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  1. 1
    Enhanced weight-based clustering algorithm to provide reliable delivery for VANET safety applications

    Enhanced weight-based clustering algorithm to provide reliable delivery for VANET safety applications by Bello Tambawal, Abubakar, Noor, Rafidah Md, Salleh, Rosli, Chembe, Christopher, Oche, Michael

    Published 2019
    “…This has led to unstable clusters which could affect the timely delivery of safety applications. …”
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  2. 2
    An Evolutionary Stream Clustering Technique for Outlier Detection

    An Evolutionary Stream Clustering Technique for Outlier Detection by Supardi, N.A., Abdulkadir, S.J., Aziz, N.

    Published 2020
    “…Generally, it does not require the number of clusters in advance. Most of the traditional density-based clustering is not applicable in data streams due to its own characteristics. …”
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  3. 3
    A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm

    A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm by Alomoush W., Alrosan A., Norwawi N., Alomari Y., Albashish D., Almomani A., Alqahtani M.

    Published 2024
    journal::journal article
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  4. 4
    Backhaul load and performance optimality of partial joint processing schemes in LTE-A networks

    Backhaul load and performance optimality of partial joint processing schemes in LTE-A networks by Kousha, Mohammad

    Published 2014
    “…All these achieved because the proposed algorithm targets those users located at the cluster borders who more likely cause rank deficiency. …”
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  5. 5
    Data clustering using the bees algorithm

    Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

    Published 2007
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  6. 6
    A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds

    A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds by Salim, Naomie, Shah, J. Z.

    Published 2007
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  7. 7
    Enhancement Of Clustering Algorithm Using 3D Euclidean Distance To Improve Network Connectivity In Wireless Sensor Networks For Correlated Node Behaviours

    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
    thesis::doctoral thesis
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  8. 8
    Modified ACS centroid memory for data clustering

    Modified ACS centroid memory for data clustering by Jabbar, Ayad Mohammed, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2019
    “…A comparison of the performance of several common clustering algorithms using real-world data sets shows that the accuracy of the proposed algorithm surpasses those of its counterparts.…”
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  9. 9
    On some methods of feature engineering useful for craniodental morphometrics of rats, shrews and kangaroos / Aneesha Pillay Balachandran Pillay

    On some methods of feature engineering useful for craniodental morphometrics of rats, shrews and kangaroos / Aneesha Pillay Balachandran Pillay by Aneesha Pillay , Balachandran Pillay

    Published 2024
    “…Functional data geometric morphometrics (FDGM) for 2D landmark data is introduced and its performance is compared with the classical GM method. …”
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  10. 10
    An improved ACS algorithm for data clustering

    An improved ACS algorithm for data clustering by Mohammed Jabbar, Ayad, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2020
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  11. 11
    A partition based feature selection approach for mixed data clustering / Ashish Dutt

    A partition based feature selection approach for mixed data clustering / Ashish Dutt by Ashish , Dutt

    Published 2020
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  12. 12
    Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation

    Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation by Tan , Khang Siang

    Published 2011
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  13. 13
    Max-D clustering K-means algorithm for Autogeneration of Centroids and Distance of Data Points Cluster

    Max-D clustering K-means algorithm for Autogeneration of Centroids and Distance of Data Points Cluster by Wan Maseri, Wan Mohd, Beg, Abul Hashem, Tutut, Herawan, K., F.Rabbi

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  14. 14
    Clustering chemical data set using particle swarm optimization based algorithm

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

    Published 2008
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  15. 15
    MGR: An Information Theory Based Hierarchical Divisive Clustering Algorithm for Categorical Data

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

    Published 2014
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  16. 16
    Integrated bisect K-means and firefly algorithm for hierarchical text clustering

    Integrated bisect K-means and firefly algorithm for hierarchical text clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2016
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  17. 17
    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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  18. 18
    Hybrid Henry gas solubility optimization algorithm with dynamic cluster-to-algorithm mapping

    Hybrid Henry gas solubility optimization algorithm with dynamic cluster-to-algorithm mapping by Kamal Z., Zamli, Kader, Md. Abdul, Azad, Saiful, Ahmed, Bestoun S.

    Published 2021
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  19. 19
    Clustering of Chemical Compounds using Unsupervised Neural Networks Algorithms: a comparison

    Clustering of Chemical Compounds using Unsupervised Neural Networks Algorithms: a comparison by Zeb Shah, Jehan, Salim, Naomie

    Published 2006
    “…In this work the applications of a number of self-organizing map (SOM) neural network algorithms to the clustering of chemical datasets are investigated. …”
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  20. 20
    Clustering of chemical compounds using unsupervised neural networks algorithms : a comparison

    Clustering of chemical compounds using unsupervised neural networks algorithms : a comparison by Zeb Shah, Jehan, Salim, Naomie

    Published 2006
    “…In this work the applications of a number of self-organizing map (SOM) neural network algorithms to the clustering of chemical datasets are investigated. …”
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