Search Results - ((research algorithm) OR (((bees algorithm) OR (based algorithm))))
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1
Formulation of metaheuristic algorithms based on artificial bee colony for engineering problems
Published 2024“…The Artificial Bee Colony (ABC) algorithm is a powerful metaheuristic optimization technique inspired by the honeybee foraging behaviour. …”
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Thesis -
2
Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC)
Published 2015“…In this paper, an algorithm to classify leaf disease severity based on lesions is presented. …”
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3
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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4
Application of Bee Colony Optimization (BCO) in NP-Hard Problems
Published 2011“…This report presents the first stage of an ongoing research which is the problem solving of highly complex tasks using Bee-Inspired algorithms. …”
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Final Year Project -
5
Minimizing the total cost of inventory by using artificial bee colony algorithm / Nurul Syakira Mohd Zin
Published 2022“…The algorithm characterised a swarm-based meta-heuristic algorithm comprised of three divisions of bee troops in the ABC model, namely employed, onlooker, and scout bees. …”
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Research Reports -
6
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. …”
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Adjusted 0-1 knapsack problem in cargo flow by using artificial bee colony algorithm / Nor Zuliiziati Md Jani
Published 2021“…The ABC algorithm consists of four phases of initialisation, employed bees, onlooker bees and scout bees. …”
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Student Project -
8
Performance Enhancement Of Artificial Bee Colony Optimization Algorithm
Published 2013“…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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9
Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…On the other hand, LM algorithms which are derivative based algorithms still face a risk of getting stuck in local minima. …”
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Sequence-based interaction testing implementation using Bees Algorithm
Published 2023Subjects: “…Bees Algorithm…”
Conference paper -
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Global gbest guided-artificial bee colony algorithm for numerical function optimization
Published 2018“…The modification, hybridization and improvement strategies made ABC more attractive to science and engineering researchers. The two well-known honeybees-based upgraded algorithms, Gbest Guided Artificial Bee Colony (GGABC) and Global Artificial Bee Colony Search (GABCS), use the foraging behavior of the global best and guided best honeybees for solving complex optimization tasks. …”
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Adjusted 0-1 knapsack problem in cargo flow by using artificial bee colony algorithm / Siti Hafawati Jamaluddin ... [et al.]
Published 2022“…ABC algorithm was derived from the bee colony which consists of four phases of initialisation, employed bees, onlooker bees and scout bees. …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification
Published 2016“…The performance of the proposed Bat-BP algorithm is then compared with Artificial Bee Colony using BPNN (ABC-BP), Artificial Bee Colony using Levenberg-Marquardt (ABC-LM) and BPNN algorithm. …”
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HABCSm: A Hamming Based t -way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation
Published 2021“…Consequently, a new meta-heuristic based t -way strategy called Hybrid Artificial Bee Colony (HABCSm) strategy, based on merging the advantages of the Artificial Bee Colony (ABC) algorithm with the advantages of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. …”
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HABCSm: A Hamming Based t -way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation
Published 2021“…Consequently, a new meta-heuristic based t -way strategy called Hybrid Artificial Bee Colony (HABCSm) strategy, based on merging the advantages of the Artificial Bee Colony (ABC) algorithm with the advantages of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. …”
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16
Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control
Published 2014“…This paper presents the implementation of multiobjective based optimization of Artificial Bee Colony (ABC) algorithm for Load Frequency Control (LFC) on a two area interconnected reheat thermal power system. …”
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Review of Multi-Objective Swarm Intelligence Optimization Algorithms
Published 2021“…The MOO approaches include scalarization, Pareto dominance, decomposition and indicator-based. In this paper, the status of MOO research and state-of-the-art MOSI algorithms namely, multi-objective particle swarm, artificial bee colony, firefly algorithm, bat algorithm, gravitational search algorithm, grey wolf optimizer, bacterial foraging and moth-flame optimization algorithms have been reviewed. …”
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Pairwise Test Suite Generation Based on Hybrid Artificial Bee Colony Algorithm
Published 2020“…Complementing to the earlier researches, this paper proposes a new pairwise test suite generation called Pairwise Hybrid Artificial Bee Colony (PhABC) strategy based on hybridize of an Artificial Bee Colony (ABC) algorithm with a Particle Swarm Optimization (PSO) algorithm. …”
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Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation
Published 2019“…This is called hybrid artificial bee colony (HABC) strategy, which is based on hybridize of an artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. …”
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An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons
Published 2020“…This study proposes a new binary classification model for intrusion detection, based on hybridization of Artificial Bee Colony algorithm (ABC) and Dragonfly algorithm (DA) for training an artificial neural network (ANN) in order to increase the classification accuracy rate for malicious and non-malicious traffic in networks. …”
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