Search Results - (( parallel distribution issues algorithm ) OR ( parameter optimization mead algorithm ))

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    Single and Multiple variables control using Tree Physiology Optimization by Halim, A.H., Ismail, I.

    Published 2017
    “…In the proposed method, each shoot from each branch search for possible solution in parallel and the fitness is evaluated based on all best values found by branch search. The proposed algorithm is also compared with deterministic gradient-free algorithm: Nelder-Mead simplex (NMS) and another metaheuristic algorithm: Particle Swarm Optimization (PSO). …”
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    Article
  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
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    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

    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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    Modelling transmission dynamics of covid-19 during Pre-vaccination period in Malaysia: a predictive guiseird model using streamlit by Zulkarnain, Norsyahidah, Abdul Hadi, Muhammad Salihi, Mohammad, Nurul Farahain, Shogar, Ibrahim

    Published 2023
    “…The mathematical model is solved using Scipy odeint function, which uses Livermore Solver for Ordinary Differential Equations with an Automatic method switching (LSODA) algorithm. The time-varying coefficients of SEIRD model that best fit the real data of COVID-19 cases are obtained using the Nelder-Mead optimization algorithm. …”
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    Proceeding Paper
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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
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    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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    Conference or Workshop Item
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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
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    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
  16. 16

    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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    Article
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