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  1. 1
    Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC)

    Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC) by Ahmad, Faudziah, Ku-Mahamud, Ku Ruhana, Sainin, Mohd Shamrie, Airuddin, Ahmad

    Published 2015
    “…The algorithm involved three main steps, filtration, recognition and detection.Artificial Bee Colony, Fuzzy Logic, Otsu and Geometry formula were incorporated to achieve the goal.Ninety-four leaf images were used in this algorithm combination experiment.The study was conducted in four phases, filtration, recognition, detection and evaluation.Comparison was made with four other algorithms, Otsu, Canny, Robert and Sobel. …”
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  2. 2
    Computational intelligence technique for DG installation within contingency scenario / Muhamad Saifullah Mahmud Affandi

    Computational intelligence technique for DG installation within contingency scenario / Muhamad Saifullah Mahmud Affandi by Mahmud Affandi, Muhamad Saifullah

    Published 2014
    “…Meanwhile, for ABC algorithm is inspired of the intelligent behavior of bees during the nectar search process. …”
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  3. 3
    Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control

    Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control by Naidu, K., Mokhlis, Hazlie, Bakar, Ab Halim Abu

    Published 2014
    “…The robustness of the proposed algorithm is further investigated by evaluating the response of the system under simultaneous step load perturbation (SLP), changing load demand and collectively varying system parameters in the range of ±50%. …”
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  4. 4
    Improved cuckoo search based neural network learning algorithms for data classification

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…Finally, the proposed CS hybrid variants such as; HACPSO, HACPSO-BP, HACPSO-LM, CSBP, CSLM, CSERN, and CSLMERN are evaluated and compared with conventional Back propagation Neural Network (BPNN), Artificial Bee Colony Neural Network (ABCNN), Artificial Bee Colony Back propagation algorithm (ABC-BP), and Artificial Bee Colony Levenberg-Marquardt algorithm (ABC-LM). …”
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  5. 5
    Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim

    Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim by Che Ibrahim, Mohd Erman Safawie

    Published 2012
    “…This project focuses on step-up cluster computing and a parallel Genetic Algorithm. …”
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  6. 6
    Examination invigilation timetable using Genetic Algorithm / Mohamad Fakhrullah Ibrahim

    Examination invigilation timetable using Genetic Algorithm / Mohamad Fakhrullah Ibrahim by Ibrahim, Mohamad Fakhrullah

    Published 2025
    “…To overcome these issues, a system utilizing a Genetic Algorithm (GA) was developed to automate and optimize the timetabling process. …”
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  7. 7
    An enhanced version of black hole algorithm via levy flight for optimization and data lustering problems

    An enhanced version of black hole algorithm via levy flight for optimization and data lustering problems by Haneen, Abd Wahab, Noraziah, Ahmad, Alsewari, Abdulrahman A., Sinan, Q. Salih

    Published 2019
    “…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems, in which it is a population-based metaheuristic that emulates the phenomenon of the black holes in the universe. …”
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  8. 8
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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  9. 9
    An enhanced version of black hole algorithm via levy flight for optimization and data clustering problems

    An enhanced version of black hole algorithm via levy flight for optimization and data clustering problems by Abdulwahab, Haneen A., Noraziah, Ahmad, Al-Sewari, Abdul Rahman Ahmed Mohammed, Salih, Sinan Q.

    Published 2019
    “…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems, in which it is a population-based metaheuristic that emulates the phenomenon of the black holes in the universe. …”
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  10. 10
    Nomadic people optimizer (NPO) for large-scale optimization problems

    Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

    Published 2019
    “…The local search of NPO is implemented using a unique distribution formula, while the global search ability contains a levy flight equation which generates a step for moving the families towards the new positions. …”
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  11. 11
    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation

    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

    Published 2019
    “…In order to train Ridgelet probabilistic neural network, a modified differential evolution algorithm with new mutation phase, crossover process, and selection mechanism is introduced. …”
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  12. 12
    Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization

    Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization by Khosropanah, Pegah, Ramli, Abdul Rahman, Lim, Kheng Seang, Marhaban, Mohammad Hamiruce, Ahmedov, Anvarjon

    Published 2018
    “…We also developed an unsupervised algorithm utilizing a wavelet method to remove eye blink artifacts. …”
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  13. 13
    Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization

    Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization by Khosropanah, Pegah, Ramli, Abdul Rahman, Lim, Kheng Seang, Marhaban, Mohammad Hamiruce, Ahmedov, Anvarjon

    Published 2018
    “…We also developed an unsupervised algorithm utilizing a wavelet method to remove eye blink artifacts. …”
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  14. 14
    RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights

    RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights by Seyed Vahid Moravvej, Roohallah Alizadehsani, Sadia Khanam, Zahra Sobhaninia, Afshin Shoeibi, Fahime Khozeimeh, Zahra Alizadeh Sani, Ru-San Tan, Abbas Khosravi, Saeid Nahavandi, Nahrizul Adib Kadri, N. Arunkumar, U.Rajendra Acharya, Muhammad Mokhzaini Azizan

    Published 2024
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  15. 15
    Evaluation of optimal cooling control for seeded batch crystallization inclusive dissolution with uncertainties

    Evaluation of optimal cooling control for seeded batch crystallization inclusive dissolution with uncertainties by Siti Zubaidah, Adnan

    Published 2020
    “…The optimization algorithm was employed in order to determine the optimal set-point trajectory for closed-loop control. …”
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  16. 16
    Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches

    Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches by Mohd Pauzi, Nur Fazlinda

    Published 2015
    “…The performance of the ABC algorithm was evaluated through three different onlooker approaches i.e. method 3+0+0 (three onlooker bees are dedicated to the best employee bee), method 2+1+0 (two onlooker bees are dedicated to the best employee bee and one onlooker bee is dedicated to second best employee bee) and method 1+1+1 (one onlooker bee is dedicated to each employee bee). …”
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  17. 17
    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation

    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

    Published 2018
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  18. 18
    Defect detection based on extreme edge of defective region histogram

    Defect detection based on extreme edge of defective region histogram by Wakaf, Zouhir, Jalab, Hamid Abdullah

    Published 2018
    “…This study proposes a new automatic thresholding algorithm based on the acquisition of the defective region histogram and the selection of its extreme edge as the threshold value to segment all defective objects in the foreground from the image background. …”
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  19. 19
    Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor

    Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor by Hafz Nour, Mutasim Ibrahim

    Published 2008
    “…In the proposed method, the measured motor’s current and the estimated motor’s voltage are processed through a signal processing block and a PI regulator to calculate the angle of the rotor position.Finally the performance of the HMRASC and the rotor position angle estimation algorithms are evaluated by simulation and verified experimentally for two motors using MCK2407 kit and IMDM15 board which are based on the TMS320LF2407 fixed point Digital Signal Processor (DSP) for different operating conditions. …”
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  20. 20
    Algorithm in the fluidized-bed reactor for the polymerization of propylene

    Algorithm in the fluidized-bed reactor for the polymerization of propylene by Zanil, Mohd Fauzi, Chan, K.O., Hussain, Mohd Azlan

    Published 2019
    “…A modified artificial bee optimization is proposed in this study. The algorithm is based on the colony behavior of certain bee species to achieve optimal solution in the bounded environment. …”
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