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  1. 1
    Web cluster load balancing via genetic-fuzzy based algorithm

    Web cluster load balancing via genetic-fuzzy based algorithm by Chin, Wen Cheong, Lim, Amy Hui Lan

    Published 2007
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  2. 2
    Adaptive System State Based Load Balancing For Web Application Server Cluster Of Heterogeneous Performance Nodes

    Adaptive System State Based Load Balancing For Web Application Server Cluster Of Heterogeneous Performance Nodes by Lu, Chin Mei

    Published 2013
    “…This research is to propose a new efficient DNS-based load balancing algorithms that can solve a sudden increase of demand for service requests when they are applied to a local Domain Name Service (DNS) server for Web based applications and selected services. …”
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  3. 3
    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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  4. 4
    Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi

    Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi by Yazdi, Saeed Reza Aghabozorgi Sahaf

    Published 2013
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  5. 5
    Clustering-based cloud migration strategies

    Clustering-based cloud migration strategies by Aslam, M., Rahim, L.B.A., Watada, J., Hashmani, M.

    Published 2018
    “…The k-means algorithm of the partitioning clustering method is used to analyze cloud migration strategies in this study. …”
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  6. 6
    Clustering-based cloud migration strategies

    Clustering-based cloud migration strategies by Aslam, M., Rahim, L.B.A., Watada, J., Hashmani, M.

    Published 2018
    “…The k-means algorithm of the partitioning clustering method is used to analyze cloud migration strategies in this study. …”
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  7. 7
    Handwriting recognition using webcam for data entry

    Handwriting recognition using webcam for data entry by Wong , Yoong Xiang

    Published 2014
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    Final Year Project
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  8. 8
    A new algorithm to measure relevance among Web pages

    A new algorithm to measure relevance among Web pages by Sadi, M.S., Rahman, M.M. Hafizur, Horiguchi, Susumu

    Published 2006
    “…This paper proposes a new algorithm to measure relevance among Web pages (RWP) using a hybrid method of hyperlink analysis and content analysis. …”
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  9. 9
    Research trends among new investigators at ISOQOL: a bibliometric analysis from 2019 to 2023

    Research trends among new investigators at ISOQOL: a bibliometric analysis from 2019 to 2023 by Kwon, Jae-Yung, Kaur, Manraj N., Elsman, Ellen B. M., Mehdipour, Ava, Lo, Lori Suet Hang, Ahmed Osman, Ahmed Mohamed Yehia Naguib, Herbelet, Sandrine, Ng, Carrie-Anne, van der Weijst, Lotte

    Published 2025
    “…Thematic mapping was conducted using clustering algorithms to identify established and emerging research areas. …”
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  10. 10
    Clustering ensemble learning method based on incremental genetic algorithms

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

    Published 2012
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  11. 11
    Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation

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

    Published 2011
    “…However, two main issues plague these clustering algorithms: initialization sensitivity of cluster centers and unknown number of actual clusters in the given dataset. …”
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  12. 12
    A study of density-grid based clustering algorithms on data streams

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

    Published 2011
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  13. 13
    On density-based data streams clustering algorithms: A survey

    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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  14. 14
    A review: accuracy optimization in clustering ensembles using genetic algorithms

    A review: accuracy optimization in clustering ensembles using genetic algorithms by Ghaemi, Reza, Sulaiman, Md. Nasir, Ibrahim, Hamidah, Mustapha, Norwati

    Published 2011
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  15. 15
    Fuzzy clustering algorithms and their applications to chemical datasets

    Fuzzy clustering algorithms and their applications to chemical datasets by Shah, Jehan Zeb, Salim, Naomie

    Published 2005
    “…In this work the importance of fuzzy based clustering methods is highlighted and their applications in the field of chemoinformatics, and issues involved are reviewed. …”
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  16. 16
    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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  17. 17
    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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  18. 18
    Knowledge-based genetic algorithm for multidimensional data clustering

    Knowledge-based genetic algorithm for multidimensional data clustering by Purnomo, Muhammad Ridwan Andi, Saleh, Chairul, Lagaida, R.L., Hassan, Azmi

    Published 2013
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  19. 19
    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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  20. 20
    An adaptive density-based method for clustering evolving data streams / Amineh Amini

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

    Published 2014
    “…Due to these characteristics the traditional densitybased clustering is not applicable. Recently, a number of density-based algorithms have been developed for clustering data streams. …”
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