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  1. 1
    Application of Bee Colony Optimization (BCO) in NP-Hard Problems

    Application of Bee Colony Optimization (BCO) in NP-Hard Problems by Kamarudin, Muhammad Sariy Syazwan

    Published 2011
    “…Bee-Inspired algorithms were presumed to bring the new direction in the field of Swann Intelligence. …”
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  2. 2
    Intelligent road recognition system for automous vehicle

    Intelligent road recognition system for automous vehicle by Soon, Adrian Bee Toing

    Published 2013
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  3. 3
    Application of the bees algorithm to the selection features for manufacturing data

    Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

    Published 2007
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  4. 4
    Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm

    Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm by Sulaiman, Suriani, Ahmed Yahya, Saba, Mohd Shukor, Nur Sakinah, Ismail , Amelia Ritahani, Zaahirah, Qazi, Yaacob, Hamwira Sakti, Abdul Rahman, Abdul Wahab, Dzulkifli, Mariam Adawiah

    Published 2015
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  5. 5
    A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem

    A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem by Lee, Wei Wen, Hashim, Mohd Ruzaini

    Published 2023
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  6. 6
    Test Data Generation for Event Driven System Using Bees Algorithm

    Test Data Generation for Event Driven System Using Bees Algorithm by Mohammed Zabil, Mohd H., Kamal Z., Zamli

    Published 2013
    “…In this paper we discuss and proposed a new strategy for generating test data for event-driven system using a bio inspired artificial intelligent, namely Bees Algorithm (BA). …”
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  7. 7
    Artificial intelligence to predict pre-clinical dental student academic performance based on pre-university results: a preliminary study

    Artificial intelligence to predict pre-clinical dental student academic performance based on pre-university results: a preliminary study by Lestari, Widya, Abdullah, Adilah Syahirah, Ahmad Amin, Afifah Munirah, faridah, Nur, Sukotjo, Cortino, Ismail, Azlini, mohamad ibrahim, mohamad shafiq, Insani, Nashuha, Utomo, Chandra Prasetyo

    Published 2024
    “…RF was the most precise algorithm for predicting grades A, B, and C, followed by LR, DT, and SVM. …”
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  8. 8
    Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions

    Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions by Kalantari, Ali, Kamsin, Amirrudin, Shamshirband, Shahaboddin, Gani, Abdullah, Alinejad-Rokny, Hamid, Chronopoulos, Anthony T.

    Published 2018
    “…On the other hand, the hybridization of SVM with other methods such as SVM-Genetic Algorithm (SVM-GA), SVM-Artificial Immune System (SVM-AIS), SVM-AIRS and fuzzy support vector machine (FSVM) had great performances achieving better results in terms of accuracy, sensitivity and specificity.…”
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  9. 9
    Intelligent Tuning of PID Controller for Double-Link Flexible Robotic Arm Manipulator by Artificial Bee Colony Algorithm

    Intelligent Tuning of PID Controller for Double-Link Flexible Robotic Arm Manipulator by Artificial Bee Colony Algorithm by Jamali, Annisa, Mat Darus, I.Z., Yatim, H.M, A. Talib, M. H., Hadi, M.S, Tokhi, M.O.

    Published 2020
    “…This research focuses on the development of intelligent controller utilizing artificial bee colony (ABC) algorithm to tune proportional integral derivative (PID) parameters for controlling two-link flexible manipulator (TLFRM). …”
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  10. 10
    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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  11. 11
    A hybrid of Simple Constrained artificial bee colony algorithm and flux balance analysis for enhancing Lactate and Succinate in Escherichia Coli

    A hybrid of Simple Constrained artificial bee colony algorithm and flux balance analysis for enhancing Lactate and Succinate in Escherichia Coli by Hon, Mei Kie, Mohd Saberi, Mohamad, Abdul Hakim, Mohamed Salleh, Choon, Yee Wen, Muhammad Akmal, Remli, Mohd Arfian, Ismail, Omatu, Sigeru, Corchado, Juan Manuel

    Published 2018
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  12. 12
    Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi Mohammed

    Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi M... by Mohammed, Daw Saleh Sasi

    Published 2016
    “…In order produce a global optimal solution of AUC, the self-adaptive strategy was proposed to serve as a new mutation technique responsible to provide a new population for discrete artificial bee colony. The newly designed algorithm is termed as the discrete artificial bee colony associated with selfadaptive strategy (DABCSAS). …”
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  13. 13
    Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation

    Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation by Alazzawi, A.K., Rais, H.M., Basri, S.

    Published 2019
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  14. 14
    Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation

    Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation by Alazzawi, A.K., Rais, H.M., Basri, S.

    Published 2019
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  15. 15
    Lung cancer medical images classification using hybrid CNN-SVM

    Lung cancer medical images classification using hybrid CNN-SVM by Abdulrazak Yahya, Saleh, Chee, Ka Chin, Vanessa, Penshie, Hamada Rasheed Hassan, Al-Absi

    Published 2021
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  16. 16
    Optimal economic environmental power dispatch by using artificial bee colony algorithm

    Optimal economic environmental power dispatch by using artificial bee colony algorithm by Hassan, Elia Erwani, Mohd Noor, Hanan Izzati, Hashim, Mohd Ruzaini, Sulaima, Mohamad Fani, Bahaman, Nazrulazhar

    Published 2024
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  17. 17
    Autism Spectrum Disorder Classification Using Deep Learning

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…The CNN algorithm produces better results with an accuracy of 97.07%, compared with the SVM algorithm. …”
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  18. 18
    Time series data intelligent clustering algorithm for landslide displacement prediction

    Time series data intelligent clustering algorithm for landslide displacement prediction by Han, Liu, Shang, Tao, Shu, Jisen, Khan Chowdhury, Ahmed Jalal

    Published 2018
    “…To address this problem, an intelligent clustering algorithm for time series data in landslide displacement prediction based on nonlinear dynamic time bending is proposed in this paper. …”
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  19. 19
    Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi Mohammed

    Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi M... by Sasi Mohamme, Daw Saleh

    Published 2017
    “…In order produce a global optimal solution of AUC, the self-adaptive strategy was proposed to serve as a new mutation technique responsible to provide a new population for discrete artificial bee colony. The newly designed algorithm is termed as the discrete artificial bee colony associated with selfadaptive strategy (DABCSAS). …”
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  20. 20
    Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation

    Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation by Illias, Hazlee Azil, Wee, Zhao Liang

    Published 2018
    “…In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. …”
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