臺灣博碩士論文加值系統

雖然許多衡量直觀模糊集間距離、相似度、非相似度於關聯度的方法已相繼被提出，卻鮮見有基於信息觀點比較兩模糊集的研究。本研究植基于直觀模糊集，由信息理論的角度探討兩模糊集的差異性。另外，我們除引入信息概念外，並修正Vlachos & Sergiadis (2007)所提出非統計性熵值法(cross-entropy)，加入猶豫度(hesitation)的信息後並導出相關數理推演，修正為考量所有信息的改良式熵值法(improved cross-entropy)；最後並提出等實例驗證其可行性與效果。

The thesis addresses the issue of information-theoretic discrimination measures for intuitionistic fuzzy sets (IFSs). Although many measures of distance, similarity, dissimilarity, and correlation between IFSs have been proposed, there is no reference regarding information-driven measures used for comparison between sets. In this work, we introduce the concepts of discrimination information and cross-entropy in the intuitionistic fuzzy sets and improve non-probabilistic entropy proposed by Vlachos & Sergiadis (2007) for IFSs. Based on this entropy measure, we add information of hesitation and reveal an intuitive and mathematical connection between the notions of entropy for IFSs in terms of fuzziness and intuitionism. Finally, we demonstrate the applications of the proposed discrimination information measure for pattern recognition, medical diagnosis, and bacteria detection.

Content
Abstract
ContentList of Figures
List of Tables
CHAPTER 1 INTRODUCTION 1
1.1 Background 1
1.2 Motivation 1
1.3 Workflow 2
CHAPTER 2 RELATED WORK 4
2.1 Applications on Intuitionistic Fuzzy Sets 4
2.1.1 Pattern Recognition 5
2.1.2 Medical Diagnose 8
2.2 Entropy Measure 10
2.2.1 Fuzzy Entropy 10
2.2.2 Iuntuitionistic Fuzzy Entropy 13
2.2.3 Vague Entropy 13
2.3 Elements of Intuitionistic Fuzzy Sets 15
2.4 Intuitionistic Fuzzy Entropy Measure 18
CHAPTER 3 METHODOLOGY 28
3.1 Discrimination Measure by Cross-Entropy 28
3.2 Improved Cross-Entropy Measure 34
3.3 Enhanced Procedure on Ranking 36
3.3.1 Case Study 36
3.3.2 Enhanced Process on Ranking Discrimination 38
CHAPTER 4 ILLUSTRATED EXAMPLES 42
4.1 Medical Diagnosis 42
4.2 Bacteria Clustering 45
CHAPTER 5 CONCLUSION & FUTURE RESEARCH 51
5.1 Conclusion 51
5.2 Future Research 51
References 53

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