Search Results - (( iot applications _ algorithm ) OR ( its application clustering algorithm ))*
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Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream
Published 2023“…The AGMB algorithm is built upon three algorithms: 1) Grid-Multi-Buffer Stream Clustering (GMBSC), 2) Cautious Grid-Multi-Buffer Stream Clustering (C-GMBSC) and 3) Adaptive-Grid-Multi-Buffer Stream Clustering (A-GMBSC). …”
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Authentication-chains: blockchain-inspired lightweight authentication protocol for IoT networks
Published 2023“…Internet of Things networks (IoT) are becoming very important in industrial, medical, and commercial applications. …”
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Data clustering using the bees algorithm
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Enhancement Of Clustering Algorithm Using 3D Euclidean Distance To Improve Network Connectivity In Wireless Sensor Networks For Correlated Node Behaviours
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Modified ACS centroid memory for data clustering
Published 2019“…A comparison of the performance of several common clustering algorithms using real-world data sets shows that the accuracy of the proposed algorithm surpasses those of its counterparts.…”
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An improved ACS algorithm for data clustering
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Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering
Published 2024“…The fuzzy C-ordered-means clustering (FCOM) is a fuzzy clustering algorithm that enhances robustness and clustering accuracy through the ordered mechanism based on fuzzy C-means (FCM). …”
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Clustering of Chemical Compounds using Unsupervised Neural Networks Algorithms: a comparison
Published 2006“…In this work the applications of a number of self-organizing map (SOM) neural network algorithms to the clustering of chemical datasets are investigated. …”
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Dynamic Task Offloading Algorithm for optimising IoT network quality of service in the Mobile-Fog-Cloud System
Published 2023“…The application of the Internet of Things (IoT) is increasing to almost all aspects of human endevour. …”
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Clustering of chemical compounds using unsupervised neural networks algorithms : a comparison
Published 2006“…In this work the applications of a number of self-organizing map (SOM) neural network algorithms to the clustering of chemical datasets are investigated. …”
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