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  1. 1
    Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduction.

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

    Published 2023
    “…Having those said, this study proposes BESS optimisation to reduce the total system losses using modified Whale Optimisation Algorithm (WOA) with high exploration and exploitation features. …”
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  2. 2
    Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment

    Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment by M. F., Masrom, N. M. A., Ghani, M. O., Tokhi

    Published 2021
    “…This paper presents investigations into the development of an interval type-2 fuzzy logic control (IT2FLC) mechanism integrated with particle swarm optimization and spiral dynamic algorithm. The particle swarm optimization and spiral dynamic algorithm are used for enhanced performance of the IT2FLC by finding optimised values for input and output controller gains and parameter values of IT2FLC membership function as comparison purpose in order to identify better solution for the system. …”
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  3. 3
    Adaptive Spiral Dynamics Metaheuristic Algorithm for Global Optimisation with Application to Modelling of a Flexible System

    Adaptive Spiral Dynamics Metaheuristic Algorithm for Global Optimisation with Application to Modelling of a Flexible System by Ahmad Nor Kasruddin, Nasir, Raja Mohd Taufika, Raja Ismail, Tokhi, M. O.

    Published 2016
    “…This paper presents a nature-inspired metaheuristic algorithm namely linear adaptive spiral dynamics algorithm (LASDA) and its application to modelling of a flexible system. …”
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  4. 4
    Optimising cloud computing performance with an enhanced dynamic load balancing algorithm for superior task allocation

    Optimising cloud computing performance with an enhanced dynamic load balancing algorithm for superior task allocation by Zhanuzak, Raiymbek, Ala'anzy, Mohammed Alaa, Othman, Mohamed, Algarni, Abdulmohsen

    Published 2024
    “…Unlike benchmark algorithms that rely on static VM selection or post-hoc relocation of cloudlets, the EDLB algorithm dynamically identifies optimal cloudlet placement in real-time. …”
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  5. 5
    Optimisation of distributed generation in electric power systems using fuzzy-genetic algorithm approach

    Optimisation of distributed generation in electric power systems using fuzzy-genetic algorithm approach by Akorede, Mudathir Funsho

    Published 2011
    “…In the study, a 15-bus test system is employed and modelled in detail using Power System Analysis Toolbox (PSAT). …”
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  6. 6
    Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation

    Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation by Toha, Siti Fauziah, Abd Latiff, I., Mohamad, M., Tokhi, M Osman

    Published 2009
    “…The proposed method formulates a modified inertia weight algorithm by using a dynamic spread factor (SF). The inertia weight plays an important role in terms of balancing both the global and local search. …”
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  7. 7
    Gait identification and optimisation for amphi-underwater robot by using ant colony algorithm

    Gait identification and optimisation for amphi-underwater robot by using ant colony algorithm by Mohd Yusof, Muhammad Syafiq, Toha @ Tohara, Siti Fauziah

    Published 2019
    “…The algorithm being compared, between Ant Colony Algorithm (ACO) and the Particle Swarm Optimisation (PSO) in terms of time and distance. …”
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  8. 8
    Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function

    Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function by Tan, Min Keng

    Published 2019
    “…This study aims to explore the potential of implementing multi-agent-based Genetic Algorithm (GA) with interactive metamodel to acquire regular optimisation on dynamic characteristic of traffic flow. …”
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  9. 9
    Position tracking of DC motor with PID controller utilising particle swarm optimisation algorithm with levy flight and doppler effect

    Position tracking of DC motor with PID controller utilising particle swarm optimisation algorithm with levy flight and doppler effect by Nur Iffah, Mohamed Azmi, Nafrizuan, Mat Yahya

    Published 2025
    “…This paper presents the implementation of the PSO-LFDE (Particle Swarm Optimization with Lévy Flight Doppler Effect) algorithm for optimizing PID controller parameters in a DC motor system. …”
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  10. 10
    A comparative evaluation of PID-based optimisation controller algorithms for DC motor

    A comparative evaluation of PID-based optimisation controller algorithms for DC motor by Ahamed S.R., Parumasivam P., Hossain Lipu M.S., Hannan M.A., Ker P.J.

    Published 2023
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  11. 11
    PID-based control of a single-link flexible manipulator in vertical motion with genetic optimisation

    PID-based control of a single-link flexible manipulator in vertical motion with genetic optimisation by Md Zain, Badrul Aisham, Tokhi, M. Osman, Toha, Siti Fauziah

    Published 2009
    “…GA optimization is used to optimize the parameters of the proportional-integral-derivative (PID) based controllers for control of rigid-body and flexible motion dynamics of the system. …”
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  12. 12
    Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system

    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
    “…The PSO algorithm is used to optimize the loop-shaping step (subject to QFT constraints), which is performed manually in the standard QFT control design. …”
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  13. 13
    Novel Adaptive Bacterial Foraging Algorithms for Global Optimisation with Application to Modelling of a TRS

    Novel Adaptive Bacterial Foraging Algorithms for Global Optimisation with Application to Modelling of a TRS by Ahmad Nor Kasruddin, Nasir, Nor Maniha, Abd Ghani, Tokhi, M. O.

    Published 2015
    “…On the contrary, if a small step size is used, an optimal solution may be achieved, but at a very slow pace, thus affecting the speed of convergence. …”
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  14. 14
    Effective method for optimal allocation of distributed generation units in meshed electric power systems

    Effective method for optimal allocation of distributed generation units in meshed electric power systems by Akorede, Mudathir Funsho, Hizam, Hashim, Aris, Ishak, Ab Kadir, Mohd Zainal Abidin

    Published 2011
    “…These objective functions are fuzzified into a single multi-objective function, and subsequently solved using genetic algorithm (GA). In the GA, a fuzzy controller is used to dynamically adjust the crossover and mutation rates to maintain the proper population diversity (PD) during GA's operation. …”
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  15. 15
    Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module

    Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module by Koh J.S.P., Aris I.B., Ramachandaramurthy V.K., Bashi S.M., Marhaban M.H.

    Published 2023
    “…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). …”
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  16. 16
    Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module

    Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module by Koh J.S.P., Aris I.B., Ramachandaramurthy V.K., Bashi S.M., Marhaban M.H.

    Published 2023
    “…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). …”
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  17. 17
    Efficient gear fault feature selection based on moth‑flame optimisation in discrete wavelet packet analysis domain

    Efficient gear fault feature selection based on moth‑flame optimisation in discrete wavelet packet analysis domain by Ong, Pauline, Tieh, Tony Hieng Cai, Lai, Kee Huong, Lee, Woon Kiow, Ismon, Maznan

    Published 2019
    “…For this purpose, this study used the intensification and diversification properties of the recently proposed moth-flame optimisation (MFO) algorithm and utilised the algorithm in the proposed feature selection scheme. …”
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  18. 18
    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…Hence, the algorithm must overcome the problem of dynamic updates in the internal parameters or counter the concept drift. …”
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  19. 19
    Optimisation and control of fed-batch yeast production using q-learning

    Optimisation and control of fed-batch yeast production using q-learning by Helen, Chuo Sin Ee

    Published 2013
    “…Q-learning (QL) is a heuristic approach suggested for the process dynamic handling to achieve the multiobjective optimisation. …”
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  20. 20
    Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module

    Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module by Koh, Johnny Siaw Paw, Aris, Ishak, Ramachandaramurthy, Vigna Kumaran, Bashi, Sinan Mahmod, Marhaban, Mohammad Hamiruce

    Published 2006
    “…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). …”
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