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  1. 1

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

    Published 2012
    “…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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    Thesis
  2. 2

    A study of density-grid based clustering algorithms on data streams by Amini, A., Saybani, M.R., Sahaf Yazdi, S.R.A.

    Published 2011
    “…In this paper we review the grid based clustering algorithms that use density-based algorithms or density concept for the clustering. …”
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    Conference or Workshop Item
  3. 3

    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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    Article
  4. 4

    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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    Conference or Workshop Item
  5. 5

    Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation by Alia, Osama Moh’d Radi

    Published 2011
    “…Second, a new dynamic HS-based fuzzy clustering algorithm (DCHS) is proposed to automatically estimate the appropriate number of clusters as well as a good fuzzy partitioning of the given dataset. …”
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    Thesis
  6. 6

    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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    Thesis
  7. 7

    MuDi-Stream: A multi density clustering algorithm for evolving data stream by Amini, A., Saboohi, H., Herawan, T., Teh, Y.W.

    Published 2016
    “…The offline phase generates the final clusters using an adapted density-based clustering algorithm. …”
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    Article
  8. 8

    An adaptive density-based method for clustering evolving data streams / Amineh Amini by Amini, Amineh

    Published 2014
    “…This study proposes a density-based algorithm for clustering evolving data streams. …”
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    Thesis
  9. 9

    An enhanced cluster head selection algorithm for routing in mobile AD-HOC network by Abdulsaheb, Ghaida Muttasher

    Published 2017
    “…The performance of ECRP algorithms was compared with other cluster based algorithms. …”
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    Thesis
  10. 10

    Adaptive firefly algorithm for hierarchical text clustering by Mohammed, Athraa Jasim

    Published 2016
    “…In this research, an adaptive hierarchical text clustering algorithm is proposed based on Firefly Algorithm. …”
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    Thesis
  11. 11

    MGR: An Information Theory Based Hierarchical Divisive Clustering Algorithm for Categorical Data by Hongwu, Qin, Ma, Xiuqin, Herawan, Tutut, Jasni, Mohamad Zain

    Published 2014
    “…This research proposes mean gain ratio (MGR), a new information theory based hierarchical divisive clustering algorithm for categorical data. …”
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    Article
  12. 12

    Image segmentation based on normalised cuts with clustering algorithm by Choong, Mei Yeen

    Published 2013
    “…With the approach applied in the normalised cuts based image segmentation, the constraint of using normalised cuts algorithm in image segmentation can be alleviated. …”
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    Thesis
  13. 13

    Clustering chemical data set using particle swarm optimization based algorithm by Triyono, Triyono

    Published 2008
    “…In this study, Particle Swarm Optimization (PSO) based clustering algorithm is exploited to optimize the results of other clustering algorithm such as K-means. …”
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  14. 14
  15. 15

    Document clustering based on firefly algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2015
    “…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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    Article
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  17. 17

    Enhancement Of Clustering Algorithm Using 3D Euclidean Distance To Improve Network Connectivity In Wireless Sensor Networks For Correlated Node Behaviours by Kalid Abdlkader Marsal Salih

    Published 2024
    “…The results based on different scenarios behaviour node show that the enhance clustering algorithm built by 3D Euclidean Distance using correlated degree provides better network performance compared with LEACH, EEC, R-HEED, PEGASIS, and LCA algorithms. …”
    thesis::doctoral thesis
  18. 18

    Evaluation of FCV and FCM clustering algorithms in cluster-based compound selection by Sinarwati, Mohamad Suhaili, Mohamad Nazim, Jambli

    Published 2011
    “…One of most used clustering method is cluster-based compound selection, which involves subdividing a set of compounds into clusters and choosing one compound or a small number of compounds from each cluster. …”
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    Article
  19. 19

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

    Published 2010
    “…There are many techniques of clustering the image. The most widely used of clustering technique is Fuzzy C-Means algorithm (FCM). …”
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    Thesis
  20. 20

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…The comparison results show that, the clusters labelled by the cluster labelling algorithm were the same as using co-spectral plot. …”
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    Thesis