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  1. 1
    Cluster validity of the fuzzy C-means algorithm in mammographic image using adaptive cluster & partition entropy indexes / Azwani Aziz

    Cluster validity of the fuzzy C-means algorithm in mammographic image using adaptive cluster & partition entropy indexes / Azwani Aziz by Aziz, Azwani

    Published 2010
    “…This problem can be solved by cluster validity index. Cluster validity index is needed to find the suitable number of cluster, c in any fuzzy clustering algorithm. …”
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  2. 2
    A New Unsupervised Validation Index Model Suitable for Energy-Efficient Clustering Techniques in VANET

    A New Unsupervised Validation Index Model Suitable for Energy-Efficient Clustering Techniques in VANET by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L.

    Published 2024
    “…Clustering evaluation techniques are important to check the clustering algorithm quality. …”
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  3. 3
    Efficient genetic partitioning-around-medoid algorithm for clustering

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
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  4. 4
    On density-based data streams clustering algorithms: A survey

    On density-based data streams clustering algorithms: A survey by Teh, Y.W.

    Published 2017
    “…Recently, a lot of density-based clustering algorithms are extended for data streams. …”
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  5. 5
    Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms

    Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms by Raheem, Ajiboye Adeleke, Hauwau, Isah-Kebbe, O., Oladele Tinuke

    Published 2014
    “…Some clustering algorithms, especially those that are partitioned-based, clusters any data presented to them even if similar features do not present. …”
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  6. 6
    Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.]

    Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.] by Pusadan, Mohammad Yazdi, Rabbani, Mohammad Abied, Ardiansyah, Rizka, Ngemba, Hajra Rasmita

    Published 2023
    “…The process of determining the performance of the cluster is continued based on the internal validity test based on the silhouette index. …”
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  7. 7
    Biological-based semi-supervised clustering algorithm to improve gene function prediction

    Biological-based semi-supervised clustering algorithm to improve gene function prediction by Kasim, Shahreen, Deris, Safaai, M. Othman, Razib, Hashim, Rathiah

    Published 2011
    “…We tested our new computational framework for semi-supervised clustering of yeast gene expression data based onmultiple functional annotation databases. …”
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  8. 8
    Fuzzy clustering algorithms and their applications to chemical datasets

    Fuzzy clustering algorithms and their applications to chemical datasets by Shah, Jehan Zeb, Salim, Naomie

    Published 2005
    “…In this paper a number of fuzzy clustering approaches like fuzzy c-mean, Gustafson and Kessel , Gath and Geva, fuzzy c-varieties, adaptive fuzzy , fuzzy based c-shell algorithms and some other aspects of fuzzy clustering are discussed.…”
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  9. 9
    Optimized clustering with modified K-means algorithm

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Besides, some real data sets were examined to validate the proposed algorithm. Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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  10. 10
    Statistical performance of agglomerative hierarchical clustering technique via pairing of correlation-based distances and linkage methods

    Statistical performance of agglomerative hierarchical clustering technique via pairing of correlation-based distances and linkage methods by Nurshaziana, Mohamad Shamsuri

    Published 2025
    “…The simulation study was conducted under various data conditions; number of variables, sample sizes, percentages of outliers, and data distribution to measure the performance using Cophenetic Correlation Coefficient (CCC). To validate the clustering model on real data, the Spearman-average algorithm was applied to cluster Juru river basin data based on five water quality parameters. …”
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  11. 11
    Social media mining: a genetic based multiobjective clustering approach to topic modelling

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

    Published 2021
    “…This paper investigates the effects of using a multiobjective genetic algorithm (MOGA) based clustering technique to cluster texts for topic extraction which is designed based on the structure and purity of the clusters in order to determine the optimal initial centroids and the number of clusters, k. …”
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  12. 12
    Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream

    Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream by Abdulateef, Alaa Fareed

    Published 2023
    “…The AGMB algorithm is built upon three algorithms: 1) Grid-Multi-Buffer Stream Clustering (GMBSC), 2) Cautious Grid-Multi-Buffer Stream Clustering (C-GMBSC) and 3) Adaptive-Grid-Multi-Buffer Stream Clustering (A-GMBSC). …”
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  13. 13
    Social media mining: a genetic based multiobjective clustering approach to topic modelling

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

    Published 2021
    “…This paper investigates the effects of using a multiobjective genetic algorithm (MOGA) based clustering technique to cluster texts for topic extraction which is designed based on the structure and purity of the clusters in order to determine the optimal initial centroids and the number of clusters, k. …”
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  14. 14
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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  15. 15
    A Hybrid K-Means Hierarchical Algorithm for Natural Disaster Mitigation Clustering

    A Hybrid K-Means Hierarchical Algorithm for Natural Disaster Mitigation Clustering by Prasetyadi, Abdurrakhman, Nugroho, Budi, Tohari, Adrin

    Published 2022
    “…Based on the validation from experts, 67 districts/cities (82.7%) fell into Cluster 1 (low anticipation), nine districts/cities (11.1%) were classified into Cluster 2 (medium), and the remaining five districts/cities (6.2%) were categorized in Cluster 3 (high anticipation). …”
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  16. 16
    Effective gene selection techniques for classification of gene expression data

    Effective gene selection techniques for classification of gene expression data by Yeo, Lee Chin

    Published 2005
    “…The selected subset of genes is then be used to train the classifiers for constructing rules for future tissue classification problem. Various k-means clustering algorithms and model-based clustering algorithms are proposed to group the genes. …”
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  17. 17
    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
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  18. 18
    Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering

    Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering by Hengda, Wang, Mohamad Mohsin, Mohamad Farhan, Mohd Pozi, Muhammad Syafiq

    Published 2024
    “…The fuzzy C-ordered-means clustering (FCOM) is a fuzzy clustering algorithm that enhances robustness and clustering accuracy through the ordered mechanism based on fuzzy C-means (FCM). …”
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  19. 19
    Unequal clustering by improved particle swarm optimization in wireless sensor network

    Unequal clustering by improved particle swarm optimization in wireless sensor network by Salehian, Solmaz, K. Subramaniam, Shamala

    Published 2015
    “…The performance of the adopted IPSO algorithm are validated by Numerical experiments in conventional background, however it has not been deployed in cluster-based WSNs which is done by this research. …”
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  20. 20
    A hybrid approach for personalized news recommendation with ordered clustering algorithm, rich user and news metadata

    A hybrid approach for personalized news recommendation with ordered clustering algorithm, rich user and news metadata by Darvishy, Asghar

    Published 2019
    “…However, the existing clustering algorithms do not take into consideration the news nature in clustering the news items. …”
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