Search Results - (( parallel optimization bees algorithm ) OR ( parameter mitigation clustering algorithm ))
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Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
Published 2012“…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
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Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm
Published 2024“…Through an extensive computational experiment involving a well-known benchmark suite, the ABC algorithm demonstrated remarkable performance, consistently outperforming several popular metaheuristic algorithms, including Genetic Algorithms, Particle Swarm Optimization, Memetic Algorithms, and Whale Optimization Algorithm in 75% of the problems. …”
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Enhancement Of Clustering Algorithm Using 3D Euclidean Distance To Improve Network Connectivity In Wireless Sensor Networks For Correlated Node Behaviours
Published 2024“…Thus, this research proposes enhancement on clustering algorithm to mitigate the impact of correlated node behaviour on network performances. …”
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Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib
Published 2019“…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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A coalition model for efficient indexing in wireless sensor network with random mobility / Hazem Jihad Ali Badarneh
Published 2021“…The proposed framework aims to improve the indexing packets and mitigate the disseminated data. Static-Coalition algorithm rearranges the packets in each gateway, by source (location attribute). …”
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Detection And Identification Of Stiction In Control Valves Based On Fuzzy Clustering Method
Published 2016“…This modification prevents the fuzzy clustering algorithm from turning into numerical problem. …”
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Model-based hybrid variational level set method applied to object detection in grey scale images
Published 2024“…To tackle the persistent challenge of segmenting grayscale images with both uneven characteristics and high noise levels, a hybrid level-set algorithm based on kernel metrics is introduced. This algorithm leverages an improved multi-scale mean filter to mitigate grayscale inhomogeneity while reducing the impact of scale parameter selection. …”
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