Search Results - (( wave optimisation based algorithm ) OR ( variable optimization bat algorithm ))

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  1. 1

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”
    Conference paper
  2. 2

    The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction by Marlan Z.M., Ramlie F., Jamaludin K.R., Harudin N.

    Published 2023
    “…This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”
    Article
  3. 3
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    A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer by Alsewari, Abdul Rahman Ahmed, Sinan, Q. Salih

    Published 2019
    “…The proposed and the benchmark algorithms are tested for large-scale optimization problems which are associated with high-dimensional variability. …”
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    Article
  5. 5

    Enhanced Taguchi�s T-method using angle modulated Bat algorithm for prediction by Marlan Z.M., Ramlie F., Jamaludin K.R., Harudin N.

    Published 2023
    “…In response to this issue, this paper proposed an angle modulated Bat algorithm to be integrated with the T-method in optimizing the prediction model. …”
    Article
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    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
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    Thesis
  8. 8

    Solving large-scale problems using multi-swarm particle swarm approach by Salih, Sinan Q., Alsewari, Abdulrahman A.

    Published 2018
    “…The proposed approach strived to scale up the application of the (PSO) algorithm towards solving large-scale optimization tasks of up to 1000 real-valued variables. …”
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    Article
  9. 9
  10. 10

    Optimized controllers for stabilizing the frequency changes in hybrid wind-photovoltaic-wave energy-based maritime microgrid systems by Peddakapu, K., Mohd Rusllim, Mohamed, Srinivasarao, P., Licari, J.

    Published 2024
    “…The AOA-based 2DOF-TIDN performance is compared to the following algorithms: genetic, Jaya, bat, grasshopper optimization, particle swarm optimization, and moth flame optimization. …”
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    Article
  11. 11

    A smart handover strategy for 5G mmWave dual connectivity networks by Abdullah, Nor Fadzilah, Gannapathy, Vigneswara Rao, Nordin, Rosdiadee, Abu-Samah, Asma

    Published 2023
    “…The developed algorithm underwent testing using a 5G mmWave statistical channel model that emulates a dynamic channel matrix, including fading and the Doppler effect. …”
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    Article
  12. 12

    Active intelligent control of vibration of flexible plate structures by Md Salleh, Salihatun

    Published 2011
    “…However, the non-model based AVC algorithms are faster than their model-based AVC counterparts.…”
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    Thesis
  13. 13

    Acoustic emission partial discharge localization in oil based on artificial bee colony by Lim, Zhi Yang, Azis, Norhafiz, Mohd Hashim, Ahmad Hafiz, Mohd Radzi, Mohd Amran, Norsahperi, Nor Mohd Haziq, Mohd Ariffin, Azrul

    Published 2025
    “…Comparisons with the genetic algorithm (GA), particle swarm optimization (PSO) and bat algorithm (BA) revealed that the distance error, maximum deviation and computation time for AE PD localization based on ABC are the lowest. …”
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  14. 14
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    Factors with retirement behaviour among retirees and pre-retirees identified with a machine learning method / Muhammad Aizat Zainal Alam by Muhammad Aizat , Zainal Alam

    Published 2023
    “…The Malaysian Ageing and Retirement Survey (MARS) Data Wave 1 is used for this study where the data was sampled via multiple-stage sampling framework where each region is stratified by urban and rural areas called enumeration blocks (EBs) which are proportionate to the population size of each region across 3,384 households. …”
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    Thesis