Browsing by Author "Hsiao, WH"

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A knowledge-based method for fuzzy query processing for document retrieval
(1997-01-01)
Chen, SM
;
Hsiao, WH
;
Horng, YJ
;
交大名義發表
;
資訊工程學系
This paper presents a knowledge-based method for processing fuzzy queries and weighted-fuzzy, queries for document retrieval, where fuzzy concept matrices are used for knowledge representation and the elements in a fuzzy concept matrix are represented by trapezoidal fuzzy numbers parameterized by quadruples (a,b,c,d), where 0 less than or equal to a less than or equal to b less than or equal to c less than or equal to d less than or equal to 1. Intelligent retrieval capability and flexible user's queries are consequently provided for.
A new interpolative reasoning method in sparse rule-based systems
(1998-01-01)
Hsiao, WH
;
Chen, SM
;
Lee, CH
;
資訊工程學系
;
Department of Computer Science
In [7], Yan et al. analyzed Koczy and Hirota's linear interpolative reasoning method presented in [2,3] and found that the reasoning consequences by their method sometimes become abnormal fuzzy sets. Thus, they pointed out that a new interpolative reasoning method will be needed which can guarantee that the interpolated conclusion will also be triangular-type for a triangular-type observation. In this paper, we extend the works of [2,3,7] to present a new interpolative reasoning method to deal with fuzzy reasoning in sparse rule-based systems. The proposed method can overcome the drawback of Koczy and Hirota's method described in [7]. It can guarantee that the statement "If fuzzy rules A(1) double right arrow B-1, A(2) double right arrow B-2, and the observation A* are defined by triangular membership functions, the interpolated conclusion B* will also be triangular-type" holds. (C) 1998 Elsevier Science B.V.
A new interpolative reasoning method in sparse rule-based systems
(1998-01-01)
Hsiao, WH
;
Chen, SM
;
Lee, CH
;
資訊工程學系
;
Department of Computer Science
In [7], Yan et al. analyzed Koczy and Hirota's linear interpolative reasoning method presented in [2,3] and found that the reasoning consequences by their method sometimes become abnormal fuzzy sets. Thus, they pointed out that a new interpolative reasoning method will be needed which can guarantee that the interpolated conclusion will also be triangular-type for a triangular-type observation. In this paper, we extend the works of [2,3,7] to present a new interpolative reasoning method to deal with fuzzy reasoning in sparse rule-based systems. The proposed method can overcome the drawback of Koczy and Hirota's method described in [7]. It can guarantee that the statement "If fuzzy rules A(1) double right arrow B-1, A(2) double right arrow B-2, and the observation A* are defined by triangular membership functions, the interpolated conclusion B* will also be triangular-type" holds. (C) 1998 Elsevier Science B.V.
Bidirectional approximate reasoning based on interval-valued fuzzy sets
(1997-11-01)
Chen, SM
;
Hsiao, WH
;
Jong, WT
;
交大名義發表
;
資訊工程學系
This paper proposes a bidirectional approximate reasoning method based on interval-valued fuzzy sets, where fuzzy production rules are used for knowledge representation, and the fuzzy terms appearing in the fuzzy production rules of a rule-based system are represented by interval-valued fuzzy sets. The proposed method is more flexible than the one presented in the paper by Bien and Chun [IEEE Trans. Fuzzy Systems 2 (1994) 177] due to the fact that it allows the fuzzy terms appearing in the fuzzy production rules of a rule-based system to be represented by interval-valued fuzzy sets rather than general fuzzy sets. Furthermore, because the proposed method requires only simple arithmetic operations, and because it allows bidirectional approximate reasoning, it can be executed much faster and more flexible than the single-input-single-output approximate reasoning scheme presented in the paper by Gorzalczany [Fuzzy Sets and Systems 21 (1987) 1]. (C) 1997 Elsevier Science B.V.
Bidirectional approximate reasoning for rule-based systems using interval-valued fuzzy sets
(2000-07-16)
Chen, SM
;
Hsiao, WH
;
資訊工程學系
;
Department of Computer Science
In this paper, we extend the work of Chen et al, [Fuzzy Sets and Systems 91 (1997) 339-353] to present a new method to deal with bidirectional approximate reasoning for rule-based systems based on the direction of matching between interval-valued fuzzy sets, We also use some examples to illustrate the bidirectional approximate reasoning process. Because the proposed method can perform bidirectional approximate reasoning based on the direction of matching between interval-valued fuzzy sets, it is more reasonable and more powerful than the one presented in Chen et al., Fuzzy Sets and Systems 91 (1997) 339-353. The proposed method can provide a useful way to deal with bidirectional approximate reasoning for rule-based systems using interval-valued fuzzy sets. (C) 2000 Elsevier Science B.V, All rights reserved.