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  1. 1
    A modified crow search algorithm with niching technique for numerical optimization

    A modified crow search algorithm with niching technique for numerical optimization by Islam, J., Vasant, P.M., Negash, B.M., Watada, J.

    Published 2019
    “…Despite its easy implementation, crow search algorithm has weakness to find global optima and suffers from slow convergence rate in multi-modal optimization problems. …”
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  2. 2
    A modified crow search algorithm with niching technique for numerical optimization

    A modified crow search algorithm with niching technique for numerical optimization by Islam, J., Vasant, P.M., Negash, B.M., Watada, J.

    Published 2019
    “…Despite its easy implementation, crow search algorithm has weakness to find global optima and suffers from slow convergence rate in multi-modal optimization problems. …”
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  3. 3
    1D Multigrid Solver For Finite Element Method

    1D Multigrid Solver For Finite Element Method by Azhar, Mohamad Amiruddin

    Published 2022
    “…This available algorithm of the Multigrid solver with the Finite Element Method was modified and tested for its performance. …”
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  4. 4
    Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor

    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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  5. 5
    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
    “…Therefore, via implementation of optimisation method, the performance of AGC can be improved by varying the parameters of PID controller.…”
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  6. 6
    Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm

    Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm by Alhamdawee, Ehsan Mohsin Obaid

    Published 2016
    “…MPPT algorithms can be categorized into classical methods and artificial intelligence-based methods. …”
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  7. 7
    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
    “…However,the sink node position and size of data transmitted will not affect the performance of coverage area.This is because the coverage area value is fluctuated as the parameters value increases.Throughout the experiment conducted,sensor nodes deployed using Modified Harmony Search algorithm (MHS) gives better coverage area compared to other existing methods.The average coverage area percentage obtained by Modified Harmony Search is 63 %.The average coverage area percentage obtained by Modified Random is 48 % and the average coverage area percentage obtained by Harmony Search is 46 %.The highest coverage area recorded for Modified Harmony Search is 70 %.To enhance the energy efficiency,shortest path distance finder is added to each method.Throughout the research,Modified Harmony Search with shortest path distance finder gives optimum results.…”
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  8. 8
    Comparison performances between MABSA-PI controller and MABSA-PD controller for DC motor position system

    Comparison performances between MABSA-PI controller and MABSA-PD controller for DC motor position system by Mohamad Harith Hilmi, Fajaffri, Nafrizuan, Mat Yahya

    Published 2023
    “…The MATLAB controllers are developed using the Simulink toolbox, while the transfer function of a DC motor is obtained from its circuit. Modified adaptive bats sonar algorithm (MABSA) will be implemented in the PI controller and PD controller as the main algorithm. …”
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  9. 9
    Discrete-time system identification using genetic algorithm with single parent-based mating technique

    Discrete-time system identification using genetic algorithm with single parent-based mating technique by Zainuddin, Farah Ayiesya

    Published 2024
    “…This research focuses on improving Genetic Algorithms (GA) for SI, specifically addressing inefficiencies in common crossover operators that limit search space exploration and lead to premature convergence. …”
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  10. 10
    Image watermarking optimization algorithms in transform domains and feature regions

    Image watermarking optimization algorithms in transform domains and feature regions by Tao, Hai

    Published 2012
    “…Digital watermarking techniques have been explored considerably since its first appearance in the 1990s. The achieved tradeoffs from these techniques between imperceptibility and robustness are controversial.To solve this problem,this study proposes the application of artificial intelligent techniques into digital watermarking by using discrete wavelet transform (DWT) and singular value decomposition (SVD).To protect the copyright information of digital images,the original image is decomposed according to two-dimensional discrete wavelet transform.Subsequently the preprocessed watermark with an affined scrambling transform is embedded into the vertical subband (HLm) coefficients in wavelet domain without compromising the quality of the image.The scaling factors are trained with the assistance of Particle Swarm Optimization (PSO).A new algorithmic framework is used to forecast feasibility of hypothesized watermarked images.In addition,the novelty is to associate the Hybrid Particle Swarm Optimization (HPSO),instead of a single optimization,as a model with SVD.To embed and extract the watermark,the singular values of the blocked host image are modified according to the watermark and scaling factors. …”
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  11. 11
    A comprehensive analysis of surface electromyography for control of lower limb exoskeleton

    A comprehensive analysis of surface electromyography for control of lower limb exoskeleton by Abdelhakim, Deboucha

    Published 2016
    “…The results of the modified Butterworth filter showed good suppression of the crosstalk and brought the signal of interest into its baseline state. …”
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  12. 12
    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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  13. 13
    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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  14. 14
    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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  15. 15
    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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  16. 16
    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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  17. 17
    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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  18. 18
    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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  19. 19
    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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  20. 20
    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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