Search Results - (( java implementation modified algorithm ) OR ( using process clustering algorithm ))
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1
Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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2
Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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3
Optimized clustering with modified K-means algorithm
Published 2021“…The proposed algorithm utilised a distance measure to compute the between groups’ separation to accelerate the process of identifying an optimal number of clusters using k-means. …”
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4
An efficient parallel clustering algorithm on big data using Spark
Published 2022“…Here we are proposing a new parallel fuzzy clustering algorithm called "An efficient parallel clustering algorithm on big data using spark" which deals with real-time processing. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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6
An enhanced cluster head selection algorithm for routing in mobile AD-HOC network
Published 2017“…This thesis proposes a cluster based routing protocol, the Enhanced Cluster Routing Protocol (ECRP), which uses a modified cluster formation algorithm to build the cluster structure and select one of the nodes to be the cluster head. …”
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7
OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
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Clustering chemical data set using particle swarm optimization based algorithm
Published 2008“…The biological activities of these compounds have a large significance in the process of designing and discovering new drugs. Many algorithms had been applied to cluster chemical data set such as Ward’s algorithm. …”
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9
Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin
Published 2016“…This research purposed clustering algorithm to improve process extracting feature in images to get meaningful information because it can speed up the time to process of extracting meaningful information in images due to the efficient of the algorithm that has high performance to process the image. …”
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10
Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream
Published 2023“…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
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Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim
Published 2012“…The objectives of this project to set-up Beowulf cluster computer to apply the Travelling Salesman Problem in parallel by using Genetic Algorithms and evaluate sequential algorithms and parallel algorithms by Genetic Algorithms. …”
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12
A Hybrid K-Means Hierarchical Algorithm for Natural Disaster Mitigation Clustering
Published 2022“…This study also added keyword and disaster-type fields to provide additional information for a better clustering process. The clustering process produced three clusters for the anticipation level of natural disaster mitigation. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar
Published 2016“…This unsupervised learning usually leads to undirected knowledge discovery. The cluster detection algorithm searches for clusters of data which are similar to one another by using similarity measures. …”
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15
Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor
Published 2010“…This project is about segmentation of FLAIR brain Magnetic Resonance Image (MRI) using K-Means Clustering algorithm. A prototype system of brain segmentation is developed by implementing K-Means Clustering algorithm. …”
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16
An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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17
A novel clustering based genetic algorithm for route optimization
Published 2016“…It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”
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Improved clustering using robust and classical principal component
Published 2017“…k-means algorithm is a popular data clustering algorithm. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. …”
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20
Adaptive firefly algorithm for hierarchical text clustering
Published 2016“…The proposed Adaptive Firefly Algorithm (AFA) consists of three components: document clustering, cluster refining, and cluster merging. …”
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