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  1. 1
    Bats echolocation-inspired algorithms for global optimisation problems

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…The works related to swarm intelligence algorithms include the development of the algorithm itself, its modification and improvisation as well as its application in solving global optimisation problems. …”
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  2. 2
    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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  3. 3
    An improvement of back propagation algorithm using halley third order optimisation method for classification problems

    An improvement of back propagation algorithm using halley third order optimisation method for classification problems by Abdul Hamid, Norhamreeza

    Published 2020
    “…This algorithm utilises first order optimisation method namely Gradient Descent (GD) method which attempts to minimise the error of network. …”
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  4. 4
    Improvement Of Stereo Matching Algorithm Based On Sum Of Gradient Magnitude Differences And Semi-Global Method With Refinement Step

    Improvement Of Stereo Matching Algorithm Based On Sum Of Gradient Magnitude Differences And Semi-Global Method With Refinement Step by Hamzah, Rostam Affendi, Ibrahim, Haidi

    Published 2018
    “…A new stereo matching algorithm which uses improved matching cost computation and optimisation using the semi-global method (SGM) is proposed.The absolute difference is sensitive to low textured regions and high noise on the stereo images with radiometric distortions. …”
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  5. 5
    Aco-based feature selection algorithm for classification

    Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

    Published 2022
    “…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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  6. 6
    The fusion of particle swarm optimization (PSO) and interior point method (IPM) as cooperative movement control algorithm in Swarm Robotics / Dada Emmanuel Gbenga

    The fusion of particle swarm optimization (PSO) and interior point method (IPM) as cooperative movement control algorithm in Swarm Robotics / Dada Emmanuel Gbenga by Dada Emmanuel, Gbenga

    Published 2016
    “…Also, many of these PSO algorithms employed hybrid methods that integrate other optimisation algorithms with the standard PSO. …”
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  7. 7
    Design Of Perturbative Hyper-Heuristics For Combinatorial Optimisation

    Design Of Perturbative Hyper-Heuristics For Combinatorial Optimisation by Choong, Shin Siang

    Published 2019
    “…Exact algorithm is a sub-class of techniques that is able to guarantee global optimality. …”
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  8. 8
    OPTIMAL CABLE SELECTION IN RADIAL DISTRIBUTION NETWORKS CONSIDERING PLANNER'S DEFINED VOLTAGE DROP LIMIT

    OPTIMAL CABLE SELECTION IN RADIAL DISTRIBUTION NETWORKS CONSIDERING PLANNER'S DEFINED VOLTAGE DROP LIMIT by Ab Ghani, Mohd Ruddin

    Published 2002
    “…New computer algorithms are provided to determine the optimal cable size selection considering radial distribution networks and planner of power distribution defined allowable voltage drop all over the networks. …”
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  9. 9
    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah

    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

    Published 2015
    “…Anderson-Darling (AD) and Goodness of Fit test is used to identify the best fitted distribution model to the real data. Four traffic distribution which are normal, lognormal, Weibull and exponential distribution are fitted and derived. …”
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  10. 10
    RED, GRED, AGRED congestion control algorithms in heterogeneous traffic types

    RED, GRED, AGRED congestion control algorithms in heterogeneous traffic types by Seifaddini, Omid, Abdullah, Azizol, Vosough, Hamid

    Published 2013
    “…The performance metric used to show the analysis of these algorithms with mentioned distributions is Packet Loss (Pl).Results of simulation show that each algorithm performed a fair dropping of data packets without considering of their types.…”
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  11. 11
    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah

    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

    Published 2015
    “…Anderson-Darling (AD) and Goodness of Fit test is used to identify the best fitted distribution model to the real data. Four traffic distribution which are normal, lognormal, Weibull and exponential distribution are fitted and derived. …”
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  12. 12
    An improved particle swarm optimization algorithm for data classification

    An improved particle swarm optimization algorithm for data classification by Waqas Haider Bangyal, Kashif Nisar, Tariq Rahim Soomro, Ag Asri Ag Ibrahim, Ghulam Ali Mallah, Nafees Ul Hassan, Najeeb Ur Rehman

    Published 2023
    “…Particle Swarm Optimization (PSO) is a metaheuristic algorithm based on swarm intelligence, widely used to solve global optimisation problems throughout the real world. …”
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  13. 13
    Red, gred, agred congestion control algorithms in heterogeneous traffic types

    Red, gred, agred congestion control algorithms in heterogeneous traffic types by Seifaddini, Omid, Abdullah, Azizol, Vosough, Hamid

    Published 2013
    “…Results of simulation show that each algorithm performed a fair dropping of data packets without considering of their types.…”
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  14. 14
    Gooseneck barnacle optimization algorithm: A novel nature inspired optimization theory and application

    Gooseneck barnacle optimization algorithm: A novel nature inspired optimization theory and application by Ahmed, Marzia, Mohd Herwan, Sulaiman, Ahmad Johari, Mohamad, Rahman, Mostafijur

    Published 2024
    “…This paper introduces the Gooseneck Barnacle Optimisation Algorithm (GBO) as a novel evolutionary method inspired by the natural mating behaviour of gooseneck barnacles, which involves sperm casting and self-fertilization. …”
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  15. 15
    An Efficient Hybrid Conjugate Gradient Method for Unconstrained Optimisation

    An Efficient Hybrid Conjugate Gradient Method for Unconstrained Optimisation by Mamat, Prof. Dr. Mustafa

    Published 2020
    “…One of the common efficient techniques to solve large-scale unconstrained optimisation issues is the conjugate gradient method, because of its simplicity, low memory consumptions and global convergence properties. …”
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  16. 16
    Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor

    Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor by Ramli, Mohamad Raziff, Abal Abas, Zuraida, Desa, Mohammad Ishak, Zainal Abidin, Zaheera, Al Azzam, Malik Bader Hasan

    Published 2019
    “…Heuristic optimisation method typically hinges on the efficiency in exploitation and global diverse exploration. …”
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  17. 17
    Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation

    Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation by Toha, Siti Fauziah, Abd Latiff, I., Mohamad, M., Tokhi, M Osman

    Published 2009
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  18. 18
    Sensitivity analysis of GA parameters for ECED problem

    Sensitivity analysis of GA parameters for ECED problem by Kamil K., Razali N.M.M., Teh Y.Y.

    Published 2023
    “…Besides the conventional method by using the Lagrange Multiplier several evolutionary computation techniques such as Genetic Algorithm, Particle Swarm Optimisation, Ant Colony and Differential Evolution have been gaining popularity in solving general economic dispatch problems due to their desirable characteristics such as non-gradient dependent and ability to search for global optima. …”
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  19. 19
    Hybrid particle swarm optimization algorithm with fine tuning operators

    Hybrid particle swarm optimization algorithm with fine tuning operators by Murthy, G.R., Arumugam, M.S., Loo, C.K.

    Published 2009
    “…This method combines the merits of the parameter-free PSO (pf-PSO) and the extrapolated particle swarm optimization like algorithm (ePSO). …”
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  20. 20
    An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition

    An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

    Published 2019
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