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  1. 1
    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction

    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

    Published 2014
    “…Furthermore, here these algorithms used to train the MLP on two tasks; the seismic event's prediction and Boolean function classification. …”
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  2. 2
    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
    “…Artificial Neural Networks (ANN) techniques, mostly Back-Propagation Neural Network (BPNN) algorithm has been used as a tool for recognizing a mapping function among a known set of input and output examples. …”
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  3. 3
    Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation

    Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation by Kamaruddin, Shafie, Bahari, Muhammad Syahril, Pham, Duc Truong, Mohd Amin Hamzas, Mohd Fidzwan, Zakaria, S

    Published 2019
    “…The Bees Algorithm is a population-based optimisation algorithm inspired by the food foraging behaviour of honey bees. …”
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  4. 4
    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules

    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

    Published 2013
    “…The successful work on hybridization of ACO and SA algorithms has led to the improved learning ability of ACO for classification. …”
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  5. 5
    Global gbest guided-artificial bee colony algorithm for numerical function optimization

    Global gbest guided-artificial bee colony algorithm for numerical function optimization by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

    Published 2018
    “…The two well-known honeybees-based upgraded algorithms, Gbest Guided Artificial Bee Colony (GGABC) and Global Artificial Bee Colony Search (GABCS), use the foraging behavior of the global best and guided best honeybees for solving complex optimization tasks. …”
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  6. 6
    Protein Conformantional Search Using Bees Algorithm

    Protein Conformantional Search Using Bees Algorithm by Bahamish, Hesham Awadh A., Abdullah, Rosni, Salam, Rosalina Abdul

    Published 2008
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  7. 7
    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
    “…This report presents the first stage of an ongoing research which is the problem solving of highly complex tasks using Bee-Inspired algorithms. Bee-Inspired algorithms are partially referring to the nature of bee swarm behaviour. …”
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  8. 8
    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
    “…In addition, 2 types of scout bee were used for to intensify the probability property of the algorithm. …”
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  9. 9
    Construction of Cryptographically Strong S-Boxes Inspired by Bee Waggle Dance

    Construction of Cryptographically Strong S-Boxes Inspired by Bee Waggle Dance by Isa H., Jamil N., Z�aba M.R.

    Published 2023
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  10. 10
    Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems

    Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems by Abdul Hamid, Norhamreeza, Mohd Nawi, Nazri, Ghazali, Rozaida, Mohd Salleh, Mohd Najib

    Published 2011
    “…The back propagation (BP) algorithm is a very popular learning approach in feedforward multilayer perceptron networks. …”
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  11. 11
    Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam

    Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

    Published 2017
    “…At first, a peak classification algorithm is developed based on the general following processes including peak candidate identification, feature extraction, and classification. …”
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  12. 12
    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah

    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

    Published 2009
    “…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. The study involves the development of Artificial Bee Colony (ABC) algorithm to implement loss minimization in a distribution system. …”
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  13. 13
    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah

    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

    Published 2009
    “…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. The study involves the development of Artificial Bee Colony (ABC) algorithm to implement loss minimization in a distribution system. …”
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  14. 14
    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…Classification of imbalanced datasets remained a significant issue in data mining and machine learning (ML) fields. …”
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  15. 15
    Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification

    Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

    Published 2023
    “…Support Vector Machine and Naïve Bayes classifiers were used as a fitness function for the ABC algorithm. …”
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  16. 16
    Congestion management based optimization technique using bee colony

    Congestion management based optimization technique using bee colony by Rahim M.A., Musirin I., Abidin I.Z., Othman M.M., Joshi D.

    Published 2023
    “…The study involved the development of bee colony algorithm in addressing congestion management, considering cost optimization as the objective function. …”
    Conference Paper
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  17. 17
    Detection and classification of conflict flows in SDN using machine learning algorithms

    Detection and classification of conflict flows in SDN using machine learning algorithms by Mutaz Hamed Hussien Khairi, Sharifah Hafizah Syed Ariffin, Nurul Mu'azzah Abdul Latiff, Kamaludin Mohamad Yusof, Mohamed Khalafalla Hassan, Fahad Taha Al-Dhief, Mosab Hamda, Suleman Khan, Muzaffar Hamzah

    Published 2021
    “…Moreover, applying machine learning algorithms in the identification and classification of conflicting flows has limitations. …”
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  18. 18
    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
    “…The efficiency of the proposed methods is compared with the first and second order optimisation method by means of simulation on UCI Machine Learning Repository, Knowledge Extraction Evolutionary Learning and Kaggle dataset. …”
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  19. 19
    Mobile machine vision for railway surveillance system using deep learning algorithm

    Mobile machine vision for railway surveillance system using deep learning algorithm by Kit, Guan Lim, Daniel Siruno, Min, Keng Tan, Chung, Fan Liau, Sha, Huang, Tze, Kenneth Kin Teo

    Published 2021
    “…In this paper, object detection model is developed and implemented with deep learning algorithm. Object classification model is produced through the model training with Deep Neural Networks (DNN). …”
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    Proceedings
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  20. 20
    Functional link neural network with modified bee-firefly learning algorithm for classification task

    Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

    Published 2016
    “…The single layer property of FLNN also make the learning algorithm used less complicated compared to MLP network. …”
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