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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/95879

    Title: 灰聚類演算法
    Other Titles: The Grey Clustering Algorithm
    Authors: 翁慶昌;賴宏仁
    Contributors: 淡江大學電機工程學系
    Keywords: 灰色關聯分析;集群分析;門檻值;集群演算法;Grey Relational Analysis;Clustering Analysis;Threshold Value;Clustering Algorithm
    Date: 2000-11
    Issue Date: 2014-02-13 11:15:17 (UTC+8)
    Abstract: 本文提出一個以資料間的灰關聯分析為基礎的資料聚類方法。由資料間的灰關聯分析結果,我們可以經由一個閥值的設定來判斷資料與資料間的相似關係,再利用這個相似度的測量結果將資料分類。由於閥值的決定關係到資料聚類的結果,在本文中提出一個測量效能的方法來協助選擇適當的閥值。此一具有自動選擇參數的灰聚類演算法由於不需做任何人為的設定,即可以將資料自動聚類,為一非監督式的聚類方法。本文最後會利用幾個例子來說明灰聚類演算法的資料聚類結果。
    A data clustering algorithm based on the grey relational analysis ofdata is proposed. From the result of the grey relational analysis, wecan determine the similarity between data by setting a properthreshold value, and the similarity measurement can apply to dataclustering. Since the determination of the threshold value willdirectly affect the result of the clustering, we address a performancemeasurement to select a suitable threshold value. The grey clusteringalgorithm need not a priori setting of parameter, and can clusteringthe data directly. Some examples of data clustering are utilized toillustrate the effective of this algorithm.
    Relation: 2000年灰色系統理論與應用研討會論文集,頁277-284
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Proceeding

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