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: |
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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 |
相關次數: | 點閱:135 下載:0 |
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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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