Search Results - (( storage optimization modified algorithm ) OR ( parameters variation method algorithm ))

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  1. 1

    New Quasi-Newton Equation And Method Via Higher Order Tensor Models by Gholilou, Fahimeh Biglari

    Published 2010
    “…The efficiency of the usual QN methods is improved by accelerating the performance of the algorithms without causing more storage demand. The presented equation allows the modification of several algorithms involving QN equations for practical optimization that possess superior convergence prop- erty. …”
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    Thesis
  2. 2

    Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct... by Wong Ling Ai

    Published 2023
    “…Besides, an optimization algorithm with high efficiency is important to ensure the attainment of optimal solutions, where the optimization algorithms like genetic algorithm and particle swarm optimization are known to have high possibility of being trapped in local optimal points. …”
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    Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system by Ali, Hazem I.

    Published 2010
    “…These algorithms are designed to achieve the robustness over a wide range of system parameters change and disturbances. …”
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    Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi by Seyed Mohsen , Mousavi

    Published 2018
    “…A Modified Particle Swarm Optimization (MPSO) algorithm, a Genetic Algorithm (GA), a modified fruit fly optimization algorithm (MFOA) and a simulated annealing (SA) algorithm were used to find the optimal solution. …”
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  7. 7

    The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification by Faizol, Bin Mohd Suria

    Published 2020
    “…Technically, BFOA has been applied as supplementary algorithm for optimizing weight, parameters for other classifier algorithms and selecting optimised features for other classifiers. …”
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  8. 8

    Voltage Variation Analysis By Using Gabor Transform by Abdullah, Abdul Rahim, Tee, Wei Hown, Yusoff, Mohd Rahimi

    Published 2019
    “…The parameters extracted can detect the voltage variation signals successfully. …”
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    Article
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    Model-based hybrid variational level set method applied to lung cancer detection by Jing, Wang, Liew, Siau-Chuin, Azian, Abd Aziz

    Published 2024
    “…This paper presents a novel model-based hybrid variational level set method (VLSM) tailored for lung cancer detection. …”
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    Article
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    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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  13. 13

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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    Thesis
  14. 14

    Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz by Abdul Aziz, Mohd Azri

    Published 2018
    “…However, the use of moment of inertia and other parameters of DC motor are mostly to complete the transfer function and no specific analysis was done on the effects of their variations to the control method. …”
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    A Hybrid Sparrow Search Optimized Fractional Virtual Inertia Control for Frequency Regulation of Multi-Microgrid System by Fadheel B.A., Wahab N.I.A., Manoharan P., Mahdi A.J., Radzi M.A.B.M., Soh A.B.C., Ridha H.M., Alsoud A.R., Veerasamy V., Irudayaraj A.X.R., Alemu B.D.

    Published 2025
    “…The hybrid sparrow search and mountain gazelle optimizer algorithm (SSAMGO) optimizes the parameters for the three-loop controller. …”
    Article
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    Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz by Abdul Aziz, Mohd Azri

    Published 2018
    “…However, the use of moment of inertia and other parameters of DC motor are mostly to complete the transfer function and no specific analysis was done on the effects of their variations to the control method. …”
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  18. 18

    A review: Use of evolutionary algorithm for optimisation of machining parameters by Zolpakar, N. A., Mohd Fuad, Yasak, Pathak, Sunil

    Published 2021
    “…Lately, evolutionary algorithm, statistical approaches such as genetic algorithm (GA), particle swarm optimisation (PSO), and cuckoo search algorithm (CSA) have been utilised in simultaneous optimisation of the parameters of the desired outputs and its great potential in optimising machining processes is recognisable.…”
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    Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm by Alhamdawee, Ehsan Mohsin Obaid

    Published 2016
    “…MPPT algorithms can be categorized into classical methods and artificial intelligence-based methods. …”
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    Development Of An Algorithm To Reduce The Topographical Effects In Reflected Radiance by Yeap, Eng Choo

    Published 2020
    “…Many researchers have tried to reduce the effect of topography in the past with success; however, most of these methods are complicated and require many parameters. …”
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