Search Results - (( using optimization sensor algorithm ) OR ( using computing bee algorithm ))*
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Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm
Published 2021“…In this work, these parameters are optimized using dynamic inertia weight artificial bees colony (DIW-ABC) optimization algorithm. …”
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Acoustic emission partial discharge localization in oil based on artificial bee colony
Published 2025“…Comparisons with the genetic algorithm (GA), particle swarm optimization (PSO) and bat algorithm (BA) revealed that the distance error, maximum deviation and computation time for AE PD localization based on ABC are the lowest. …”
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Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches
Published 2015“…The research also analyzes the performance of the ABC algorithm using three different onlooker bee approaches. …”
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Application of the bees algorithm to the selection features for manufacturing data
Published 2007“…A “wrapper” feature selection method using the Bees Algorithm and Multilayer Perception (MLP) networks is described in this paper. …”
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Autonomous object movement in modeling bees foraging
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Global gbest guided-artificial bee colony algorithm for numerical function optimization
Published 2018“…Numerous computational algorithms are used to obtain a high performance in solving mathematics, engineering and statistical complexities. …”
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Using the bees algorithm to optimise a support vector machine for wood defect classification
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Protein Conformantional Search Using Bees Algorithm
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Honey bee based trust management system for cloud computing
Published 2011“…In this paper, the authors propose the concept that honey bee algorithm which has been developed to solve complex optimization problems can be successfully used to address this issue.The authors have taken a closer look at the optimization problems that had been solved using the honey bee algorithm and the similarity between these problems and the cloud computing environment.Thus concluding that the honey bee algorithm could be successfully used to solve the trust management issue in cloud computing.…”
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Data clustering using the bees algorithm
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An improved bees algorithm local search mechanism for numerical dataset
Published 2015“…Bees Algorithm (BA), a heuristic optimization procedure, represents one of the fundamental search techniques is based on the food foraging activities of bees. …”
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Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification
Published 2017“…Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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Optimization grid scheduling with priority base and bees algorithm
Published 2014“…The main aim of this current research to propose an optimization of the initial scheduler for grid computing using the bees algorithm. Modern algorithms informed this research. …”
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Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification
Published 2017“…By optimizing the training of the neural networks using optimal weight set, better results can be obtained by the neural networks.Traditional neural networks algorithms such as Back Propagation (BP) were used for ANNT, but they have some drawbacks such as computational complexity and getting trapped in the local minima.Therefore, evolutionary algorithms like the Swarm Intelligence (SI) algorithms have been employed in ANNT to overcome such issues.Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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Task scheduling in cloud computing environment using hybrid genetic algorithm and artificial bee colony
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A near-optimal centroids initialization in K-means algorithm using bees algorithm
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Multi objective bee colony optimization framework for grid job scheduling
Published 2013“…Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.Job scheduling problem is one of the key issues because of high heterogeneous and dynamic nature of resources and applications in the grid computing environment.Bee colony approach has been used to solve this problem because it can be easily adapted to the grid scheduling environment.The bee algorithms have shown encouraging results in terms of time and co st.In this paper a framework for multi objective bee colony optimization is proposed to schedule batch jobs to available resources where the number of jobs is greater than the number of resources.Pareto analysis and k-means analysis are integrated in the bee colony optimization algorithm to facilitate the scheduling of jobs to resources.…”
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