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  1. 1
    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
    “…Moreover, other than the memory-based feature, SED algorithm has fewer design parameters to be addressed and the independence of the gain sequence in the tuning process. …”
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  2. 2
    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
    “…Moreover, other than the memory-based feature, SED algorithm has fewer design parameters to be addressed and the independence of the gain sequence in the tuning process. …”
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  3. 3
    Data-driven neuroendocrine-pid tuning based on safe experimentation dynamics for control of TITO coupled tank system with stochastic input delay

    Data-driven neuroendocrine-pid tuning based on safe experimentation dynamics for control of TITO coupled tank system with stochastic input delay by Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Raja Mohd Taufika, Raja Ismail

    Published 2019
    “…The SED algorithm is an optimization method used as data-driven tools to find the optimal control parameters by using the input-output (I/O) data measurement in an actual system. …”
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  4. 4
    Clarity-optimized wavelet with autoencoder-ReliefF ranking for enhanced UHF PD signal feature extraction

    Clarity-optimized wavelet with autoencoder-ReliefF ranking for enhanced UHF PD signal feature extraction by Azam, Kayser M.K., Othman, Mohamadariff, Hossain, A K M Zakir, Kumar, Dhruba, Wong, Jee Keen Raymond, Illias, Hazlee Azil, Abdul Latef, Tarik, Mat Ibrahim, Masrullizam

    Published 2025
    “…To address the challenge of identifying the most discriminative features, this work integrates advanced feature ranking algorithms, namely, auto-encoder-based ranking and the ReliefF method. …”
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  5. 5
    Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design

    Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design by Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Mohd Zaidi, Mohd Tumari

    Published 2014
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  6. 6
    Optimization of turning parameters using genetic algorithm method

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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  7. 7
    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis

    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

    Published 2018
    “…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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  8. 8
    Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization

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

    Published 2014
    “…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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  9. 9
    Optimization of turning parameters using ant colony optimization

    Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

    Published 2008
    “…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
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  10. 10
    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail

    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

    Published 2014
    “…Trial and error often serves as the best method to determine the parameter. Therefore, a good optimization technique is required for identify the best parameter in minimizing the forecast errors. …”
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  11. 11
    Design of intelligent control system and its application on fabricated conveyor belt grain dryer

    Design of intelligent control system and its application on fabricated conveyor belt grain dryer by Lutfy, Omar F.

    Published 2011
    “…Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. …”
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  12. 12
    Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation

    Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation by Premkumar M., Ravichandran S., Hashim T.J.T., Sin T.C., Abbassi R.

    Published 2025
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  13. 13
    Application Of Genetic Algorithms For Robust Parameter Optimization

    Application Of Genetic Algorithms For Robust Parameter Optimization by Belavendram, N.

    Published 2010
    “…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
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  14. 14
    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP

    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

    Published 2021
    “…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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  15. 15
    Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization

    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
    “…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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  16. 16
    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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  17. 17
    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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  18. 18
    An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli

    An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli by Mohammed Adam, Kunna, Tuty Asmawaty, Abdul Kadir, Muhammad Akmal, Remli, Noorlin, Mohd Ali, Kohbalan, Moorthy, Noryanti, Muhammad

    Published 2020
    “…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
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  19. 19
    Optimization of Machining Parameters in Turning Operation Using PSO and AIS Algorithms: A Survey

    Optimization of Machining Parameters in Turning Operation Using PSO and AIS Algorithms: A Survey by Abbas, Adnan Jameel, Minhat, Mohamad, Abd Rahman, Md Nizam

    Published 2012
    “…Most papers in the field of turning parameters optimization are based on (PSO) algorithms, but only a few efforts that are using (AIS) algorithms. …”
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  20. 20
    Optimization of milling parameters using ant colony optimization

    Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

    Published 2008
    “…This method was demonstrated for the optimization of machining parameters for milling operation. …”
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