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  1. 1
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…Its optimality has inspired the development of a metaheuristic algorithm called Heuristic Kalman Algorithm (HKA) in 2009. …”
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  2. 2
    A genetic algorithm based approach for economic dispatch in power system / Mohd Rozely Kalil

    A genetic algorithm based approach for economic dispatch in power system / Mohd Rozely Kalil by Kalil, Mohd Rozely

    Published 1998
    “…The Genetic Algorithm developed in the project was tested on two objective functions for optimizing the economic dispatch problem, which are the total generation cost and the incremental cost function. …”
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  3. 3
    Liquid slosh suppression by implementing data-driven fractional order pid controller based on marine predators algorithm

    Liquid slosh suppression by implementing data-driven fractional order pid controller based on marine predators algorithm by Mohd Tumari, Mohd Zaidi Mohd, Mustapha, Nik Mohd Zaitul Akmal, Ahmad, Mohd Ashraf, Saat, Shahrizal, Ghazali, Mohd Riduwan

    Published 2023
    “…The MPA is used as a data-driven tuning tool in finding the optimal FOPID controller parameters based on fitness function which consists of total norm of tracking error, total norm of slosh angle as well as total norm of control input. …”
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  4. 4
    Customised fitness function of evolutionary algorithm for optimization of car park space / Ahmad Syahir Ab. Aziz

    Customised fitness function of evolutionary algorithm for optimization of car park space / Ahmad Syahir Ab. Aziz by Ab. Aziz, Ahmad Syahir

    Published 2017
    “…Therefore, framework development methodology is used to make sure the system successful and can be developed according to the schedule. Genetic algorithm is chosen for the development of the prototype to prove that genetic algorithm is the best technique to implement for optimization. …”
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  5. 5
    Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index

    Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index by Verayiah R., Mohamed A., Shareef H., Abidin I.H.Z.

    Published 2023
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  6. 6
    Optimization of assembly line balancing with energy efficiency by using tiki-taka algorithm

    Optimization of assembly line balancing with energy efficiency by using tiki-taka algorithm by Ariff Nijay, Ramli

    Published 2023
    “…Then, the TTA is developed before undergoing functionality tests by benchmarking with Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA). …”
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  7. 7
    Liquid slosh suppression by implementing data-driven fractional order PID controller based on marine predators algorithm

    Liquid slosh suppression by implementing data-driven fractional order PID controller based on marine predators algorithm by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali, Nik Mohd Zaitul Akmal, Mustapha, Shahrizal, Saat

    Published 2023
    “…The MPA is used as a data-driven tuning tool in finding the optimal FOPID controller parameters based on fitness function which consists of total norm of tracking error, total norm of slosh angle as well as total norm of control input. …”
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  8. 8
    Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain

    Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain by Hussain, Muhamad Hatta

    Published 2020
    “…The objectives of the studies are to develop a new optimization technique termed as Modified Firefly Algorithm (MFA) for minimizing the relay operating time, to develop a Multi-Objective Modified Firefly Algorithm (MOMFA) for minimizing both the total relay operating time and relay coordination time and to develop an integrated optimal predictor termed as Modified Firefly Algorithm-Artificial Neural Network (MFA-ANN) for accurate prediction of relay operating time. …”
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  9. 9
    Joint optimization of resources allocation for quality of service aware next-generation heterogeneous cellular networks / Hayder Faeq Rasool Alhashimi

    Joint optimization of resources allocation for quality of service aware next-generation heterogeneous cellular networks / Hayder Faeq Rasool Alhashimi by Hayder Faeq Rasool , Alhashimi

    Published 2025
    “…First, a greedy-based user association algorithm is proposed to allocate multiple users to MBS or SBSs to maximize the total sum rate. …”
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  10. 10
    An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system

    An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Helmi, Suid, Mohd Riduwan, Ghazali, M Osman, Tokhi

    Published 2023
    “…Comparative findings alongside other existing metaheuristic-based algorithms confirmed excellence of the proposed method through its superior performance against the conventional MPA, particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame optimization (MFO), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), salp-swarm algorithm (SSA), slime mould algorithm (SMA), flow direction algorithm (FDA), and the formally published adaptive safe experimentation dynamics (ASED)-based methods.…”
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  11. 11
    Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm

    Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm by Mohd Riduwan, Ghazali

    Published 2020
    “…Therefore, this study proposed the adaptive safe experimentation dynamics (ASED) algorithm to improve the SED algorithm performance accuracy by minimizing its objective function in terms of mean, best, worst, and standard deviation analysis. …”
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  12. 12
    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Previously, SED algorithm has been applied in to control scheme of wind farm to optimize the total power production but has yet to be applied in PID tuning. …”
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  13. 13
    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Previously, SED algorithm has been applied in to control scheme of wind farm to optimize the total power production but has yet to be applied in PID tuning. …”
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  14. 14
    Network reconfiguration and control for loss reduction using genetic algorithm

    Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

    Published 2010
    “…The proposed solution to this problem is based on a general combinatorial optimization algorithm known as Genetic Algorithm, and the load flow equations in distribution network. …”
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  15. 15
    Data-driven fractional-order PID controller tuning for liquid slosh suppression using marine predators algorithm

    Data-driven fractional-order PID controller tuning for liquid slosh suppression using marine predators algorithm by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Helmi, Suid, Mohd Riduwan, Ghazali, Shahrizal, Saat

    Published 2023
    “…In response, this study introduces a data-driven fractional-order PID (FOPID) controller designed using the Marine Predators Algorithm (MPA) for suppressing liquid slosh. The MPA serves as a data-driven tuning tool to optimize the FOPID controller parameters based on a fitness function comprising the total norms of tracking error, slosh angle, and control input. …”
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  16. 16
    Comparative study of optimal power flow using evolutionary programming and immune evolutionary programming technique in power system / Mohd Khairil Izwan Md Daim

    Comparative study of optimal power flow using evolutionary programming and immune evolutionary programming technique in power system / Mohd Khairil Izwan Md Daim by Md Daim, Mohd Khairil Izwan

    Published 2006
    “…The developed algorithm was tested against on IEEE 26 bus test system.…”
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  17. 17
    Optimal step-function approximation of load duration curve using evolutionary programming (EP) / Eda Azuin Othman

    Optimal step-function approximation of load duration curve using evolutionary programming (EP) / Eda Azuin Othman by Othman, Eda Azuin

    Published 2014
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  18. 18
    Data transmission in wireless sensor network with greedy function and particle swarm optimization

    Data transmission in wireless sensor network with greedy function and particle swarm optimization by Hamzarul Alif Hamzah, Norah Tuah, Kit Guan Lim, Min Keng Tan, Lei Zhu, Kenneth Tze Kin Teo

    Published 2019
    “…As distances affect greatly on the energy consumption, Particle Swarm Optimization (PSO) is developed to replace greedy algorithm in PEGASIS to reduce the distances of data transmission. …”
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  19. 19
    Optimization of Digital Electronic Circuit Structure Design Using Genetic Algorithm

    Optimization of Digital Electronic Circuit Structure Design Using Genetic Algorithm by Chong, Kok Hen

    Published 2008
    “…The simulator called Optimal Digital Circuit Structure Designer (ODCSD) is also developed in this work. …”
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  20. 20
    Green network planning and operational power consumption optimization in LTE-A using artificial intelligence

    Green network planning and operational power consumption optimization in LTE-A using artificial intelligence by Al-Samawi, Aida Ismail Ahmed

    Published 2015
    “…The second stage of the developed algorithm optimizes the average number of relay station per base station and their distance from the respective base station to meet the capacity constraint of the network operator. …”
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