Search Results - (( using optimisation based algorithm ) OR ( using computing clustering algorithm ))*
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…For fingerprint database optimisation, novel access point (AP) selection algorithms which are based on variant AP selection are investigated to improve computational accuracy compared to existing AP selection algorithms such as Max-Mean and InfoGain. …”
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Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement
Published 2023“…Similar to how human eyes and binocular vision perceive depth, the visual disparity information obtained from this pair of images captured by the cameras represents the impression of perceived depth. The stereo vision algorithm computes disparity using local, global, and semiglobal optimisation methods established by the researcher. …”
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Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem
Published 2017“…The problem is even more complex using virtualized clusters in a cloud computing to execute a large number of tasks. …”
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Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment
Published 2024“…Hadoop distributed architecture is used to design and implement the power private cloud computing cluster. …”
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Improvement of routing protocol in wireless sensor network for energy consumption to maximize network lifetime
Published 2013“…This document is a study about hierarchical cluster-based routing protocol algorithm where the implementation was done using Matlab simulator to study the performance of this algorithm in term of lifetime. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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Feature clustering for pso-based feature construction on high-dimensional data
Published 2019“…The Redundancy-Based Feature Clustering (RFC) algorithm was applied to choose the most informative features from the original data, while PSO was used to construct new features from those selected by RFC. …”
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New techniques incorporating computational intelligence based for voltage stability evaluation and improvement in power system / Nur Fadilah Ab. Aziz
Published 2014“…Another new hybrid algorithm that used Evolutionary Programming (EP) termed as Evolutionary Support Vector Machine (ESVM) was also developed for comparative study. …”
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Instance matching framework for heterogeneous semantic web content over linked data environment
Published 2021“…These discovered attributes serve as input to a modified training set generation component, where training sets are generated based on the potential attributes’ clusters. Property alignment check the irregular data associated to the generated sets to optimise the matching performance. …”
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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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Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction
Published 2024“…The findings of the experiments are compared to the outcomes of BOCEDS, CEDAS, and MuDi-Stream algorithms. The outcomes indicate that the EWR algorithm outperformed the baseline clustering algorithms. …”
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MuDi-Stream: A multi density clustering algorithm for evolving data stream
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Autonomous and deterministic supervised fuzzy clustering
Published 2010“…The results obtained show that the model that uses the global k-means clustering algorithm 1 has higher accuracy when compared to a model that uses the k-means clustering algorithm. …”
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An adaptive density-based method for clustering evolving data streams / Amineh Amini
Published 2014“…However, existing density-based data stream clustering algorithms are not without problems. The first problem refers to the high computation time required for the clustering process. …”
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Data clustering using the bees algorithm
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An improved ACS algorithm for data clustering
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Biological-based semi-supervised clustering algorithm to improve gene function prediction
Published 2011“…However, commonclustering algorithms do not provide a comprehensive approach that look into the three categories of annotations; biologicalprocess, molecular function, and cellular component, and were not tested with different functional annotation database formats.Furthermore, the traditional clustering algorithms use random initialization which causes inconsistent cluster generation and areunable to determine the number of clusters involved. …”
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Computational Discovery of Motifs Using Hierarchical Clustering Techniques
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