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Review of Multi-Objective Swarm Intelligence Optimization Algorithms
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Application of adaptive bats sonar algorithm to minimise car side impact design
Published 2017“…This project was focusing on the modification of bats sonar algorithm (BSA) and renamed to adaptive bats sonar algorithm (ABSA) due to some limitations of previous algorithm. …”
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Undergraduates Project Papers -
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Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm
Published 2022“…Three different optimization algorithms which are Bat Algorithm (BA), Bat Algorithm with Mutation (BAM) and Extended Bat Algorithm (EBA) are implemented to optimize the value of PID controller gain for wheel mobile robot. …”
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Book Chapter -
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Application of the bees algorithm to the selection features for manufacturing data
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Conference or Workshop Item -
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PID controller design for mobile robot using Bat Algorithm with Mutation (BAM)
Published 2019“…Here, an optimization algorithm called Bat Algorithm with Mutation (BAM) is proposed to optimize the value of PID controller gain for mobile robot. …”
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Conference or Workshop Item -
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Application of the Bees Algorithm to find optimal drill path sequence
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Proceeding Paper -
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Test Data Generation for Event Driven System Using Bees Algorithm
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Conference or Workshop Item -
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Optimization of drilling path using the bees algorithm
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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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Artificial Bee Colony Algorithm for Pairwise Test Generation
Published 2017“…PABC progresses as a means to achieve the effective use of the artificial bee colony algorithm for pairwise testing reduction.…”
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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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Article -
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Task scheduling in cloud computing environment using hybrid genetic algorithm and artificial bee colony
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Academic Exercise -
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Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman
Published 2017“…This project used Artificial Bee Colony Algorithms (ABC) by adapting the food foraging behaviour of bee in honey bee and find a suitable house for home buyer based on their requirement. …”
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Bee foraging behaviour techniques for grid scheduling problem
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.These resources are collected together to make a huge computing power.Job scheduling problem is one of the key issues in grid computing and failing to look into grid scheduling results in uncompleted view of the grid computing.Achieving optimized performance of grid system, and matching application requirements with available computing resources, are the objectives of grid job scheduling.Bee colony approaches are more adaptive to grid scheduling due to high heterogeneous and dynamic nature of resources and applications in grid.These algorithms have shown encouraging results in terms of time and cost.This paper presents some resent research activities inspired by bee foraging behavior for grid job scheduling especially ABC and BCO approaches.Different original studies related to this area are briefly described along with their comparisons against them and results.The review summary of their derived algorithms and research efforts is done.…”
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Benchmarking of Bat-inspired Interaction Testing Strategy
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