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研究生: 林小惠
論文名稱: 在直觀模糊關係上的分類
Fuzzy Clustering Algorithm on Intuition Fuzzy Relations
指導教授: 洪文良
口試委員:
學位類別: 碩士
Master
系所名稱:
論文出版年: 2003
畢業學年度: 91
語文別: 中文
論文頁數: 29
中文關鍵詞: 群集分析演算法群集分析演算法鄰近關係相似關係max-t和min-s遞移性max-t和min-s合成n步驟過程
外文關鍵詞: Cluster algorithm, Intuitionistic fuzzy sets, Proximity relation, Similarity relation, max-t and min-s transitivity, max-t and min-s composition, max-t and min-s composition
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  • Tamura等人(1978)提出max-min合成(compositions)的n步驟過程,並推廣至max-t合成;後來Yang和Shih(2001)提出max-Δ合成的n步驟過程,證明max-Δ合成是較佳的。本文推廣Tamura(1978)等人及Yang和Shih(2001)的 n步驟過程,以及結合Atanassov(1989)的觀點,將max-t和min-s合成建立在直觀模糊集合(intuitionistic fuzzy set)上。n步驟過程是由一鄰近關係矩陣,經過max-t和min-s合成,而得到具有遞移性的相似關係矩陣,再進行分群,進而得到更精緻的分群結果。abe
    Tamura et al. (1978) constructed an n-step procedure using max-min composition of fuzzy relations and extended to all types of max-t compositions. Yang and Shih (2001) proposed an n-step procedure using max-Δcomposition and proved that max-Δcompositions is better. Here, the n-step procedure is extended to max-t and min-s compositions from Tamura’s (1978) and Yang’s (2001) n-step procedures and it is established on Atanassov’s (1989) point of view-intuitionistic fuzzy sets. Then a clustering algorithm on intuition fuzzy relation is created for the max-t and min-s similarity-relation matrix. A max-Δand min-Δsimilarity- relation matrix with transitivity is obtained by beginning with a proximity-relation matrix based on the n-stpe procedure.tc
    第一章 緒論………………………………………………………….1 第二章 n步驟過程…………………………………………………..4
    2.1 模糊關係及直觀模糊關係……………………………..4
    2.2遞移性…………………………………………………...5
    2.2.1 max-t遞移性…………………………………......5
    2.2.2 min-s遞移性……………………………………...7
    2.2.3 IFR上的max-t遞移性和min-s遞移性………...8
    2.3 max-t和min-s與n步驟過程…………………………..10
    第三章 群集分析演算法…………………………..…………………17
    第四章 結論…………………………………………………….……26
    參考文獻……………………………………………………….………27
    表目錄
    表1、max-min和min-max合成之 結果分析…………….23
    表2、max-Δ和min-Δ合成之 結果分析…………………24
    圖1、max-min和min-max合成之 分析…………………..23
    圖2、max-Δ和min-Δ合成之 分析………………………24


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