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  1. 1
    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems

    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

    Published 2020
    “…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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  2. 2
    Modelling of multi-robot system for search and rescue

    Modelling of multi-robot system for search and rescue by Poy, Yi Ler

    Published 2023
    “…In this project, this sensor-based algorithm is known as the Obstacle Avoidance Algorithm. …”
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  3. 3
    Parameter identification of solar cells using improved Archimedes Optimization Algorithm

    Parameter identification of solar cells using improved Archimedes Optimization Algorithm by Krishnan, Harvin, Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

    Published 2023
    “…The parameters of solar cells for five PV models are identified using an Improved Archimedes Optimization Algorithm (IAOA) in this paper. …”
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  4. 4
    A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique

    A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique by Nur Aisyah Syafinaz, Suarin, Pebrianti, Dwi, Bayuaji, Luhur, Muhammad, Syafrullah, Zulkifli, Musa

    Published 2018
    “…Number of iterations and accuracy of localization are presented and compared with navigation strategy based on Particle Swarm Optimization (PSO). The analysis of the performance of proposed algorithm is conducted by considering two different parameters. …”
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  5. 5
    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments

    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

    Published 2013
    “…The motion planning problem poses the question of how a robot can move from an initial to a final position. Sampling-based motion planning is a class of randomized path planning algorithms with proven completeness. …”
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  6. 6
    An improved optimization algorithm-based prediction approach for the weekly trend of COVID-19 considering the total vaccination in Malaysia: A novel hybrid machine learning approach

    An improved optimization algorithm-based prediction approach for the weekly trend of COVID-19 considering the total vaccination in Malaysia: A novel hybrid machine learning approac... by Ahmed, Marzia, Sulaiman, M. H., Mohamad, A. J., Rahman, Md. Mostafijur

    Published 2023
    “…This study concludes, based on its experimental findings, that hybrid IBMOLSSVM outperforms cross validations, original BMO, ANN and few other hybrid approaches with optimally optimized parameters.…”
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  7. 7
    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors

    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

    Published 2025
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  8. 8
    A fast learning network with improved particle swarm optimization for intrusion detection system

    A fast learning network with improved particle swarm optimization for intrusion detection system by Ali, Mohammed Hasan

    Published 2019
    “…However, the internal power parameters (weight and basis) of FLN are initialized at random, causing the algorithm to be unstable. …”
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  9. 9
    Identification of manipulator kinematics parameters through iterative method

    Identification of manipulator kinematics parameters through iterative method by Baharin, Iskandar, Hasan, Md. Mahmud

    “…A gradient projection algorithm was used to obtain the optimal parameters that had satisfied the world coordinates from the joint angles reading. …”
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  10. 10
    The impact of executive function and aerobic exercise recognition in obese children under deep learning

    The impact of executive function and aerobic exercise recognition in obese children under deep learning by JING, XIN, ABDULLAH, BORHANNUDIN, ABU SAAD, HAZIZI, YANG, XIANGKUN

    Published 2025
    “…Initially, a motion recognition model based on STN and Lucas–Kanade optical flow algorithm optimization was constructed. …”
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  11. 11
    Assessing the chaotic map population initializations for sine cosine algorithm using the case study of pairwise test suite generation

    Assessing the chaotic map population initializations for sine cosine algorithm using the case study of pairwise test suite generation by Din, Fakhrud, Kamal Zuhairi, Zamli, Abdullah, Nasser

    Published 2022
    “…Sine Cosine Algorithm (SCA) is a new population based meta-heuristic algorithm that exploits both the sine and cosine functions for its update operators. …”
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  12. 12
    Logical effort base adder circuits transistor sizing using constriction factor and mutative variants of particle swarm optimization algorithm / Muhammad Aiman Johari

    Logical effort base adder circuits transistor sizing using constriction factor and mutative variants of particle swarm optimization algorithm / Muhammad Aiman Johari by Johari, Muhammad Aiman

    Published 2015
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  13. 13
    A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system

    A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system by M.H., Ali, Mohamad, Fadlizolkipi, Ahmad Firdaus, Zainal Abidin, Nik Zulkarnaen, Khidzir

    Published 2018
    “…However, the internal power parameters (weight and basis) of ELM are initialized at random, causing the algorithm to be unstable. …”
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  14. 14
    PSO-tuned pid sliding surface of sliding mode control for an electro-hydraulic actuator system

    PSO-tuned pid sliding surface of sliding mode control for an electro-hydraulic actuator system by Chong, Chee Soon

    Published 2017
    “…This thesis presents the optimization on the Proportional-Integral-Derivative (PID) sliding surface of the Sliding Mode Control (SMC) scheme by using Particle Swarm Optimization (PSO) algorithm, applied to EHA system particularly for positioning tracking control. …”
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  15. 15
    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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  16. 16
    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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  17. 17
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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  18. 18
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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  19. 19
    LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting

    LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, M. N. M., Kahar

    Published 2015
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  20. 20
    Optimization of slosh suppression system through data-driven state feedback controller

    Optimization of slosh suppression system through data-driven state feedback controller by Nurul Najihah, Zulkifli

    Published 2024
    “…By performing a one-shot experiment, the initial input-output data is generated, recorded, and properly rearranged to be utilized to solve the control problem based on the Data-driven Linear Matrix Inequality (LMI), Data-driven Pole Placement, and Fictitious Reference Iterative Tuning-Particle Swarm Optimization (FRIT-PSO) to compute the control problem. …”
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