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  1. 1
    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui

    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

    Published 2016
    “…Parallel imaging is a robust method for accelerating the data acquisition in Magnetic Resonance Imaging (MRI). …”
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  2. 2
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…The K-means algorithm requires two inputs for it to be applied onto a data set, the value K, and a proximity measure. …”
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  3. 3
    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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  4. 4
    Determination of the Best Single Imputation Algorithm for Missing Rainfall Data Treatment

    Determination of the Best Single Imputation Algorithm for Missing Rainfall Data Treatment by Saeed, Gamil Abdulraqeb Abdullah, Chuan, Zun Liang, Roslinazairimah, Zakaria, Wan Nur Syahidah, Wan Yusoff

    Published 2016
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  5. 5
    Determination of the best single imputation algorithm for missing rainfall data treatment

    Determination of the best single imputation algorithm for missing rainfall data treatment by Gamil Abdulraqeb Abdullah Saeed, Chuan, Zun Liang, Roslinazairimah Zakaria, Wan Nur Syahidah Wan Yusoff, Mohd Zuki Salleh

    Published 2016
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  6. 6
    Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting

    Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting by Ali, Noor Rasidah, Ku Mahamud, Ku Ruhana

    Published 2017
    “…Therefore, a clustering algorithm by introducing data transformation using X-means data splitting is proposed to investigate the spatial homogeneity of time series rainfall data. …”
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  7. 7
    Clustering of rainfall data using k-means algorithm

    Clustering of rainfall data using k-means algorithm by Mohd Sham, Mohamad, Yuhani, Yusof, Ku Muhammad Na’im, Ku Khalif, Mohd Khairul Bazli, Mohd Aziz

    Published 2019
    “…Clustering algorithms in data mining is the method for extracting useful information for a given data. …”
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  8. 8
    Improving the tool for analyzing Malaysia’s demographic change: data standardization analysis to form geo-demographics classification profiles using k-means algorithms

    Improving the tool for analyzing Malaysia’s demographic change: data standardization analysis to form geo-demographics classification profiles using k-means algorithms by Kamarul Ismail, Nasir Nayan, Siti Naielah Ibrahim

    Published 2016
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  9. 9
    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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  10. 10
    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
    “…Exploring the dataset features through the application of clustering algorithms is a viable means by which the conceptual description of such data can be revealed for better understanding, grouping and decision making. …”
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  11. 11
    A near-optimal centroids initialization in K-means algorithm using bees algorithm

    A near-optimal centroids initialization in K-means algorithm using bees algorithm by Mahmuddin, Massudi, Yusof, Yuhanis

    Published 2009
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  12. 12
    Integrating genetic algorithms and fuzzy c-means for anomaly detection

    Integrating genetic algorithms and fuzzy c-means for anomaly detection by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, Noor Md., Chimphlee, Siriporn, Srinoy, Surat

    Published 2005
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  13. 13
    Improved Parameterless K-Means: Auto-Generation Centroids and Distance Data Point Clusters

    Improved Parameterless K-Means: Auto-Generation Centroids and Distance Data Point Clusters by Wan Maseri, Wan Mohd, Beg, Abul Hashem, Herawan, Tutut, Noraziah, Ahmad

    Published 2011
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  14. 14
    Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks

    Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks by Mujahid Tabassum

    Published 2024
    thesis::doctoral thesis
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  15. 15
    An efficient fuzzy C-least median clustering algorithm

    An efficient fuzzy C-least median clustering algorithm by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Nizamuddin, Mohammed Khaja, Aboosalih, K C

    Published 2021
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  16. 16
    A modified π rough k-means algorithm for web page recommendation system

    A modified π rough k-means algorithm for web page recommendation system by Zidane, Khaled Ali Othman

    Published 2018
    “…Hence, this study carried out several objectives to augment the support of modified clustering algorithm. Firstly, an extended K-Means clustering algorithm (called X-Means algorithm) is proposed to filter/remove the noise from user session data to eliminate outliers or irrelevant pages. …”
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  17. 17
    Pattern discovery using k-means algorithm

    Pattern discovery using k-means algorithm by Ahmed, Almahdi Mohammed, Wan Ishak, Wan Hussain, Md Norwawi, Norita, Alkilany, Ahmed

    Published 2014
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  18. 18
    Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan

    Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan by Aznan, Muhammad Nur Syazwanie Aznan

    Published 2019
    “…Cluster analysis is one of the data mining task that are widely used in many area to extracting, grouping data with similar attribute in order to uncover the hidden pattern and meaning in the data. …”
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  19. 19
    Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm

    Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm by Mohd Sharif, Sharifah, Mohd Kusin, Faradiella, Asha’ari, Zulfa Hanan, Aris, Ahmad Zaharin

    Published 2015
    “…The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. …”
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  20. 20
    Automatic clustering of generalized regression neural network by similarity index based fuzzy c-means clustering

    Automatic clustering of generalized regression neural network by similarity index based fuzzy c-means clustering by Husain, Hafizah, Khalid, Marzuki, Yusof, Rubiyah

    Published 2004
    “…Similar data then undergoes fuzzy c-means iterative process to determine their cluster centers. …”
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