Search Results - (( probable evaluation method algorithm ) OR ( global optimisation method 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
    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
    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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  9. 9
    Tree-based contrast subspace mining method

    Tree-based contrast subspace mining method by Florence Sia Fui Sze

    Published 2020
    “…Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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  10. 10
    Analysis of tumour control probability, normal tissue complication probability and isotoxic effects for prostate cancer

    Analysis of tumour control probability, normal tissue complication probability and isotoxic effects for prostate cancer by Fauzee, Nurnada Syahrain Mohd

    Published 2016
    “…Variation in evaluation method will not give similar findings even same data is used. …”
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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
    Modified Contrast Limited Adaptive Histogram Equalization for high dynamic range images

    Modified Contrast Limited Adaptive Histogram Equalization for high dynamic range images by Tung, Li Qian

    Published 2012
    “…The generated probability map of the proposed tone mapped algorithm was then compared with the generated probability map of Ward tone mapping algorithm. …”
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  13. 13
    The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer

    The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer by Ahmad, Noor Ashikin

    Published 2015
    “…Four treatment plans are created and DVHs are evaluated based on criteria of acceptance level. NTCP values for thorax plan one and two are evaluated by using different algorithm. …”
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    Monograph
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  14. 14
    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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  15. 15
    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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  16. 16
    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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    Proceeding Paper
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  17. 17
    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern

    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

    Published 2012
    “…CE is a new algorithm that was recently developed using probability. …”
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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. …”
    Conference paper
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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
    Probabilistic evaluation of wind power generation

    Probabilistic evaluation of wind power generation by Razali N.M.M., Misbah M.

    Published 2023
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    Conference paper
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