls risk. …”
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Task scheduling on computational grids using Gravitational Search Algorithm
Published 2014“…In this paper, Gravitational Search Algorithm (GSA), as one of the latest population-based metaheuristic algorithms, is used for task scheduling on computational Grids. …”
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Transmission path optimization Based on Efficiency Communication System
Published 2022“…At the same time, the developed algorithm combines the relative position of the cluster and the base station to further improve the routing method of the sub-cluster head, Finally, the algorithm analyzes the influence of different parameters on the transmission path, and use the simulation experiments to evaluate the conclusions.…”
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
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ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs
Published 2021“…A novel and efficient cluster head selection algorithm (ECHSA) is employed to improve the performance of the cluster head (CH) selection process in clustered WSN. …”
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Classification of JPEG files by using extreme learning machine
Published 2018“…The algorithm automatically classifies the files based on evaluation measures of three methods Entropy, Byte Frequency Distribution and Rate of Change. …”
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