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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Journal of Korean Institute of Intelligent Systems
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Journal DOI :
Korean Institute of Intelligent Systems
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Volume & Issues
Volume 4, Issue 3 - Sep 1994
Volume 4, Issue 2 - Jun 1994
Volume 4, Issue 1 - Mar 1994
Selecting the target year
Lee, Hyung kwang ; Oh, Gil-Rok ; Cho, Choong-Ho ;
Journal of Korean Institute of Intelligent Systems, volume 4, issue 2, 1994, Pages 3~8
In this paper, the hypergraph is fuzzified. In a hypoergraph, there are 3types of sets which can be fuzzified. According to the fuzzificatioin level, 7 types of fuzzy hypergraphs can be obtained. After defining the 7 thpes of hypergraphs, some interesting concepts are developed such as the order, size and degree of such as the order, size and degree of the fuzzy hypergraph.
On The Completeness of $ F(X, Y)
Rhie, Gil-Seob ; Sung, Yeoul-Ouk ;
Journal of Korean Institute of Intelligent Systems, volume 4, issue 2, 1994, Pages 9~12
Let X, Y be normed linear spaces, and let p
, p.sub 2/ be lower semi-continuous fuzzy norms on X, Y respectively, and have the bounded supports on X, Y respectively. In this paper, we prove that if Y is conplete, the set of all fuzzy continuous linear maps from X into Y is a fuzzy complete fuzzy normed linear space.
Traffic Flow Assessment with the Fuzziness of Drivers Driving Speed Attitude
Journal of Korean Institute of Intelligent Systems, volume 4, issue 2, 1994, Pages 13~23
This study proposed a method of accessment for traffic flow on roads based on the driver's decision making. In order to, an attempt is carried out to express driving speeds through driver's congnitive language theoretically and experimentally. Membership function is derived to express driver's congnitive language about driving speed through a fuzzy set theory and examines the applicability for speed evaluation. As a resul, the membership function of the recognized as medium by drivers almost agrees with the frequency distribution of speeds on roads constrtained at 50km/h
Multicriteria Decision-Making Mehtodology Using Fuzzy Dependence Relations and Fuzzy Measure
Journal of Korean Institute of Intelligent Systems, volume 4, issue 2, 1994, Pages 24~34
Scientific involvement in complex decision-making system, characterized by multicriteria phenomena and fuzziness inherent in the structure of information, requires suitable methods. Especially, when powerful dependent criteria are introduced and their weighted value structure is ignorant, the systems are become more complex. This paper presents a fuzzy dependenced relation model and fuzzy measure model for this kind of multicriteria decision-making. The model we propose is based on fuzzy relation and fuzzy measure in fuzzy systems theory. For the application of the model, a numdrical example is quoted.
Truncation Effects of the Fuzzy Logic Controllers
Moon, Byung-Soo ; Moon, Je-Sun ; Lee, Jongmin ;
Journal of Korean Institute of Intelligent Systems, volume 4, issue 2, 1994, Pages 35~40
Fuzzy logic controllers are often found to behave better than PI controllers. One of the major reasons for this is that the fuzzy logic inferences used can produce nonlinear type controllers. For some applicatioins, howeveer, linear fuzzy logic controllers also perofrm better than PI controllers. In this paper, we examine linear fuzzy logic controllers to show that the truncation effects of the fuzzy logic controllers make them perform much better than the PI controllers. In terms of a performance index we used, the truncation effects reduced the index value by up to 80% for examples we studied.