Search Results - (( iot application clustering algorithm ) OR ( _ application bees algorithm ))
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Efficient tag grouping RFID anti-collision algorithm for internet of things applications based on improved k-means clustering
Published 2023“…But in dense IoT applications, much more than two tags can constitute a collision slot. …”
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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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Blockchain based security framework for device authentication and data communication in decentralized IoT network
Published 2023“…In light of the aforementioned issues, this thesis presents a lightweight, scalable, and secure authentication framework for IoT networks based on blockchain technology. First, this thesis proposes a clustering algorithm for IoT devices based on the device energy residues, the device location relative to other devices in the network, and the device computational ability. …”
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Thesis -
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A Review on Attack Graph Analysis for IoT Vulnerability Assessment: Challenges, Open Issues, and Future Directions
Published 2024“…In this review, core modeling techniques for IoT vulnerability assessment are highlighted, such as Markov Decision Processes (MDP), Feature Pyramid Networks (FPN), K-means clustering, and logistic regression models, along with other techniques involving genetic algorithms like fast-forward (FF), contingent fast-forwards (CFF), advanced reinforcement-learning algorithms, and HARMs models. …”
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Improved K-means clustering and adaptive distance threshold for energy reduction in WSN-IoTs
Published 2025“…This study introduces an enhanced energy aware clustering approach that combines an improved K-Means algorithm with an adaptive distance threshold to optimize relay node selection and cluster formation. …”
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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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Thesis -
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Analysis of Chinese patents associated with incremental clustering algorithms: A review / Archana Chaudhari
Published 2022“…To achieve learning from such dynamic data sources, incremental clustering algorithms are used mandatorily. This mandate has given rise to increased patents related to incremental clustering concept, which is primarily a significant part of Machine Learning field. …”
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Lightweight ontology architecture for QoS aware service discovery and semantic CoAP data management in heterogeneous IoT environment
Published 2026“…The architecture employs Modified-Ordered Points to Identify the Clustering Structure (M-OPTICS) to cluster and eliminate redundant IoT data. …”
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Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks
Published 2024thesis::doctoral thesis -
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Using the bees algorithm to optimise a support vector machine for wood defect classification
Published 2007“…This paper describes a new application of the Bees Algorithm to the optimization of a Support Vector Machine (SVM) for the problem of classifying defects in plywood. …”
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Conference or Workshop Item -
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Application of the bees algorithm to the selection features for manufacturing data
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Application of Bee Colony Optimization (BCO) in NP-Hard Problems
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Final Year Project -
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Optimal design of step – cone pulley problem using the bees algorithm
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Book Chapter -
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Application of the Bees Algorithm to find optimal drill path sequence
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Proceeding Paper -
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Assembly sequence optimization using the bees algorithm
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Book Chapter
