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  1. 1
    An implementation of brain emotional learning based intelligent controller for AVR system

    An implementation of brain emotional learning based intelligent controller for AVR system by Saat, Shahrizal, Ghazali, Mohd Riduwan, Ahmad, Mohd Ashraf, Mustapha, Nik Mohd Zaitul Akmal, Tumari, Mohd Zaidi Mohd

    Published 2023
    “…In this paper, an intelligent controller based on brain emotional learning called BELBIC is applied and optimized by Particle Swarm optimization algorithm. …”
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  2. 2
    Predictive Functional Control With Reduced-Order Observer Design Using Particle Swarm Optimization For Pneumatic System

    Predictive Functional Control With Reduced-Order Observer Design Using Particle Swarm Optimization For Pneumatic System by Abd Rahman, Azira

    Published 2020
    “…Development of PFC-ROO algorithm is considered as a new control strategy for Intelligent Pneumatic Actuator (IPA) system for position control. …”
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  3. 3
    Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm

    Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

    Published 2018
    “…However, the performance of system is expected to be different from different algorithm.…”
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  4. 4
    An implementation of brain emotional learning based intelligent Controller for AVR system

    An implementation of brain emotional learning based intelligent Controller for AVR system by Shahrizal, Saat, Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Nik Mohd Zaitul Akmal, Mustapha, Mohd Zaidi, Mohd Tumari

    Published 2023
    “…In this paper, an intelligent controller based on brain emotional learning called BELBIC is applied and optimized by Particle Swarm optimization algorithm. …”
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  5. 5
    Social Spider Optimization On Pid Controller

    Social Spider Optimization On Pid Controller by Yaacob, Noor Diyana

    Published 2017
    “…The response of the controller can be described in terms of the degree to which the system peak overshoot, Mp, steady-state error, ess, rise time, Tr and settling time, Ts. …”
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  6. 6
    Using artificial intelligence search in solving the camera placement problem

    Using artificial intelligence search in solving the camera placement problem by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P.

    Published 2022
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  7. 7
    Visualization of dengue incidences using expectation maximization (EM) algorithm

    Visualization of dengue incidences using expectation maximization (EM) algorithm by Mathur, N., Asirvadam, V.S., Dass, S.C., Gill, B.S.

    Published 2017
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  8. 8
    Time-Variant online Auto-Tuned PI controller using PSO algorithm for high accuracy dual active bridge DC-DC converter

    Time-Variant online Auto-Tuned PI controller using PSO algorithm for high accuracy dual active bridge DC-DC converter by Suliana, Ab Ghani, Hamdan, Daniyal, Norazila, Jaalam, Nur Huda, Ramlan, Norhafidzah, Mohd Saad

    Published 2022
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  9. 9
    Optimized Intelligent Controller for Energy Storage based Microgrid towards Sustainable Energy Future

    Optimized Intelligent Controller for Energy Storage based Microgrid towards Sustainable Energy Future by Abu S.M., Hannan M.A., Mansor M., Ker P.J., Yaw Long C.

    Published 2024
    “…This system relies on a single renewable energy source, a photovoltaic (PV) system that is integrated with the energy storage system (ESS) including hydrogen-based fuel cell, battery, and supercapacitor for effective power management. …”
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  10. 10
    Evaluation of intracerebral haemorrhages surface area using artificial intelligence in computed tomography

    Evaluation of intracerebral haemorrhages surface area using artificial intelligence in computed tomography by Huddin, Azzam Basseri, Huddin, Aqilah Baseri, Tharek, Anas, Wan Zaki, Wan Mimi Diyana, Muda, Ahmad Sobri

    Published 2022
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  11. 11
    Time-variant online auto-tuned pi controller using pso algorithm for high accuracy dual active bridge dc-dc converter

    Time-variant online auto-tuned pi controller using pso algorithm for high accuracy dual active bridge dc-dc converter by Suliana, Ab Ghani, Hamdan, Daniyal, Norazila, Jaalam, Nur Huda, Ramlan, Norhafidzah, Mohd Saad

    Published 2022
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  12. 12
    Optimal planning of energy storage system for hybrid power system considering multi correlated input stochastic variables

    Optimal planning of energy storage system for hybrid power system considering multi correlated input stochastic variables by ALAhmad A.K., Verayiah R., Ramasamy A., Marsadek M., Shareef H.

    Published 2025
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  13. 13
    Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning

    Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning by Ismail, Amelia Ritahani, Azhary, Muhammad Zulhazmi Rafiqi, Hitam, Nor Azizah

    Published 2025
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  14. 14
    Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation

    Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation by Kamal Z., Zamli, Ahmed, Bestoun S., Mahmoud, Thair, Afzal, Wasif

    Published 2018
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  15. 15
    Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration

    Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration by ALAhmad A.K., Verayiah R., Shareef H.

    Published 2025
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  16. 16
    Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid

    Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid by Abdul Hamid, Zulkiffli

    Published 2013
    “…At first, in producing a good optimization algorithm, a hybridization technique was proposed for adopting the finest features of two different algorithms; namely the Genetic Algorithm (GA) and continuous domain Ant Colony Optimization (ACOr). …”
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  17. 17
    DNA sequence design for direct-proportional length-based DNA computing: Particle swarm optimization vs population based ant colony optimization

    DNA sequence design for direct-proportional length-based DNA computing: Particle swarm optimization vs population based ant colony optimization by Zulkifli, Md. Yusof, Muhammad Arif, Abdul Rahim, Sophan Wahyudi, Nawawi, Kamal, Khalil, Zuwairie, Ibrahim

    Published 2012
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  18. 18
    Dual-loop single dimension fuzzy-based sliding mode control design for robust tracking of an underactuated quadrotor craft

    Dual-loop single dimension fuzzy-based sliding mode control design for robust tracking of an underactuated quadrotor craft by Abro, G.E.M., Bin Mohd Zulkifli, S.A., Asirvadam, V.S.

    Published 2022
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  19. 19
    Dual-loop single dimension fuzzy-based sliding mode control design for robust tracking of an underactuated quadrotor craft

    Dual-loop single dimension fuzzy-based sliding mode control design for robust tracking of an underactuated quadrotor craft by Abro, G.E.M., Bin Mohd Zulkifli, S.A., Asirvadam, V.S.

    Published 2022
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  20. 20
    Comparing deep learning CNN method with traditional MRI-based hippocampal segmentation and volumetry for early Alzheimer’s disease diagnosis across diverse populations

    Comparing deep learning CNN method with traditional MRI-based hippocampal segmentation and volumetry for early Alzheimer’s disease diagnosis across diverse populations by Ibrahim, Nur Shahidatul Nabila, Suppiah, Subapriya, Ibrahim, Buhari, Mohad Azmi, Nur Hafizah, Seriramulu, Vengkatha Priya, Mohamad, Mazlyfarina, Hanafi, Marsyita, Mohammad Sallehuddin, Hakimah, Omar Sharif, Nurallysha Najwa, Razali, Rizah Mazzuin, Harrun, Noor Harzana

    Published 2025
    “…Traditional voxel-based morphometry (VBM) used for measuring hippocampal volume can be time-laborious and sensitive to pre-processing errors, thus CNN-based algorithms can minimize the time and reduce human errors. …”
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