Search Results - (( java implementation clustering algorithm ) OR ( patterns using efficient algorithm ))
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Thesis -
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Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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Final Year Project -
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A web-based implementation of k-means algorithms
Published 2022“…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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Final Year Project / Dissertation / Thesis -
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Conference or Workshop Item -
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Efficient prime-based method for interactive mining of frequent patterns.
Published 2011“…During the mining process, the mining algorithm reduces the number of candidate patterns and comparisons by using a new candidate set called candidate head set and several efficient pruning techniques. …”
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A numerical method for frequent pattern mining
Published 2009“…The PC_Miner algorithm traverses the PC_Tree by using an efficient pruning technique. …”
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An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP
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Conference or Workshop Item -
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A new split based searching for exact pattern matching for natural texts
Published 2018“…Exact pattern matching algorithms are popular and used widely in several applications, such as molecular biology, text processing, image processing, web search engines, network intrusion detection systems and operating systems. …”
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Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset
Published 2018“…An abundant literature has dedicated in frequent pattern mining and tremendous efficient algorithms for frequent itemset mining in the transaction database. …”
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Prime-based method for interactive mining of frequent patterns
Published 2010“…Thus far, a few efficient interactive mining algorithms have been proposed. …”
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Butterfly traffic pattern in selection algorithm on hierarchical torus network
Published 2015“…In this paper, we have evaluated the dynamic communication performances of an HTN is evaluated by using dimension-order routing and LS+CS algorithm under butterfly traffic pattern. …”
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Proceeding Paper -
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Fast discovery of long patterns for association rules
Published 2003“…An algorithm called Flex for identifying frequent patterns especially efficient when the patterns are long is proposed by successive construction of the nodes lexicographic tree. …”
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Exploring High Resolution Test Pattern To Improve The Cache Failure Analysis
Published 2017“…Finally, the high resolution test pattern is being used in real case application for proving the high resolution test pattern have the capability in improving FA efficiency in identifying the failing bits. …”
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Thesis -
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Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification
Published 2017“…The results obtained illustrate that HPABC algorithm can efficiently be used for ANNT. HPABC outperformed the original ABC and PSO as well as other state-of-art and hybrid algorithms in terms of time, function evaluation number and recognition accuracy.…”
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Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification
Published 2017“…In this work, we aimed to highlight the performance of the Hybrid Particle-move Artificial Bee Colony (HPABC) algorithm by applying it on the ANNT application.The performance of the HPABC algorithm was investigated on four benchmark pattern-classification data sets and the results were compared with other algorithms.The results obtained illustrate that HPABC algorithm can efficiently be used for ANNT.HPABC outperformed the original ABC and PSO as well as other state-of-art and hybrid algorithms in terms of time, function evaluation number and recognition accuracy.…”
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