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  1. 1
    An improved particle swarm optimization (PSO) based MPPT for PV With reduced steady-state oscillation

    An improved particle swarm optimization (PSO) based MPPT for PV With reduced steady-state oscillation by Ishaque, K., Salam, Z., Amjad, M., Mekhilef, Saad

    Published 2012
    “…This paper proposes an improved maximum power point tracking (MPPT) method for the photovoltaic (PV) system using a modified particle swarm optimization (PSO) algorithm. …”
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  2. 2
    Online DE optimization for Fuzzy-PID controller of semi-active suspension system featuring MR damper

    Online DE optimization for Fuzzy-PID controller of semi-active suspension system featuring MR damper by Ahmed, Hesham, As’arry, Azizan, Hairuddin, Abdul Aziz, Hassan, Mohd Khair, Liu, Yunyun, Onwudinjo, Erasmus Cufe Ujunwa

    Published 2022
    “…In this paper, MR fluid damper with Fuzzy-PID controller is examined to be optimized using a modified DE algorithm. However, in the Fuzzy-PID controller, the fuzzy logic algorithm is used to auto-tune the PID controller, but it cannot be considered as a fully real-time controller since the fuzzy algorithm uses a previous knowledge base built offline. …”
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  3. 3
    Optimisation of automatic generation control performance in two-area power system with pid controllers using mepso / Lu Li

    Optimisation of automatic generation control performance in two-area power system with pid controllers using mepso / Lu Li by Lu , Li

    Published 2018
    “…The AGC in two-area power system was constructed and simulated by using MATLAB R2017b software. From the simulation results, it was found that with the same number of PID controllers, the performance of AGC optimised by using MEPSO-TVAC algorithm is better in terms of overshoot and fitness value than using EPSO and PSO algorithms. …”
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  4. 4
    Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm

    Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm by Ren Hao, Mok, Ahmad, Mohd Ashraf

    Published 2022
    “…Nevertheless, many existing optimization tools for tuning the FOPID controller, which are based on multi-agent based optimization, require large number of function evaluation in their algorithm that could lead to high computational burden. …”
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  5. 5
    PID CONTROLLER TUNING OF 3-PHASE SEPARATOR IN OIL & GAS INDUSTRY USING BACTERIA FORAGING OPTIMIZATION ALGORITHM

    PID CONTROLLER TUNING OF 3-PHASE SEPARATOR IN OIL & GAS INDUSTRY USING BACTERIA FORAGING OPTIMIZATION ALGORITHM by HO JOON , HENG

    Published 2012
    “…So, this paper will introduce Bacterial Foraging Optimization Algorithm (BFOA) in optimizing the parameters for PI control. …”
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  6. 6
    Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques

    Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

    Published 2018
    “…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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  7. 7
    A hybrid of ant colony optimization, genetic algorithm and flux balance analysis for optimization of succinic acid production in Escherichia coli

    A hybrid of ant colony optimization, genetic algorithm and flux balance analysis for optimization of succinic acid production in Escherichia coli by Tan, Jun Bin, Choon, Yee Wen, Moorthy, Kohbalan, Hasyiya Karimah, Adli, Muhammad Akmal, Remli, Mohd Arfian, Ismail, Zuwairie, Ibrahim, Mohd Saberi, Mohamad

    Published 2023
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  8. 8
    SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique

    SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique by Doroody C., Tiong S.K., Darzi S.

    Published 2023
    Conference Paper
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  9. 9
    Optimization Method Using Modified Harmony Search For Coverage And Energy Efficiency In Wireless Sensor Network

    Optimization Method Using Modified Harmony Search For Coverage And Energy Efficiency In Wireless Sensor Network by Halim, Nurul Hamimi

    Published 2018
    “…Coverage and energy efficiency metrics are two fundamental issues for almost all types of application in wireless sensor network (WSNs).Coverage reflects how well an area is monitored by sensor nodes and in energy efficient networks where less energy is consumed to provide the same level of services.These twin specifics are presented to evaluate the performance of a wireless sensor network.Due to its simplicity and ease of analysis,full coverage is widely implemented in many theoretical studies.However,sometimes full coverage is not the best way to represent some real-world application due to its strong restrictions and its deterministic characteristics.In this thesis,Modified Harmony Search algorithm (MHS) is proposed to achieve a sensor node deployment such that the covered area is optimal and data transfer has low energy consumption.Through computer simulations, experimental results verified that the proposed method improved the coverage of area in compare to some related methods.Based on the result obtain from every experiments,coverage area percentage performance is affected by the number of hotspots.This is shown by Harmony Search (HS) based method where the coverage area percentage increases as the number of hotspot increase. …”
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  10. 10
    Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy

    Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

    Published 2024
    “…The realization of this objective is steered by two distinct methodologies: the Method for Pure Multi-Objective Optimal Control (PMM) and the Hybrid Method (HM). …”
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  11. 11
    Intelligent Optimization Techniques for Optimal Power Flow using Interline Power Flow Controller

    Intelligent Optimization Techniques for Optimal Power Flow using Interline Power Flow Controller by Mohamed, Mohamed, K.H, Kondapalli, Rama Rao. K. S.

    Published 2010
    “…The optimal control parameters are derived to minimize the transmission line losses employing three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm and Simulated Annealing. …”
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  12. 12
    Solving the optimal power flow problems using the superiority of feasible solutions-moth flame optimizer

    Solving the optimal power flow problems using the superiority of feasible solutions-moth flame optimizer by Alam, Mohammad Khurshed

    Published 2024
    “…The main goal of this study is to use a cuttingedge version of recent metaheuristic algorithm, namely Moth-Flame Optimizer (MFO) algorithm for solving the mentioned OPF problems. …”
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  13. 13
    A green clustering protocol for mobile sensor network using particle swarm optimization

    A green clustering protocol for mobile sensor network using particle swarm optimization by Latiff, N.M.A., NikAbdMalik, N., Latiff, A.H.A.

    Published 2016
    “…In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. We define a new fitness function that can optimize the energy consumption of the whole network and minimize the relative distance between cluster heads and their respective member nodes. …”
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  14. 14
    A green clustering protocol for mobile sensor network using particle swarm optimization

    A green clustering protocol for mobile sensor network using particle swarm optimization by Latiff, N.M.A., NikAbdMalik, N., Latiff, A.H.A.

    Published 2016
    “…In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. We define a new fitness function that can optimize the energy consumption of the whole network and minimize the relative distance between cluster heads and their respective member nodes. …”
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  15. 15
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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  16. 16
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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  17. 17
    Use of AR Block Processing for Estimating the State Variables of Power System

    Use of AR Block Processing for Estimating the State Variables of Power System by Mohd Nor, Nursyarizal, Jegatheesan, Ramiah, Perumal, Nallagownden

    Published 2008
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  18. 18
    Cut-off solar charge controller as an alternative towards system efficiency optimization

    Cut-off solar charge controller as an alternative towards system efficiency optimization by Sabry, Ahmad H., Almassri, Ahmed M., Wan Hasan, Wan Zuha, Mohd Radzi, Mohd Amran, Ab Kadir, Mohd Zainal Abidin, Shafie, Suhaidi

    Published 2014
    “…A Simulink Matlab simulator is attempted in the simulation phase of this research. …”
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  19. 19
    A Subspace Approach for Extracting Signals Highly Corrupted by Colored Noise

    A Subspace Approach for Extracting Signals Highly Corrupted by Colored Noise by Yusoff, Mohd Zuki, Hussin, Fawnizu Azmadi

    Published 2010
    “…SNR values can be as low as -10 dB in real clinical environments. The simulation results produced by the post-modified SSA2 algorithm, show a higher degree of consistencies in detecting the VEP's P100, P200, and P300 peaks, in comparisons to the pre-modified SSA1 method. …”
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  20. 20
    Information Theoretic-based Feature Selection for Machine Learning

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…In these extended IFS method, feature selection method was defined and presented as a 0-1 Knapsack Problem (MKP). …”
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