Search Results - (( java implementation clustering algorithm ) OR ( based testing function algorithm ))
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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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Thesis -
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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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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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March-based diagnosis algorithm for static random-access memory stuck-at faults and transition faults
Published 2012“…Therefore, this thesis proposed a new two phase algorithm based on March tests to specifically distinguish the two faults. …”
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A block cipher based on genetic algorithm
Published 2016“…In many algorithms which are based on the genetic algorithm approach, diffusion properties using crossover and mutation function are being generated to produce a secure data transmission. …”
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Performance Evaluation of Vector Evaluated Gravitational Search Algorithms Based on ZDT Test Functions
Published 2014“…Performance evaluation is done based on ZDT test functions, which is a common benchmark problem for multiobjective optimization. …”
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Biological-based semi-supervised clustering algorithm to improve gene function prediction
Published 2011“…In addition, CluFA is more comprehensive in its capability to predict the functions of unknowngenes. We tested our new computational framework for semi-supervised clustering of yeast gene expression data based onmultiple functional annotation databases. …”
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Hybrid artificial immune system-genetic algorithm optimization based on mathematical test functions
Published 2023“…To differentiate between the results in terms of achieving the minimum value for these functions, eight mathematical test functions are being used to make comparison. �2010 IEEE.…”
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An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion
Published 2018“…In order to identify the strength and weakness of these algorithms for MC/DC compliant test cases, this research proposes an experimental study involving four neighborhoods based meta-heuristic algorithms. …”
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Transform of Artificial Immune System algorithm optimization based on mathematical test function
Published 2023Conference Paper -
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…Thereafter, a multi-objective hybrid algorithm (MOHA), an extension of the self-adaptive hybrid algorithm is proposed and tested on the established multi-objective (MO) test functions. …”
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…The BOGS-BAT algorithm is based on three techniques. The first technique is to move or switch solution from single function to functions that contain more than one objective functions. …”
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Common benchmark functions for metaheuristic evaluation: a review
Published 2017“…In literature, benchmark test functions have been used for evaluating performance of metaheuristic algorithms. …”
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A Kalman-Filter-Based Sine-Cosine Algorithm
Published 2019“…A solution that has a lower cost function is considered as the best solution. The algorithm is tested with various benchmark functions and compared with the original SCA algorithm. …”
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