Search Results - (( parallel optimization strategy algorithm ) OR ( rate optimization method algorithm ))

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    A Parallel new high order iterative algorithm on shared memory multiprocessors parallel computer by Mohamed Othman, Abdul Rahman Abdullah

    Published 2004
    “…In this paper, the parallel implementation of the algorithm with optimal strategy on shared memory multiprocessors (SMP) was presented and discussed. …”
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    Article
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    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
    “…Parallel processing is implemented together with the proposed strategy to minimize the program running time. …”
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    Thesis
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    Tree Physiology Optimization tuning rule for Proportional-Integral control by Halim, A.H., Ismail, I.

    Published 2017
    “…This paper presents a tuning correlation for Proportional-Integral (PI) controller parameters using Tree Physiology Optimization algorithm (TPO). TPO is a metaheuristic algorithm that has parallel search strategy inspired from plant growth system. …”
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    Article
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    Development of a real-time clutch transition strategy for a parallel hybrid electric vehicle by Vu, Trieu Minh

    Published 2011
    “…The present paper develops a real-time clutch transition strategy for a parallel hybrid electric vehicle (HEV) in order to achieve quick and smooth clutch transition engagements between pure electrical driving and hybrid driving. …”
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    Citation Index Journal
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    Parallel CFD Simulations of Multiphase Systems: Jet into a Cylindrical Bath and Rotary Drum on a Rectangular Bath. by Hasan, Nurul

    Published 2001
    “…In short, this research is intended to establish a strategic procedure to optimize a parallel version of a CFD package, FLUENT. …”
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    Article
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    Single and Multiple variables control using Tree Physiology Optimization by Halim, A.H., Ismail, I.

    Published 2017
    “…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
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    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…The HFPSO technique hybridizes the Firefly Optimization (FFO) algorithm and the Particle Swarm Optimization (PSO) method to improve the exploitation and exploration strategies and enhance the convergence rate. …”
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    Thesis
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    A study of the high-performance computing parallelism in solving complexity of meteorology data and calculations by Noor Affendi, Mohd Ridhuan, Hussin, Masnida, Hasan, Dana

    Published 2024
    “…Our investigation elaborates on, identifies, and analyzes the features and characteristics of parallel computing that are utilized in it. The paper also focuses on examining parallelization modeling, the algorithms involved, and optimization strategies employed in HPC-enabled meteorological simulations. …”
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    Article
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    Machining optimization using Firefly Algorithm / Farhan Md Jasni by Md Jasni, Farhan

    Published 2020
    “…For this project, we will verify the Firefly Algorithm (FA) into finding total profit rate by optimizing the machining parameter of milling operation and compare the effectiveness of FA with other non¬conventional method. …”
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    Student Project
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    Optimization of cnc turning parameters for minimizing temperature rise in aluminum using a genetic algorithm by Mimi Muzlina, Mukri

    Published 2024
    “…The genetic algorithm is used in this optimization because it is capable of searching for global optimal solutions since the configuration of the method can be very flexible, allowing it to be used for a variety of problems. …”
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    Thesis
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    Optimization of mycelium growth using genetic algorithm for multi-objective functions by Muhamad Faiz, Abu Bakar

    Published 2019
    “…Through the implementation of selected multi-objective genetic algorithm, NSGA-ii was able to produce pareto front for optimizing both nitrogen concentration and the extension rate of the mycelium. …”
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    Undergraduates Project Papers
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    Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates by Yeong, Lin Koay, Hong, Seng Sim, Yong, Kheng Goh, Sing, Yee Chua, Wah, June Leong

    Published 2024
    “…The process of training neural networks heavily involves solving optimization problems. Most optimization algorithms use a !…”
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    Conference or Workshop Item
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    Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

    Published 2008
    “…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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    Undergraduates Project Papers
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    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

    Published 2018
    “…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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    Conference or Workshop Item
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    GENETIC ALGORITHM OPTIMIZED PACKET FILTERING by NURIKA, OKTA

    Published 2013
    “…n our research, we present a method to optimize packet filtering by genetic algorithm. …”
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    Thesis
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    Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing by Elrasheed Ismail, Sultan

    Published 2013
    “…Load balancing optimization techniques such as Ant Colony Optimization (ACO), First Come First Served (FCFS), Round Robin (RR) and Particle Swarm Optimization (PSO) are popular techniques being used for scheduling and load balancing. …”
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    Thesis
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    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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    Article