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  1. 1
    Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification

    Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification by Fajila, Fathima, Yusof, Yuhanis

    Published 2024
    “…Recently, the swarm-based hybrid algorithms have given significant performance in cancer 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
    “…Specifically, 6 benchmark classification datasets are used for training the hybrid Artificial Neural Network algorithms. …”
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  3. 3
    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals

    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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  4. 4
    GPSO versus GA in facial emotion detection

    GPSO versus GA in facial emotion detection by Bashir, Mohammed Ghandi, Ramachandran, Nagarajan, Prof. Dr., Sazali, Yaacob, Prof. Dr., Hazry, Desa, Assoc. Prof. Dr.

    Published 2012
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  5. 5
    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection

    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

    Published 2020
    “…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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  6. 6
    Differential evolution for neural networks learning enhancement

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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  7. 7
    Hybrid binary grey Wolf with Harris hawks optimizer for feature selection

    Hybrid binary grey Wolf with Harris hawks optimizer for feature selection by Al-Wajih, R., Abdulkadir, S.J., Aziz, N., Al-Tashi, Q., Talpur, N.

    Published 2021
    “…The findings revealed that the proposed method was effective in improving the performance of the BGWO algorithm. …”
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  8. 8
    Hybrid Binary Grey Wolf with Harris Hawks Optimizer for Feature Selection

    Hybrid Binary Grey Wolf with Harris Hawks Optimizer for Feature Selection by Al-Wajih, R., Abdulkadir, S.J., Aziz, N., Al-Tashi, Q., Talpur, N.

    Published 2021
    “…The findings revealed that the proposed method was effective in improving the performance of the BGWO algorithm. …”
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  9. 9
    Hybrid binary grey Wolf with Harris hawks optimizer for feature selection

    Hybrid binary grey Wolf with Harris hawks optimizer for feature selection by Al-Wajih, R., Abdulkadir, S.J., Aziz, N., Al-Tashi, Q., Talpur, N.

    Published 2021
    “…The findings revealed that the proposed method was effective in improving the performance of the BGWO algorithm. …”
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  10. 10
    Binary Multi-Objective Grey Wolf Optimizer for Feature Selection in Classification

    Binary Multi-Objective Grey Wolf Optimizer for Feature Selection in Classification by Al-Tashi, Q., Abdulkadir, S.J., Rais, H.M., Mirjalili, S., Alhussian, H., Ragab, M.G., Alqushaibi, A.

    Published 2020
    “…A wrapper based Artificial Neural Network (ANN) is used to assess the classification performance of a subset of selected features. …”
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  11. 11
    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization

    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2015
    “…The algorithm is improved with Particle Swarm Optimization that trains three different supervised classifiers. …”
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  12. 12
    Swarm intelligence-based feature selection for amphetamine-type stimulants (ATS) drug 3D molecular structure classification

    Swarm intelligence-based feature selection for amphetamine-type stimulants (ATS) drug 3D molecular structure classification by Draman @ Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri

    Published 2021
    “…For this purpose, the binary version of swarm algorithms facilitated with the S-shaped or sigmoid transfer function known as binary whale optimization algorithm (BWOA), binary particle swarm optimiza-tion algorithm (BPSO), and new binary manta-ray foraging opti-mization algorithm (BMRFO) are developed for feature selection. …”
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  13. 13
    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification

    Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

    Published 2022
    “…The major contribution of this research is to introduce a Taylor-Bird Swarm optimization-based Deep Belief Network (Taylor-BSA-based DBN) for medical data classification. …”
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  14. 14
    Feature selection based on particle swarm optimization algorithm for sentiment analysis classification

    Feature selection based on particle swarm optimization algorithm for sentiment analysis classification by Nurcahyawati, Vivine, Mustaffa, Zuriani

    Published 2021
    “…An improved approach was proposed to increase the sentiment analysis accuracy based on text pre-processing and Naïve Bayes Classifier algorithm hybrid with Particle Swarm Optimization (NBC-PSO). …”
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  15. 15
    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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  16. 16
    An improved data classification framework based on fractional particle swarm optimization

    An improved data classification framework based on fractional particle swarm optimization by Sherwani, Fahad

    Published 2019
    “…It can be concluded from the simulation results that the proposed MOFPSO-ERNN classification algorithm demonstrated good classification performance in terms of classification accuracy (Breast Cancer = 99.01%, EEG = 99.99%, PIMA Indian Diabetes = 99.37%, Iris = 99.6%, Thyroid = 99.88%) as compared to the existing hybrid classification techniques. …”
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  17. 17
    Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation

    Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Draman @ Muda, Noor Azilah

    Published 2011
    “…Ant Swarm Optimization refers to the hybridization of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms to enhance optimization performance. …”
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  18. 18
    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization

    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2014
    “…Several machine learning techniques based on supervised learning have been adopted in the classification of malware. …”
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  19. 19
    On the exploration and exploitation in popular swarm-based metaheuristic algorithms

    On the exploration and exploitation in popular swarm-based metaheuristic algorithms by Hussain, Kashif, Mohd Salleh, Mohd Najib, Cheng, Shi, Shi, Yuhui

    Published 2018
    “…Among such algorithms are swarm-based methods like particle swarm optimization and ant colony optimization which are increasingly attracting new researchers. …”
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  20. 20
    Swarm negative selection algorithm for electroencephalogram signals classification

    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…Such automated systems must rely on robust and effective algorithms for detection and prediction. Approach: The proposed detection system of epileptic seizure in EEG signals is based on Discrete Wavelet Transform (DWT) and Swarm Negative Selection (SNS) algorithm. …”
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