Search Results - (( its application system algorithm ) OR ( some application colony algorithm ))*
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Artificial Bee Colony Algorithm for Pairwise Test Generation
Published 2017“…In this paper, we evaluated and proposed a pairwise strategy named Pairwise Artificial Bee Colony algorithm (PABC). According to the benchmarking results, the PABC strategies outdo some existing strategies to generate a test case in many of the system configurations taken into consideration. …”
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Enhancing Solutions Of Capacity Vehicle Routing Problem Based On An Improvement Ant Colony System Algorithm
Published 2019“…Several authors over the last only some decades have recognized many types of research and used several algorithms with various methods to solve it. …”
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Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman
Published 2017“…In the future, the efficiency of the result will be improved based on technology growth with adding some application such as GPS and map of the house in mobile version.…”
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A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots
Published 2019“…According to [13], the two best-known swarm intelligence algorithms are Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO). …”
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A survey on improvement of Mahalanobis Taguchi system and its application
Published 2024Subjects:Article -
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Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem
Published 2008“…This research explored and developed new heuristics based on GA for solving VRPSD. New algorithms, journal papers and computerized system were also developed. …”
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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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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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Optimizing support vector machine parameters using continuous ant colony optimization
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