Search Results - (( _ application clustering algorithm ) OR ( its applications window algorithm ))

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    Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

    Published 2011
    “…Nowadays, in the grid community, distributed and clustering system, a lot of work has been focused on providing efficient and safe replication management services through designing of algorithms and systems. …”
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    Thesis
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    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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    Thesis
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    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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    Thesis
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    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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    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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    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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    Thesis
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    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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    Article
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