Search Results - (( data solution bees algorithm ) OR ( java data optimization algorithm ))
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Data clustering using the bees algorithm
Published 2007“…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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Optimising a waste management system using the Artificial Bee Colony (ABC) algorithm
Published 2025“…Future work may focus on integrating real-time data, adjusting algorithm parameters and hybridizing ABC algorithm with other metaheuristics to further improve performance.…”
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Student Project -
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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 aim of this research is to determine the flow of the shipment based on volume and to determine the total cost based on the flow of shipment by using Artificial Bee Colony (ABC) algorithm. The ABC algorithm consists of four phases of initialisation, employed bees, onlooker bees and scout bees. …”
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Student Project -
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Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification
Published 2023“…In this paper, the filter method chi square and the Artificial Bee Colony) ABC algorithm were both used as FS methods . …”
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Undergraduates Project Papers -
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Hybrid artificial bee colony algorithm with branch and bound for two–sided assembly line balancing
Published 2018“…Recently, the artificial bee colony (ABC) algorithm was used in the solution process where it was considered as a very useful, effective and well-known algorithm. …”
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Thesis -
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Acoustic emission partial discharge localization in oil based on artificial bee colony
Published 2025“…The employed bees explored the bounded search space, and onlooker bees refined PD locations found by the employed bees through local search. …”
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Data Analysis using Particle Swarm Optimization Algorithm
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Final Year Project / Dissertation / Thesis -
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Angle Based Protein Tertiary Structure Prediction Using Bees Optimization Algorithm
Published 2010“…In this project, angles based control with Bees Optimization search algorithm were adopted to search with guidance the protein conformational space in order to find the optimum solution. …”
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Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification
Published 2015“…The proposed CSERN and CSBPERN algorithms are compared with artificial bee colony using BP algorithm and other hybrid variants algorithms. …”
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Methods of intrusion detection in information security incident detection: a comparative study
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A random search based effective algorithm for pairwise test data generation
Published 2011“…This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. …”
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Scalable approach for mining association rules from structured XML data
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EasyA: Easy and effective way to generate pairwise test data
Published 2013“…This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. …”
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Conference or Workshop Item -
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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