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  1. 1
    Using a novel algorithm in ultrasound images to detect renal stones

    Using a novel algorithm in ultrasound images to detect renal stones by Sania Eskandari, Saeed Meshgini, Ali Farzamnia

    Published 2021
    “…As for the Fuzzy C-means algorithm, we report those values: 99.87, 80.59, 53.17%, and the average computation time is 346.29 s. …”
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  2. 2
    Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid

    Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid by Lorpunmanee, Siriluck, Md Sap, Mohd Noor, Abdullah, Abdul Hanan

    Published 2006
    “…In this paper, we combine Fuzzy C-Mean and Genetic Algorithms which are popular algorithms, the Grid can be used for scheduling. …”
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  3. 3
    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 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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  4. 4
    Comparison of performance and computational complexity of nonlinear active noise control algorithms

    Comparison of performance and computational complexity of nonlinear active noise control algorithms by Sahib, Mouayad A., Raja Ahmad, Raja Mohd Kamil

    Published 2011
    “…However, the relative performance and computational complexities of these algorithm in comparison to FXLMS algorithm have not been carefully studied. …”
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  5. 5
    A static jobs scheduling for independent jobs in Grid Environment by using Fuzzy C-Mean and Genetic algorithms

    A static jobs scheduling for independent jobs in Grid Environment by using Fuzzy C-Mean and Genetic algorithms by Lorpunmanee, Siriluck, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan, Srinoy, Surat

    Published 2006
    “…We present a static job scheduling algorithm by using Fuzzy C-Mean and Genetic algorithms. …”
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  6. 6
    Efficient genetic partitioning-around-medoid algorithm for clustering

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

    Published 2019
    “…One of the main issues in genetic k-means based algorithms is their sensitivity to outliers and unevenly distributed clusters due to the mean compromised computations. …”
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  7. 7
    MaxD K-Means: A clustering algorithm for auto-generation of centroids and distance of data points in clusters

    MaxD K-Means: A clustering algorithm for auto-generation of centroids and distance of data points in clusters by Wan Maseri, Wan Mohd, Beg, Abul Hashem, Herawan, Tutut, Fazley Rabbi, Khandakar

    Published 2012
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  8. 8
    Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering

    Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering by Rahmah, Mokhtar, Raza, Muhammad Ahsan, Fauziah, Zainuddin, Nor Azhar, Ahmad, Raza, Muhammad Fahad, Raza, Binish

    Published 2021
    “…In this paper, we have compared the performance of K-Mean and XMean clustering algorithms using two datasets of student enrollment in higher education institutions. …”
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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
    “…In order to obtain the optimum number of clusters and at the same time could deal with correlated variables in huge data, modified k-means algorithm was proposed. The proposed algorithm utilised a distance measure to compute the between groups’ separation to accelerate the process of identifying an optimal number of clusters using k-means. …”
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  10. 10
    Malaria parasites segmentation in red blood cells images using mean-shift and median-cut

    Malaria parasites segmentation in red blood cells images using mean-shift and median-cut by Tn. Muda, Tn. Zalizam, A Salam, Rosalina

    Published 2010
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  11. 11
    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
    “…Genetic Algorithms (GA) to the problem of selection of optimized feature subsets to reduce the error caused by using land-selected features. …”
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  12. 12
    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

    Published 2009
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  13. 13
    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

    Published 2008
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  14. 14
    Marketplace product recommendation using collaborative filter / Muhammad Alif Fauzan Ismail

    Marketplace product recommendation using collaborative filter / Muhammad Alif Fauzan Ismail by Ismail, Muhammad Alif Fauzan

    Published 2021
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  15. 15
    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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  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
    Checkpointing in selected most fitted resource task scheduling in grid computing

    Checkpointing in selected most fitted resource task scheduling in grid computing by Latip, Rohaya, Lew, Wai San, Chanchary, Fara Habib

    Published 2012
    “…We applied the algorithm of MeanFailure with Checkpointing in the SMF algorithm and named it MeanFailureCP-SMF. …”
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  18. 18
    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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  19. 19
    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
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  20. 20
    Improved clustering using robust and classical principal component

    Improved clustering using robust and classical principal component by Hassn, Ahmed Kadom

    Published 2017
    “…The classical k-means algorithm and the k-means by PCA algorithm are very sensitive to the presence of outlier. …”
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