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  1. 1
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  2. 2
    Hybrid of swarm intelligent algorithms in medical applications

    Hybrid of swarm intelligent algorithms in medical applications by Abubakar, Adamu, Haruna, Chiroma, Abdullah Muaz, Sanah, Ya'u Gital, Abdulsalam, Baba Dauda, Ali, Joda Usman, Muhammed

    Published 2019
    “…In this study, feed forward and Elman recurrent neural network (ERN) with swarm intelligent algorithms is used for the classification of the mentioned diseases. …”
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  3. 3
    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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  4. 4
    Studying the Effect of Training Levenberg Marquardt Neural Network by Using Hybrid Meta-Heuristic Algorithms

    Studying the Effect of Training Levenberg Marquardt Neural Network by Using Hybrid Meta-Heuristic Algorithms by Abubakar, A., Khan, A., Nawi, N.M., Rehman, M.Z., Teh, Y.W., Chiroma, H., Herawan, T.

    Published 2016
    “…The performances of the proposed Accelerated Particle Swarm Optimization Levenberg Marquardt (APSO-LM) algorithms compared by means of simulations on 7-Bit Parity and six UCI benchmark classification datasets. …”
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  5. 5
    Nature-Inspired Drone Swarming for Wildfires Suppression Considering Distributed Fire Spots and Energy Consumption

    Nature-Inspired Drone Swarming for Wildfires Suppression Considering Distributed Fire Spots and Energy Consumption by Alsammak I.L.H., Mahmoud M.A., Gunasekaran S.S., Ahmed A.N., Alkilabi M.

    Published 2024
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  6. 6
    Studying the effect of training Levenberg Marquardt neural network by using hybrid meta-heuristic algorithms

    Studying the effect of training Levenberg Marquardt neural network by using hybrid meta-heuristic algorithms by Abubakar, Adamu, Khan, Abdullah, Nawi, Nazri Mohd, Rehman, M. Z., Teh , Ying Wah, Chiroma , Haruna, Herawan, Tutut

    Published 2016
    “…The performances of the proposed Accelerated Particle Swarm Optimization Levenberg Marquardt (APSO_LM) algorithms compared by means of simulations on 7-Bit Parity and six UCI benchmark classification datasets. …”
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  7. 7
    Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method

    Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method by Abbaszadeh M., Soltani-Mohammadi S., Ahmed A.N.

    Published 2023
    “…Copper deposits; Deposits; Geology; Learning algorithms; Mineralogy; Static Var compensators; Support vector machines; Three dimensional computer graphics; Alteration zones; Grid search; Grid-search method; Mineralization zone; Model Selection; Particle swarm optimization algorithm; Penalty parameters; Performance; Support vector classifiers; Support vectors machine; Particle swarm optimization (PSO); accuracy assessment; algorithm; classification; computer simulation; copper; geological survey; mineral alteration; mineralization; numerical model; ore deposit; parameterization; performance assessment; porphyry; resource assessment; support vector machine; three-dimensional modeling; Iran…”
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  8. 8
    EEG signal classification using Particle Swarm Optimization (PSO) neural network for brain machine interfaces

    EEG signal classification using Particle Swarm Optimization (PSO) neural network for brain machine interfaces by Paulraj, Murugesapandian, Hema, Chengalvarayan Radhakrishnamurthy, Ramachandran, Nagarajan, Sazali, Yaacob, Abdul Hamid, Adom

    Published 2009
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  9. 9
    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
    “…This research proposed an improved CS called hybrid Accelerated Cuckoo Particle Swarm Optimization algorithm (HACPSO) with Accelerated particle Swarm Optimization (APSO) algorithm. …”
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  10. 10
    Malicious URL classification using artificial fish swarm optimization and deep learning

    Malicious URL classification using artificial fish swarm optimization and deep learning by Mustafa Hilal, Anwer, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, K. Nour, Mohamed, M. Asiri, Mashael, M. Al-Sharafi, Ali, Othman, Mahmoud, Motwakel, Abdelwahed

    Published 2023
    “…With this motivation, the current article develops an Artificial Fish Swarm Algorithm (AFSA) with Deep Learning Enabled Malicious URL Detection and Classification (AFSADL-MURLC) model. …”
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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
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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  13. 13
    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
    “…The simulation results of the MLP trained with improved algorithms were compared with that when trained with the standard BP, ABC, Global ABC and Particle Swarm Optimization algorithm. …”
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  14. 14
    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification

    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

    Published 2023
    “…The simulation results on the benchmark medical datasets revealed that the proposed SCSO-KNN approach has outperformed comparative algorithms with an average classification accuracy of 93.96 by selecting 14.2 features within 1.91 s. …”
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  15. 15
    An improved bat algorithm with artificial neural networks for classification problems

    An improved bat algorithm with artificial neural networks for classification problems by Rehman Gillani, Syed Muhammad Zubair

    Published 2016
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  16. 16
    An Educational Tool Aimed at Learning Metaheuristics

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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  17. 17
    Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers

    Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2022
    “…From the simulation results, it is suggested that TLBO and HBO perform better compared to the rest of algorithms.…”
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  18. 18
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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  19. 19
    Enhancing land cover classification in remote sensing imagery using an optimal deep learning model

    Enhancing land cover classification in remote sensing imagery using an optimal deep learning model by Motwake, Abdelwahed, Hassan Abdalla Hashim, Aisha, Obayya, Marwa, Eltahir, Majdy M.

    Published 2023
    “…The current study presents an Improved Sand Cat Swarm Optimization with Deep Learning-based Land Cover Classification (ISCSODL-LCC) approach on the RSIs. …”
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  20. 20
    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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