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  1. 1

    Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

    Published 2014
    “…Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. …”
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    Thesis
  2. 2

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

    Published 2018
    “…In this research, swarming intelligence is used to solve optimisation problem. Grey Wolf Optimizer and Dragonfly Algorithm were chosen. …”
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    Monograph
  3. 3

    Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization by Nur Iffah, Mohamed Azmi, Kamal Arifin, Mat Piah, Wan Azhar, Wan Yusoff, F. R. M., Romlay

    Published 2017
    “…Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. …”
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    Conference or Workshop Item
  4. 4

    Optimization of power system stabilizers using participation factor and genetic algorithm by Hassan, L.H., Moghavvemi, M., Almurib, H.A.F., Muttaqi, K.M., Ganapathy, V.G.

    Published 2014
    “…This paper describes a method to determine the optimal location and the number of multi-machine power system stabilizers (PSSs) using participation factor (PF) and genetic algorithm (GA). …”
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    Article
  5. 5

    Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength by Hussain Talpur, Kashif

    Published 2015
    “…Many researchers have trained ANFIS parameters using metaheuristic algorithms but very few have considered optimizing the ANFIS rule-base. …”
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    Thesis
  6. 6

    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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    Thesis
  7. 7

    PID-Ant Colony Optimization (ACO) control for electric power assist steering system for electric vehicle by Abu Hanifah, Rabiatuladawiyah, Toha, Siti Fauziah, Ahmad, Salmiah

    Published 2013
    “…The fast tuning feature of ACO algorithm is the factor that distinguish this hybrid method as compared to conventional trial and error method PID controller tuning. …”
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    Proceeding Paper
  8. 8

    Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization by Lee, Jesee Kar Ming

    Published 2022
    “…The ANN model is further improved using GA and PSO. Each algorithm has its own parameters and is further optimized using RSM. …”
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    Thesis
  9. 9

    A modified technique in RFID networking planning and optimization by Nawawi, Azli

    Published 2015
    “…In this research, PSO algorithm was used in the optimization process as it was considered as a very useful, efficient and well known algorithm. …”
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    Thesis
  10. 10

    Power generation allocation in smart grid using Dwarf Mongoose Optimization / Mohamad Irfan Shamani by Shamani, Mohamad Irfan

    Published 2025
    “…A real-word problem where DMO could be used is optimization energy allocation within power generation system. …”
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    Thesis
  11. 11

    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

    Published 2017
    “…Typically, parameter estimation is performed using various types of Least Squares (LS) algorithms due to its stable and efficient numerical computation. …”
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    Thesis
  12. 12

    Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

    Published 2010
    “…Also the WLS algorithm is modified to include Unified Power Flow Controller (UPFC) parameters. …”
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    Thesis
  13. 13

    Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor by Nur Naajihah, Ab Rahman

    Published 2024
    “…The swarm intelligence group selected Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Modified Adaptive Bats Sonar Algorithms (MABSA) to optimize the parameters of the PI-PD controller. …”
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    Thesis
  14. 14
  15. 15

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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    Thesis
  16. 16

    Evolutionary tuning of modular fuzzy controller for two-wheeled wheelchair by Ahmad, Salmiah, Siddique, Nazmul H., Tokhi, Mohammad Osman

    Published 2012
    “…Due to its signficant advantages over other searching methods, a genetic algorithm approach is used to optimize the scaling factors of the MFC and results show that the optimized parameters give better system performance for such a complex, highly nonlinear two-wheeled wheelchair system.…”
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    Article
  17. 17

    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

    Published 2017
    “…The proposed algorithms have been examined and validated using the IEEE 30-bus and IEEE 118-bus test systems. …”
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    Thesis
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  19. 19

    Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

    Published 2023
    “…Algorithms; Evolutionary algorithms; Mean square error; Optimization; Parameter estimation; Photovoltaic cells; Coefficient of determination; DEAM; Five parameters; Hybrid differential evolution; Improved differential evolutions; IV characteristics; Photovoltaic modules; Root mean square errors; Iterative methods; algorithm; artificial intelligence; electromagnetic method; error analysis; experimental study; photovoltaic system…”
    Article
  20. 20

    Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models by Gholami M., Ghanbari-Adivi E., Ehteram M., Singh V.P., Najah Ahmed A., Mosavi A., El-Shafie A.

    Published 2024
    “…This study proposes ensemble models for predicting LDC based on multilayer perceptron (MULP) methods and optimization algorithms. The honey badger optimization algorithm (HBOA), salp swarm algorithm (SASA), firefly algorithm (FIFA), and particle swarm optimization algorithm (PASOA) are used to adjust the MULP parameters. …”
    Article