Search Results - (( mobile evaluation clustering algorithm ) OR ( based classification _ algorithm ))*
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Hybrid intelligent approach for network intrusion detection
Published 2015“…Due to the prevailing limitations of finding novel attacks, high false detection, and accuracy in previous intrusion detection approaches, this study has proposed a hybrid intelligent approach for network intrusion detection based on k-means clustering algorithm and support vector machine classification algorithm. …”
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Centre based evolving clustering framework with extended mobility features for vehicular ad-hoc networks
Published 2021“…Due to the high mobility of vehicles in VANET, it is more attractive to adapt the evolving data clustering to an evolving VANET clustering framework. …”
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A Center-Based Stable Evolving Clustering Algorithm With Grid Partitioning And Extended Mobility Features For VANETs
Published 2020“…An improvement percentage of the efficiency in (CEC-GP) over the benchmarks Center based stable clustering (CBSC) and evolving data clustering algorithm (EDCA) is 65% and 394% respectively.…”
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Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network
Published 2023“…The effectiveness of the clustering model is the most important challenge. The K-Means clustering algorithm is an effective algorithm for multi-clusters that can be used in VANETs. …”
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Evaluation of Clustering and Multi-hop Routing Protocols in Mobile Ad-hoc Sensor Networks
Published 2015“…One of the techniques to conserve more energy is through topology management using clustering network. A HEED (Hybrid, Energy-Efficient, Distributed) is one of the clustering algorithm for sensor networks. …”
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Cauchy Density-based Algorithm for VANETs Clustering in 3D Road Environments
Published 2022“…In addition, a clustering algorithm that defines mobility vector and uses Cauchy-based density for enabling adding vehicles to their respective clusters. …”
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Text spam messages classification using Artificial Immune System (AIS) algorithms
Published 2024thesis::master thesis -
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An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control
Published 2017“…Simulation experiments were conducted to evaluate the performance of FLCCA in terms of the number of clusters formed, reaffiliation count and clustering control overheads. …”
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ChoCD : Usable and secure graphical password authentication scheme
Published 2024thesis::master thesis -
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A coverage path planning approach for autonomous radiation mapping with a mobile robot
Published 2023Article -
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A coalition model for efficient indexing in wireless sensor network with random mobility / Hazem Jihad Ali Badarneh
Published 2021“…The second evaluation divides into three scenarios. The first one evaluates Coalition-Based Index-Tree framework independently, without any effect from Dynamic-Coalition framework and Static-Coalition algorithm. …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique
Published 2018“…The clustering algorithm consists of two components: the temporal micro-clusters generation and the temporal micro clusters merging. …”
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QoS BASED ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORK
Published 2012“…Clustering within normal sensor nodes is done by optimizing the network/coverage lifetime through a cluster-head-selection algorithm and a sleep/wake scheduling algorithm. …”
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Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment
Published 2021“…After using the RANSAC algorithm to remove the map ground, the European clustering algorithm is used for point cloud segmentation. …”
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Position-based multicast routing in mobile ad hoc networks: an analytical study
Published 2012“…The results show that the used virtual clustering is very useful in improving scalability and outperforms other clustering schemes. …”
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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…The algorithm’s performance was compared with other variants of Ant-Miner and state-of-the-art rules-based classification algorithms based on classification accuracy and model complexity. …”
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Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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