Search Results - (( global optimisation methods algorithm ) OR ( parallel optimization means algorithm ))*

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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
    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function

    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function by Hammash, Nayif Mohammed

    Published 2012
    “…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
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  3. 3
    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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  4. 4
    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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  5. 5
    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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  6. 6
    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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  7. 7
    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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  8. 8
    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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  9. 9
    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line

    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line by Noroziroshan, Alireza, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Napsiah

    Published 2010
    “…As the total objective values in most of problems could not be improved by simulated algorithm, it proved the well performing of proposed intelligence based genetic algorithm in reaching the near optimal solutions.…”
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  10. 10
    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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  11. 11
    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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  12. 12
    Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization

    Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization by M. F. F., Ab Rashid, Ahmad Nasser, Mohd Rose, N. M. Zuki, N. M.

    Published 2022
    “…Based on the optimization results, the MFO outperformed other comparison algorithms for the mean fitness and also the best fitness. …”
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  13. 13
    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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  14. 14
    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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  15. 15
    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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  16. 16
    An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title

    An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title by Khalaf, Emad Taha

    Published 2019
    “…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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  17. 17
    Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models.

    Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models. by Kwad, Ayad Mahmood

    Published 2022
    “…Best Hammerstein parallel NN polynomial based model and series-parallel NN polynomial model are 88.75% and 93.9% respectively, for best Hammerstein parallel NN sigmoid based model and series-parallel NN sigmoid based model 78.26% and 95.95% respectively, and for best Hammerstein parallel NN hyperbolic tangent based model and series-parallel NN hyperbolic tangent based model 70.7% and 96.4% respectively. …”
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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
    Dengue outbreak prediction: hybrid meta-heuristic model

    Dengue outbreak prediction: hybrid meta-heuristic model by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Ernawan, Ferda, Yuhanis, Yusof, Mohamad Farhan, Mohamad Mohsin

    Published 2018
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