| 研究生: |
邱智煇 Chih-Hui Chiu |
|---|---|
| 論文名稱: |
模糊集合之模糊度探討 The study of fuzziness for fuzzy sets |
| 指導教授: |
王文俊
Wen-June Wang |
| 口試委員: | |
| 學位類別: |
博士 Doctor |
| 系所名稱: |
資訊電機學院 - 電機工程學系 Department of Electrical Engineering |
| 畢業學年度: | 88 |
| 語文別: | 中文 |
| 論文頁數: | 65 |
| 中文關鍵詞: | 熵 、模糊數學 、模糊理論 |
| 外文關鍵詞: | Entropy, Fuzzy Arithmetic Operation, Fuzzy Theory |
| 相關次數: | 點閱:11 下載:0 |
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本論文探討的主題包括模糊集合(Fuzzy set)之模糊性(Fuzziness)研究、模糊數(Fuzzy number)之次序(Lattice)問題及模糊系統的穩定性(Stability of fuzzy system)研究。
首先,第二章提及如何利用熵(Entropy)來量測一個模糊集合的模糊程度,進一步討論到熵的一些特性。另外亦提到資訊量(Information energy)的觀念,並研究熵和資訊量之間的關係。除此之外,第三章和第四章中所提之模糊集合經模糊數學運算(Arithmetic operation)或經擴充定理(Extension Principle)之後熵的變化亦是討論的重點。本論文提出幾個簡單的公式來求得運算後所得之模糊集合的熵值。接著,本論文第五章還提出一些簡單的方法來求熵值,利用這些方法我們不須做積分運算便可容易地得到一個模糊集合的熵值。
另外,本論文對於模糊數次序的問題亦有所探討,並提出一速算法來取代傳統複雜的方法。
最後,模糊系統穩定性的問題在附錄中被討論。
In this dissertation, fuzzy sets'' fuzziness is our main study topic. By the way, the lattice of fuzzy numbers and the stability of fuzzy systems are also discussed.
In Chapter 2, we investigate the entropy relationship between two same type of fuzzy sets and study some properties of the information energy. Then, the relationship between the information energy and the entropy of a fuzzy set is derived. Chapter 3 and Chapter 4 consider the entropy change of fuzzy numbers through arithmetic operations and function mapping. Several simple formulas to get the entropy value for the fuzzy numbers'' sum and for the extension principle are proposed respectively. Chapter 5 proposes an new idea called "entropy unit" to get any fuzzy set''s entropy value easily and quickly.
Moreover, Chapter 6 try to simplify the operations of MIN and MAX of fuzzy numbers such that the operations of MIN and MAX can be implemented easily and quickly.
[1]R. Ambrosio and G. B. Martini, Maximum and minimum between fuzzy symbols in non-interactive and weakly non-interactive situations, Fuzzy Sets and Systems 12 (1984) 27-35.
[2]J. C. Bezdek, Analysis of fuzzy information, CRC Press, Boca Raton, 1987.
[3]Y. H. Chen and W. J. Wang, Fuzzy entropy management via scaling, elevation, and saturation, Fuzzy Sets and Systems 95 (1998) 173-178.
[4]D. Dubois and H. Prade, Fuzzy sets and systems: theory and applications, New York : Academic Press, 1980.
[4]D. Dubois and H. Prade, Fuzzy sets and systems: theory and applications, New York : Academic Press, 1980.
[6]D. Dumitrescu, Entropy of a fuzzy process, Fuzzy Sets and System 55 (1993) 169-177.
[7]D. Dumitrescu, Entropy of fuzzy dynamical systems, Fuzzy Sets and System 70 (1995) 45-57.
[8]D. Dumitrescu, A definition of an information energy in fuzzy sets theory, Studia Univ. Babes-bolyai Math. 22 (1977) 57-59.
[9]A. De Luca and S. Termini, A definition of non-probabilistic entropy in the setting of fuzzy sets theory, Information & Control 20 (1972) 301-312.
[10]T. Geerts, A note on lattices of euclidean subspaces, Automatica Vol 31, No. 2, pp.345-346, 1995.
[11]J. -S. R. Jang, C. -T, Sun and E. Mizutani, Neuro-Fuzzy and Soft Computing (Prentice-Hall, Inc., Upper Saddle River, New Jersey, 1997).
[12]A. Kaufmann, Introduction to the Theory of Fuzzy Subsets (Academic Press, New York, 1975).
[13]J. G. Kim and S. J. Cho, Structure of a lattice of fuzzy subgroups, Fuzzy Sets and Systems 89 (1997) 263-266.
[14]A. Kaufmann and M. M. Gupta, Introduction to Fuzzy Arithemetic Theory and Applications, (Van Nostrand Reinhold, 1991).
[15]G. J. Klir and B. Yuan, Fuzzy Sets and Fuzzy Logic Theory and Applications, (Prentic Hall PTR, NJ 07458, 1995).
[16]X. Liu, The least upper bound of content for realizable matrices on lattice [0,1],Fuzzy Sets and Systems 80 (1996) 257-259.
[17]M. Mares, Computation over fuzzy quantities, CRC Press, Boca Raton, 1994.
[18]D. L. Mon, C. H. Cheng and J. C. Lin, Evaluating weapon system using fuzzy analytic hierarchy process based on entropy weight, Fuzzy Sets and System 62 (1994) 127-134.
[19]L. Pardo, Information energy of a fuzzy event and a partition of fuzzy events, IEEE Trans. Systems, Man and Cybernet, Vol. SMC-15, No. 1 (1985) 139-144.
[19]L. Pardo, Information energy of a fuzzy event and a partition of fuzzy events, IEEE Trans. Systems, Man and Cybernet, Vol. SMC-15, No. 1 (1985) 139-144.
[21]W. Pedrycz, Why triangular membership function, Fuzzy Sets and Systems 64 (1994) 21-30.
[22]T. Terano, K. Asai and M. Sugeno, Fuzzy Systems Theorey and Its Applications (Academic Press. 1992).
[23]W. J. Wang and C. H. Chiu, Entropy variation on the fuzzy numbers with arithmetic operation, Fuzzy Sets and Systems 103 (1999) 443-455.
[24]W. J. Wang and C. H. Chiu, The entropy change of fuzzy numbers with arithmetic operations, Fuzzy Sets and Systems 111 (1999) 357-366.
[25]W. J. Wang and C. H. Chiu, The entropy change in extension principle, Fuzzy Sets and Systems 103 (1999) 153-162.
[26]L. Xuecheng, Entropy, distance measure and similarity measure of fuzzy sets and their relations, Fuzzy Sets and System 52 (1992) 305-318.
[27]R .R. Yager, On the measure of fuzziness and negation, Part I: membership in unit interval, Internat. J. General Systems 5 (1979) 221-229.
[28]C. Yu, Correlation of fuzzy numbers, Fuzzy Sets and Systems 55 (1993) 303-307.
[29]H. -J. Zimmermann, Fuzzy Set Theory and Its Applications (Kluwer-Nijhoff,Boston-Dordrecht-Lancaster,1985).
[30]K. L. Zhang and K. Hirota, On fuzzy number lattice , Fuzzy Sets and Systems 92 (1997) 113-122.