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    ASIA unversity > 資訊學院 > 資訊工程學系 > 期刊論文 >  Item 310904400/18438

    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/18438

    Title: A New Density-Based Scheme for Clustering Based on Genetic Algorithm
    Authors: 林智揚;Lin, Chih-Yang
    Contributors: 資訊工程學系
    Keywords: Clustering algorithms;genetic algorithms;DBSCAN
    Date: 2005
    Issue Date: 2012-11-26 13:53:34 (UTC+8)
    Abstract: Density-based clustering can identify arbitrary data shapes and noises. Achieving good clustering performance necessitates regulating the appropriate parameters in the density-based clustering. To select suitable parameters successfully, this study proposes an interactive idea called GADAC to choose suitable parameters and accept the diverse radii for clustering. Adopting the diverse radii is the original idea employed to the density-based clustering, where the radii can be adjusted by the genetic algorithmto cover the clusters more accurately. Experimental results demonstrate that the noise and all clusters in any data shapes can be identified precisely in the proposed scheme. Additionally, the shape covering in the proposed scheme is more accurate than that in DBSCAN.
    Relation: Fundamenta Informaticae
    Appears in Collections:[資訊工程學系] 期刊論文

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