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  1. 1
    Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman

    Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman by Azman, Muhammad Izzat Azri

    Published 2017
    “…This project used Artificial Bee Colony Algorithms (ABC) by adapting the food foraging behaviour of bee in honey bee and find a suitable house for home buyer based on their requirement. …”
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  2. 2
    Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement

    Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement by Kadmin, Ahmad Fauzan

    Published 2023
    “…The estimation of Stereo Matching Algorithm (SMA) is one of the extensive research topics for obtaining the disparity map from two images. …”
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  3. 3
    Optimizing dam and reservoir operations using machine learning

    Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

    Published 2025
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  4. 4
    Fetal heart rate monitoring during pregnancy for assessing the well-being of the fetus

    Fetal heart rate monitoring during pregnancy for assessing the well-being of the fetus by Ibrahimy, Muhammad Ibn

    Published 2018
    “…The performance achieved from the comparison shows non-significant differences of means, low error percentages and linear correlation coefficient. …”
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  5. 5
    Fetal heart rate monitoring during pregnancy for assessing the well being of the fetus

    Fetal heart rate monitoring during pregnancy for assessing the well being of the fetus by Ibrahimy, Muhammad Ibn

    Published 2017
    “…The performance achieved from the comparison shows non-significant differences of means, low error percentages and linear correlation coefficient. …”
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  6. 6
    Fetal heart rate monitoring during pregnancy for assessing the well being of the fetus

    Fetal heart rate monitoring during pregnancy for assessing the well being of the fetus by Ibrahimy, Muhammad Ibn

    Published 2018
    “…The performance achieved from the comparison shows non-significant differences of means, low error percentages and linear correlation coefficient. …”
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  7. 7
    Fetal heart rate monitoring during pregnancy for assessing the well being of the fetus

    Fetal heart rate monitoring during pregnancy for assessing the well being of the fetus by Ibrahimy, Muhammad Ibn

    Published 2017
    “…The performance achieved from the comparison shows non-significant differences of means, low error percentages and linear correlation coefficient. …”
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  8. 8
    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 means that it spends a long time for the bees algorithm converge the optimum solution. …”
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  9. 9
    Data clustering using the bees algorithm

    Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

    Published 2007
    “…This paper proposes a clustering method that integrates the simplicity of the k-means algorithm with the capability of the Bees Algorithm to avoid local optima. …”
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  10. 10
    Non-fiducial based electrocardiogram biometrics with kernel methods

    Non-fiducial based electrocardiogram biometrics with kernel methods by Hejazi, Maryamsadat

    Published 2017
    “…The effectiveness of this algorithm is investigated by comparing with other AC based feature extraction algorithms involving AC/LDA (Linear Discriminant Analysis) and AC/PCA (Principal Component Analysis). …”
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  11. 11
    A near-optimal centroids initialization in K-means algorithm using bees algorithm

    A near-optimal centroids initialization in K-means algorithm using bees algorithm by Mahmuddin, Massudi, Yusof, Yuhanis

    Published 2009
    “…The K-mean algorithm is one of the popular clustering techniques.The algorithm requires user to state and initialize centroid values of each group in advance. …”
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  12. 12
    Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems

    Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems by Rahimi, Amir Masoud, Ramezani-Khansari, Ehsan

    Published 2021
    “…This study seeks to solve this problem using Artificial Bee Colony (ABC) Algorithm along with the proposed Discrete Nearest Neighborhood Algorithm (DNNA). …”
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  13. 13
    An improved artificial bee colony algorithm based on mean best-guided approach for continuous optimization problems and real brain MRI images segmentation

    An improved artificial bee colony algorithm based on mean best-guided approach for continuous optimization problems and real brain MRI images segmentation by Alrosan, Ayat, Alomoush, Waleed, Norwawi, Norita, Alswaitti, Mohammed, Makhadmeh, Sharif Naser

    Published 2024
    Subjects: “…Optimization algorithms…”
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  14. 14
    Power-efficient wireless coverage using minimum number of uavs

    Power-efficient wireless coverage using minimum number of uavs by Sawalmeh A., Othman N.S., Liu G., Khreishah A., Alenezi A., Alanazi A.

    Published 2023
    “…Antennas; Disasters; Genetic algorithms; Iterative methods; K-means clustering; Particle swarm optimization (PSO); 3-D placements; Artificial bee colony; Efficient 3d placement; Genetic algorithm; K-means; Particle swarm optimization; Placement algorithm; Power efficient; Unmanned aerial vehicle; Wireless coverage; Unmanned aerial vehicles (UAV); algorithm; animal; bee; Algorithms; Animals; Bees; Unmanned Aerial Devices…”
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  15. 15
    Adaptive filtering of EEG/ERP through bounded range artificial Bee Colony (BR-ABC) algorithm

    Adaptive filtering of EEG/ERP through bounded range artificial Bee Colony (BR-ABC) algorithm by Ahirwal, M.K., Kumar, A., Singh, G.K.

    Published 2014
    “…ANCs are also implemented with Least Mean Square (LMS) and Recursive Least Square (RLS) algorithm. …”
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  16. 16
    Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm

    Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm by Farah Nur Arina, Baharudin, Nor Azlina, Ab. Aziz, Mohamad Razwan, Abdul Malek, Anith Khairunnisa, Ghazali, Zuwairie, Ibrahim

    Published 2022
    “…Inertia weight artificial bee colony (IW-ABC) algorithms using linearly increasing, linearly decreasing, and exponentially increasing inertia are proposed here for the optimization of the indoor comfort index and energy usage. …”
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  17. 17
    Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm

    Indoor comfort and energy consumption optimization using an inertia weight artificial bee colony algorithm by Farah Nur Arina, Baharudin, Nor Azlina, Ab. Aziz, Mohamad Razwan, Abdul Malek, Anith Khairunnisa, Ghazali, Zuwairie, Ibrahim

    Published 2022
    “…Inertia weight artificial bee colony (IW-ABC) algorithms using linearly increasing, linearly decreasing, and exponentially increasing inertia are proposed here for the optimization of the indoor comfort index and energy usage. …”
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  18. 18
    Optimization grid scheduling with priority base and bees algorithm

    Optimization grid scheduling with priority base and bees algorithm by Ahmed, Mohammed Shihab

    Published 2014
    “…The main aim of this current research to propose an optimization of the initial scheduler for grid computing using the bees algorithm. Modern algorithms informed this research. …”
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  19. 19
    Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction

    Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

    Published 2014
    “…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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  20. 20
    Hydroclimatic data prediction using a new ensemble group method of data handling coupled with artificial bee colony algorithm

    Hydroclimatic data prediction using a new ensemble group method of data handling coupled with artificial bee colony algorithm by Basri Badyalina, Nurkhairany Amyra Mokhtar, Nur Amalina Mat Jan, Muhammad Fadhil Marsani, Mohamad Faizal Ramli, Muhammad Majid, Fatin Farazh Ya'acob

    Published 2022
    “…It is rare to find a hydrological application using the group method of data handling (GMDH) model, artificial bee colony (ABC) algorithm, and ensemble technique, precisely predicting ungauged sites. …”
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