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Autor:
Xizhao Wang, Suyun Zhao
Publikováno v:
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).
In order to improve the reasoning ability of rough sets, this paper generalizes the Pawlark's rough set model to the fuzzy environment. Fuzzy indiscernibility relation is proposed in this paper to replace Pawlark's underlining indiscernibility relati
Publikováno v:
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).
In this paper we discuss the basic relationship between the ordinal fuzzy set theory and the rough set theory. A new generalized definition of lower and upper approximations and a method for detecting the ordinal definable is put forward.
Publikováno v:
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).
In this paper a fuzzy method for data fusion is proposed. First, the admission function is defined to measure the consistency of the sensors' information. Simultaneously, the fuzzy measure is adopted for measuring the reliability of the sensors group
Publikováno v:
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).
The present paper provides first the concept and different tasks of case-base maintenance. Then the use of some soft computing techniques, including fuzzy sets, rough sets and fuzzy integral, is described in maintaining the case base completeness. Fr
Publikováno v:
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).
This paper proposes a fuzzy classification system and its application in tobacco leaves grading. The mathematic description of the fuzzy classification model is given out, and we discuss the fuzzy membership function to calculate the membership of th
Autor:
Jian-Jiang Lu, Bao-Wen Xu
Publikováno v:
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).
Quantitative attributes are partitioned into several fuzzy sets by fuzzy c-means algorithm, and the search technology of a priori algorithm is improved to discover interesting fuzzy association rules. Then, the prediction method with the variable thr
Autor:
Li-Jun Xu, Kang-Lin Xie
Publikováno v:
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).
The paper presents a new approach of mining fuzzy association rules. Most existing methods need to perform multiple scans of the database to get frequent itemsets and work poorly if the data are densely populated and duplicated. Our approach only nee
Autor:
Sheng-Hua Wang, Yan-Kui Liu
Publikováno v:
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).
In this paper, a new class of fuzzy programming problems, called fuzzy two-stage programming, is first presented. Then some basic properties of the two-stage model are discussed. In addition, three solution concepts, wait-and-see solution, here-and-n
Autor:
Qiang-Yuan Yu, Dayou Liu
Publikováno v:
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).
In the applications of spatial information systems, the attribute data of sample points vary in an interval range rather than staying as precise values. The modeling, analyzing and reasoning of these kinds of data are getting more imperative and thus
Autor:
Wu-Neng Zhou
Publikováno v:
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).
In this paper, the concepts of fuzzy semiregular set and fuzzy semiregular compactness are introduced. In terms of net, filter and fuzzy semiregularization, the characterizations of fuzzy semiregular compact sets are characterized. Furthermore, many