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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2008.1
- 수록면
- 140 - 145 (6page)
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초록· 키워드
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Fuzzy partition is a conceptual vehicle that encapsulates data into information granules. Fuzzy equalization concerns a process of building information granules that are semantically and experimentally meaningful. A few algorithms generating fuzzy partitions with fuzzy equalization have been suggested. Simulations and experiments have showed that fuzzy partition representing more characteristics of given input distribution usually produces meaningful results. In this paper, given two points and cardinality of fuzzy partition, we prove that it is not true that there always exists a fuzzy partition with fuzzy equalization in which two of points having peaks fall on the given two points. Then, we establish an algorithm that minimizes the maximum distance between given two points and adjacent points having peaks in the partition. A numerical example is presented to show the validity of the suggested algorithm.
목차
등록된 정보가 없습니다.
참고문헌 (15)
참고문헌 신청
Au, W. H. / 2006 / A Fuzzy Approach to Partitioning Contonuous Attributes for Classification / IEEE Transactions on Systems Man and Cybernetics 18 (5) : 715 ~ 719
Foulloy, L. / 2006 / Building a Class of Fuzzy Equivalence Relations / Fuzzy Sets and Systems 157 : 1417 ~ 1437
Guillaume, S. / 2006 / Expert Guided Integration of Induced Knowledge into a Fuzzy Knowledge base / Soft Computing 10 : 773 ~ 784
Hirota, K / 1999 / Fuzzy Computing for Data Mining / Proceeding of the IEEE : 1575 ~ 1600
Pedrycz, W. / 1990 / Fuzzy Sets Framework for development of Perception Perspective / Fuzzy Sets and Systems 37 : 123 ~ 137
Foulloy, L. / 2006 / Building a Class of Fuzzy Equivalence Relations / Fuzzy Sets and Systems 157 : 1417 ~ 1437
Guillaume, S. / 2006 / Expert Guided Integration of Induced Knowledge into a Fuzzy Knowledge base / Soft Computing 10 : 773 ~ 784
Hirota, K / 1999 / Fuzzy Computing for Data Mining / Proceeding of the IEEE : 1575 ~ 1600
Pedrycz, W. / 1990 / Fuzzy Sets Framework for development of Perception Perspective / Fuzzy Sets and Systems 37 : 123 ~ 137
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