Search Results - (( java implementation clustering algorithm ) OR ( using data based 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 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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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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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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Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms
Published 2014“…This study explores the performance accuracies of partitioning-based algorithms and probabilistic model-based algorithm. …”
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Image Encrytion Using Block Based Transformation Algorithm
Published 2008“…Most of the available encryption algorithms are mainly used for textual data and may not be suitable for multimedia data such as images. …”
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A study of density-grid based clustering algorithms on data streams
Published 2011“…In this paper we review the grid based clustering algorithms that use density-based algorithms or density concept for the clustering. …”
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Clustering Spatial Data Using a Kernel-Based Algorithm
Published 2005“…Therefore, this work comes up with new clustering algorithm using kernel-based methods for effective and efficient data analysis by exploring structures in the data.…”
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On density-based data streams clustering algorithms: A survey
Published 2017“…Recently, a lot of density-based clustering algorithms are extended for data streams. …”
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Clustering chemical data set using particle swarm optimization based algorithm
Published 2008“…We found that PSO algorithm reveals better performance than Ward’s algorithm on continuous data format; however for binary data format, Ward’s algorithm outperforms arrogantly.…”
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Predicting future sales using genetic algorithm: data mining sales / Siti Hajar Yaacob
Published 2014“…Besides that, Genetic Algorithm is applying to predict future sales based on the sales and product data. …”
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Implementation Of FPGA Based Encryption Chip Using VHD - Data Encryption Standard (DES) Algorithm
Published 2006“…There are many researchers used Data Encryption Standard (DES) Algorithm to implement in FPGAs. …”
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Monograph -
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MuDi-Stream: A multi density clustering algorithm for evolving data stream
Published 2016“…However, existing density-based data stream clustering algorithms are not without problem. …”
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LCSS-Based Algorithm for Computing Multivariate Data Set Similarity: A Case Study of Real-Time WSN Data
Published 2019“…To address this issue, we propose an efficient algorithm to measure the similarity indexes of multivariate data sets using a non-metric-based methodology. …”
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Case Slicing Technique for Feature Selection
Published 2004“…Since the 1960s, many algorithms for data classification have been proposed. …”
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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Classification is a process of grouping or placing data into appropriate categories or classes based on specificattributes or features to predict labels or classes of new data based on patternsobserved from previously trained data. …”
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