Search Results - (( parallel optimization bees algorithm ) OR ( parallel distribution issues algorithm ))*

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  1. 1

    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function by Hammash, Nayif Mohammed

    Published 2012
    “…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
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    Thesis
  2. 2

    Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm by Mohd Abdul Hadi, Osman, Mohd Fadzil Faisae, Ab Rashid, Nik Mohd Zuki, Nik Mohamed, Muhammad Ammar, Nik Mu’tasim

    Published 2024
    “…Through an extensive computational experiment involving a well-known benchmark suite, the ABC algorithm demonstrated remarkable performance, consistently outperforming several popular metaheuristic algorithms, including Genetic Algorithms, Particle Swarm Optimization, Memetic Algorithms, and Whale Optimization Algorithm in 75% of the problems. …”
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  3. 3

    Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

    Published 2023
    “…This work is focused on the implementation of evolutionary based computer algorithms, genetic algorithms (GAs), on microcontrollers. …”
    Conference paper
  4. 4

    The visualization of three dimensional brain tumors' growth on distributed parallel computer systems by Alias, Norma, Masseri, Mohd. Ikhwan Safa, Islam, Md. Rajibul, Khalid, Siti Nurhidayah

    Published 2009
    “…The main objective of this study is to visualize the brain tumors’ growth in three-dimensional and implement the algorithm on distributed parallel computer systems. …”
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    Article
  5. 5

    Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib by Dian Najihah , Abu Talib

    Published 2019
    “…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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    Thesis
  6. 6

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…The first step lies at the modelling of parallel applications running on heterogeneous parallel computers. …”
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    Thesis
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    Regenerative braking strategy for electric vehicles using improved adaptive genetic algorithm by Taleghani, Hussein

    Published 2017
    “…One uses Standard Genetic Algorithm (SGA), the second strategy uses Improved Adaptive Genetic Algorithm (IAGA). …”
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    Thesis
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    Conjunctions in biological neural architectures for visual pose estimation / Tom´As Maul by Tom´As, Maul

    Published 2006
    “…A highly parallel approach based on simple inter-map conjunctions, or correspondence distributions, is chosen and tested on synthetic and real patterns. …”
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    Thesis
  12. 12

    An adaptive controller of hydro generators for smart grid application in Malaysia by Mohamad, H., Bakar, A.H.A., Ping, H.W., Mokhlis, Hazlie

    Published 2010
    “…The controller has been modeled considering the existing Malaysia' distribution network of mini hydro power plant connected in parallel to the grid. …”
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    3d Morphing And Shape Transformation Using Slices by Yasmin, Shamima

    Published 2009
    “…This thesis addresses the above-mentioned issues by proposing a novel 3D morphing algorithm using slices. …”
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    Thesis
  16. 16

    Critical insight for MAPReduce optimization in Hadoop by Khan, Burhan ul Islam, Olanrewaju, Rashidah Funke, Altaf, Hunain, Shah, Asadullah

    Published 2014
    “…Achieving an optimal approach for higher performance in terms of efficient load balancing, load distribution, optimum resource utilization, minimum overheads and least possible delay has been the vital issue for cloud infrastructure. …”
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    Article
  17. 17

    Random sampling method of large-scale graph data classification by Rashed Mustafa, Mohammad Sultan Mahmud, Mahir Shadid

    Published 2024
    “…After that, we randomly select a subset of data blocks, each being a random sample of the graph dataset, and compute the different graph property distributions. Since the data blocks in this model are much smaller than the entire data set, it is more efficient to analyze them on a standalone small machine, and multiple data blocks can be analyzed on multiple nodes of the cluster in parallel. …”
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