Search Results - ((((linear algorithm) OR (means algorithm))) OR (bees algorithm))
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Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
Published 2012“…This means that it spends a long time for the bees algorithm converge the optimum solution. …”
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Data clustering using the bees algorithm
Published 2007“…This paper proposes a clustering method that integrates the simplicity of the k-means algorithm with the capability of the Bees Algorithm to avoid local optima. …”
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A near-optimal centroids initialization in K-means algorithm using bees algorithm
Published 2009“…The K-mean algorithm is one of the popular clustering techniques.The algorithm requires user to state and initialize centroid values of each group in advance. …”
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Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems
Published 2021“…This study seeks to solve this problem using Artificial Bee Colony (ABC) Algorithm along with the proposed Discrete Nearest Neighborhood Algorithm (DNNA). …”
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An improved artificial bee colony algorithm based on mean best-guided approach for continuous optimization problems and real brain MRI images segmentation
Published 2024Subjects: “…Optimization algorithms…”
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Power-efficient wireless coverage using minimum number of uavs
Published 2023“…Antennas; Disasters; Genetic algorithms; Iterative methods; K-means clustering; Particle swarm optimization (PSO); 3-D placements; Artificial bee colony; Efficient 3d placement; Genetic algorithm; K-means; Particle swarm optimization; Placement algorithm; Power efficient; Unmanned aerial vehicle; Wireless coverage; Unmanned aerial vehicles (UAV); algorithm; animal; bee; Algorithms; Animals; Bees; Unmanned Aerial Devices…”
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Adaptive filtering of EEG/ERP through bounded range artificial Bee Colony (BR-ABC) algorithm
Published 2014“…ANCs are also implemented with Least Mean Square (LMS) and Recursive Least Square (RLS) algorithm. …”
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Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm
Published 2022“…Inertia weight artificial bee colony (IW-ABC) algorithms using linearly increasing, linearly decreasing, and exponentially increasing inertia are proposed here for the optimization of the indoor comfort index and energy usage. …”
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Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm
Published 2022“…Inertia weight artificial bee colony (IW-ABC) algorithms using linearly increasing, linearly decreasing, and exponentially increasing inertia are proposed here for the optimization of the indoor comfort index and energy usage. …”
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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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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction
Published 2014“…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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Hydroclimatic data prediction using a new ensemble group method of data handling coupled with artificial bee colony algorithm
Published 2022“…It is rare to find a hydrological application using the group method of data handling (GMDH) model, artificial bee colony (ABC) algorithm, and ensemble technique, precisely predicting ungauged sites. …”
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Widely linear dynamic quaternion valued least mean square algorithm for linear filtering
Published 2017“…The performance of the proposed algorithms are compared with quaternion least mean square QLMS, zero-attract quaternion least mean square ZA-QLMS, and widely linear quaternion least mean square WL-QLMS algorithms. …”
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Artificial Bee Colony Algorithm for Pairwise Test Generation
Published 2017“…In a case where PABC is not at its optimal stage or its best performance, the experiments of a test case are effectively competitive. PABC progresses as a means to achieve the effective use of the artificial bee colony algorithm for pairwise testing reduction.…”
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Group method of data handling with artificial bee colony in combining forecasts
Published 2018“…In this study, the use of Artificial Bee Colony (ABC) algorithm to combine several time series forecasts is presented. …”
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Grey Wolf Optimizer Based Battery Energy Storage System Sizing for Economic Operation of Microgrid
Published 2023“…Electric batteries; Energy management; Energy management systems; Genetic algorithms; Integer programming; Operating costs; Particle swarm optimization (PSO); Artificial bee colonies (ABC); Battery energy storage systems; battery sizing; Gravitational search algorithm (GSA); Grey Wolf Optimizer; Meta-heuristic optimization techniques; Micro grid; Mixed integer linear programming (MILP); Battery storage…”
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Modeling of widely-linear quaternion valued systems using hypercomplex algorithms
Published 2015“…The data-driven optimal modeling and identification of widely-linear quaternion-valued synthetic systems is achieved by using a quaternion-valued gradient based algorithms. …”
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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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An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2013“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. Still, BP-learning algorithm has difficulties such as trapping in local optima and slow convergence especially for solving non-linearly separable classification problems. …”
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