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  1. 1
    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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  2. 2
    The implementation of z-numbers in fuzzy clustering algorithm for wellness of chronic kidney disease patients

    The implementation of z-numbers in fuzzy clustering algorithm for wellness of chronic kidney disease patients by N. J., Mohd Jamal, Ku Muhammad Naim, Ku Khalif, Mohd Sham, Mohamad

    Published 2019
    “…By gleaning insights from the data, fuzzy clustering capable to learn from data, identify patterns and make decision with minimum human intervention. …”
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  3. 3
    Clustering for binary data sets by using genetic algorithm-incremental K-means

    Clustering for binary data sets by using genetic algorithm-incremental K-means by Saharan, S., Baragona, R., Nor, M. E., Salleh, R. M., Asrah, N. M.

    Published 2018
    “…This research was initially driven by the lack of clustering algorithms that specifically focus in binary data. …”
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  4. 4
    The new efficient and accurate attribute-oriented clustering algorithms for categorical data

    The new efficient and accurate attribute-oriented clustering algorithms for categorical data by Qin, Hongwu

    Published 2012
    “…Many algorithms for clustering categorical data have been proposed, in which attribute-oriented hierarchical divisive clustering algorithm Min-Min Roughness (MMR) has the highest efficiency among these algorithms with low clustering accuracy, conversely, genetic clustering algorithm Genetic-Average Normalized Mutual Information (G-ANMI) has the highest clustering accuracy among these algorithms with low clustering efficiency. …”
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  5. 5
    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
    “…While many algorithms for clustering categorical data have been proposed, some have low clustering accuracy while others have high computational complexity. …”
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  6. 6
    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
    “…The clusters formed revealed the capability and drawbacks of each algorithm on the data points.…”
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  7. 7
    Parallelization of noise reduction algorithm for seismic data on a beowulf cluster

    Parallelization of noise reduction algorithm for seismic data on a beowulf cluster by Aziz, I. A., Sandran, T., Haron, N. S., Hasan, M. H, Mehat, M.

    Published 2010
    “…The proposed algorithm has been implemented on an experimental Beowulf cluster which consists of 12 nodes operating on Linux Ubuntu platform. …”
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  8. 8
    Autonomous and deterministic supervised fuzzy clustering

    Autonomous and deterministic supervised fuzzy clustering by Lim, K.M., Loo, C.K., Lim, W.S.

    Published 2010
    “…The model is tested on medical diagnosis benchmark data and Westland vibration data. The results obtained show that the model that uses the global k-means clustering algorithm 1 has higher accuracy when compared to a model that uses the k-means clustering algorithm. …”
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  9. 9
    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data

    The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Siddiqui, Sumrana, Sarkar, Rashel

    Published 2024
    “…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
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  10. 10
    An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets

    An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets by Azlin, Ahmad, Rubiyah, Yusof, Nor Saradatul Akmar, Zulkifli, Mohd Najib, Ismail

    Published 2021
    “…Therefore, this proposed algorithm can be implemented in clustering other complex datasets, such as high dimensional and streaming data.…”
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  11. 11
    An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets

    An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets by Ahmad, Azlin, Yusof, Rubiyah, Zulkifli, Nor Saradatul Akma, Ismail, Mohd Najib

    Published 2021
    “…Therefore, this proposed algorithm can be implemented in clustering other complex datasets, such as high dimensional and streaming data.…”
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  12. 12
    Datasets Size: Effect on Clustering Results

    Datasets Size: Effect on Clustering Results by Raheem, Ajiboye Adeleke, Ruzaini, Abdullah Arshah, Hongwu, Qin

    Published 2013
    “…This gives a wider acceptance to data mining, being an interdisciplinary field that implements algorithm on stored data with a view to discovering hidden knowledge. …”
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  13. 13
    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 purpose of this study is to apply the K-Means algorithm to perform clustering on COVID-19 data to determine the high spread of the virus in regions in Indonesia based on the frequency of the data. …”
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  14. 14
    A new variant of black hole algorithm based on multi population and levy flight for clustering problem

    A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

    Published 2020
    “…Meta-heuristic algorithm has been successfully implemented on data clustering problems seeking a near optimal solution in terms of quality of the resultant clusters. …”
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  15. 15
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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  16. 16
    Reliability fuzzy clustering algorithm for wellness of elderly people

    Reliability fuzzy clustering algorithm for wellness of elderly people by N. J., Mohd Jamal, Ku Muhammad Naim, Ku Khalif, Mohd Sham, Mohamad

    Published 2019
    “…By gleaning insights from the data, the fuzzy clustering can learn from data, identify patterns and make decisions with minimal human intervention. …”
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  17. 17
    A novel hierarchical clustering algorithm for the analysis of 3D anthropometric data of the human head

    A novel hierarchical clustering algorithm for the analysis of 3D anthropometric data of the human head by Ellena, Thierry, Subic, Aleksandar, Mustafaa, Helmy, Yen, Pang Toh

    Published 2018
    “…A linkage criterion based on the centroid distance was implemented, while clusters were created one after another in an enhanced manner. …”
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  18. 18
    Improving on the network lifetime of clustered-based wireless sensor network using modified leach algorithm

    Improving on the network lifetime of clustered-based wireless sensor network using modified leach algorithm by Zeni, Saltihie

    Published 2012
    “…Meanwhile in LEACH, the cluster head selection was based on distributed algorithm. …”
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  19. 19
    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…The preprocessing phase utilizes Canopy clustering to expedite the initial partitioning of data points, which are subsequently refined by K-means to enhance clustering performance. …”
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  20. 20
    Big data clustering using grid computing and ant-based algorithm

    Big data clustering using grid computing and ant-based algorithm by Ku-Mahamud, Ku Ruhana

    Published 2013
    “…This paper presents a framework for big data clustering which utilizes grid technology and ant-based algorithm.…”
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