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  1. 1

    Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD) by Rashed, Alwatben Batoul, Hamdan, Hazlina, Mohd Sharef, Nurfadhlina, Sulaiman, Md Nasir, Yaakob, Razali, Abubakar, Mansir

    Published 2020
    “…The proposed method was evaluated against five clustering approaches that have succeeded in optimization that comprises of K-means Clustering, MCPSO, IMCPSO, Spectral clustering, Birch, and average-link algorithms. …”
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  2. 2

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…Two major difficulties in clustering ensemble include diversity of clustering and consensus functions. Genetic algorithms are well known methods with high ability to resolve optimization problems including clustering. …”
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    Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering by Rashed, Alwatben Batoul

    Published 2022
    “…For optimum results in performance analysis, the optimal value of the MOPSO-CD was evaluated using (ZDT), (WFG), and (DTLZ) with two or three objectives over D2MOPSO, AgMOPSO, MMOPSO, and EMOSO algorithms. …”
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  5. 5

    Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks by Han, Fengrong, Izzeldin, Ibrahim Mohamed Abdelaziz, Kamarul Hawari, Ghazali, Zhao, Yue, Li, Ning

    Published 2023
    “…It developed a novel method to determine localization coverage. The localization coverage is also added to be one evaluation metric in our study, which makes up for the lack of this evaluation indicator in most of the studies. …”
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  6. 6

    Tree-based contrast subspace mining method by Florence Sia Fui Sze

    Published 2020
    “…Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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  7. 7

    Development of committee machine models for multiple response optimization problems by Golestaneh, Seyed Jafar

    Published 2014
    “…There are several methods in two categories to solve MRO problems. The first category includes premier methods such as Response Surface Methodology (RSM) and Taguchi method and the second one includes newer methods like hybrid methods of ANNs and Genetic Algorithm (GA). …”
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  8. 8

    Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman by Azman, Alya Kauthar

    Published 2025
    “…This study applies Genetic Algorithms (GA) to optimize space distribution for test scheduling, addressing the challenge of managing multiple test sessions across distinct locations. …”
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    Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

    Published 2019
    “…Researchers have in the past few decades resorted to several methods that are inspired from complex optimization problems. …”
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  12. 12

    Dual search maximum power point algorithm based on mathematical analysis under partially-shaded conditions by Hajighorbani, Shahrooz

    Published 2016
    “…In the first group, the conventional techniques are combined with other techniques and the second group is based on the optimization methods. …”
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  13. 13

    Solving large-scale problems using multi-swarm particle swarm approach by Salih, Sinan Q., Alsewari, Abdulrahman A.

    Published 2018
    “…In the simulation part, several benchmark functions were performed with different numbers of dimensions. The proposed algorithm was tested on several test functions, with four different number of dimensions (100, 500, and 1000) it was evaluated in terms of performance efficiency and compared to standard PSO (SPSO), and mastersalve PSO algorithm. …”
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  14. 14

    Comparison of mabsa, PSO and GWO of PI-PD controller for dc motor by Nur Naajihah, Ab Rahman

    Published 2024
    “…The swarm intelligence group selected Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Modified Adaptive Bats Sonar Algorithms (MABSA) to optimize the parameters of the PI-PD controller. …”
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  15. 15

    Optimal power allocation scheme for plug-in hybrid electric vehicles using swarm intelligence techniques by Vasant, P.M., Rahman, I., Singh, B.S.M., Abdullah-Al-Wadud, M.

    Published 2016
    “…However, PSOGSA method takes much longer computational time than single methods because of incorporating two single methods in one algorithm. …”
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  16. 16

    Optimal power allocation scheme for plug-in hybrid electric vehicles using swarm intelligence techniques by Vasant, P.M., Rahman, I., Singh, B.S.M., Abdullah-Al-Wadud, M.

    Published 2016
    “…However, PSOGSA method takes much longer computational time than single methods because of incorporating two single methods in one algorithm. …”
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  17. 17

    Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L., Kwong C.F.

    Published 2023
    “…The K-Means clustering algorithm is an effective algorithm for multi-clusters that can be used in VANETs. …”
    Article
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    Comparison between reverse and traditional screening algorithms for syphilis diagnosis in Hospital Universiti Sains Malaysia by Sidek, Nurul Azira

    Published 2021
    “…Results: Out of 206 serum samples, 32 (15.53%) were diagnosed with syphilis using the reverse algorithm, but only 23 (11.17%) were diagnosed with syphilis using the traditional algorithm. …”
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    Breast cancer diagnosis through an optimization-driven multispectral gamma correction (ODMGC) by Raj A, Arul Edwin, Ahmad, Nabihah, Durai S, Ananiah

    Published 2024
    “…The algorithm was successfully implemented in MATLAB 2020a, and the classifier was developed in Jupyter Notebook using Python. …”
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  20. 20

    An evolutionary based features construction methods for data summarization approach by Rayner Alfred, Suraya Alias, Chin, Kim On

    Published 2015
    “…In other words, this research will discuss the application of genetic algorithm to optimize the feature construction process from the Coral Reefs data to generate input data for the data summarization method called Dynamic Aggregation of Relational Attributes (DARA). …”
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