• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.5
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• pp.1411-1418
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• 1996

Large scale plants are equipped with a number of the rotating machineries which ocuupy important positions in the plant system. Therefore, the most important one is a vibraiton diagnostic thchnology which can detect quickly any abnormal symptom of operating malfunction and guve operational and inspection guides adequately. A new diagnosis method is developed in this paper, in which the fuzzy set theory is introduced to diagnose the defects of ratating machinery. The selection of memgership function and the fuzzy operation model are discussed in datail here. The systme is sucessfully used for various defacts diagnosis of rotating machinery. The result indicate that realixtic application can be builtusing this approach.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.491-501
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• 2002

Case-based reasoning is emerging as a leading methodology for the application of artificial intelligence. CBR is a reasoning methodology that exploits similar experienced solutions, in the form of past cases, to solve new problems. Hybrid model achieves some convergence of the wide proliferation of credit evaluation modeling. As a result, Hybrid model showed that proposed methodology classify more accurately than any of techniques individually do. It is confirmed that proposed methodology predicts significantly better than individual techniques and the other combining methodologies. The objective of the proposed approach is to determines a set of weighting values that can best formalize the match between the input case and the previously stored cases and integrates fuzzy sit concepts into the case indexing and retrieval process. The GA is used to search for the best set of weighting values that are able to promote the association consistency among the cases. The fitness value in this study is defined as the number of old cases whose solutions match the input cases solution. In order to obtain the fitness value, many procedures have to be executed beforehand. Also this study tries to transform financial values into category ones using fuzzy logic approach fur performance of credit evaluation. Fuzzy set theory allows numerical features to be converted into fuzzy terms to simplify the matching process, and allows greater flexibility in the retrieval of candidate cases. Our proposed model is to apply an intelligent system for bankruptcy prediction.

• Journal of Korean Society for Quality Management
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• v.31 no.3
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• pp.98-113
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• 2003

Kano model distinguishes three types of customer requirements, namely, one-dimensional quality, must-be quality, and attractive quality. There are a few methods for classifying a given customer requirement into one of the Kano's quality elements. However, the existing methods have a common limitation in that they are based on Kano evaluation table. Kano evaluation table is not always effective for the classification task, and suffers from a significant information loss. This paper proposes an alternative to Kano's evaluation table and a new classification scheme based on fuzzy set concept. The proposed method is illustrated using a case study on the ADSL service.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.1
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• pp.57-71
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• 1988

Checklist method is rapid and comprehensive to evaluate in practice. Check items are commonly rated by subjective utility function; i.e., evaluator's significant judgment. Since human judgment includes fuzziness (vagueness) inherently in spite of its significance, fuzzy set theory is useful in this case. The paper illustrates a evaluation method using fuzzy checklist where check items are rated as fuzzy numbers. Pairwise comparison data is used to determine the weights of check items, since it has comparative advantage for human's fuzzy judgment. Sample of BASIC program is provided for microcomputer. When uncertainty is due to subjectivity or imprecision of data, this method can be applied to practical problems widely.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.1
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• pp.5-15
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• 1997

This paper mentions a fault tree analysis using not probability but natural language and fuzzy theory, Reliability estimate of each basic event and dependence level estimate among subsystems are expressed by linguistic terms. Analysis results are also expressed by natural language. The meaning of linguistic terms is expressed by a fuzzy set. In the presented analysis approach parametrized operations of fuzzy sets are considered so that analyst's subjectivity can be introduced into the analysis. This paper gives the Chernobyl accident as an example of the fuzzy fault tree analysis using linguistic terms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.5 no.1
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• pp.49-53
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• 1980

Since Zadeh had published the fuzzy set theory at 1965, it has been applied to many fields such as realizability of communication nets, automatic control, learning systems, switching circuits. In this paper, the method of applying a fuzzy logic to a pattern classification is studied and the difference of fuzzy logic from Boolean algebra is discussed. Classfication experiment is carried out 16 persons' photos of three families by fourty male and female observers and recognition rate 94% is obtained.

• Journal of Korea Water Resources Association
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• v.46 no.2
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• pp.171-182
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• 2013

This paper presents the application of fuzzy set theory in multi criteria decision making (MCDM). FAHP (Fuzzy Analytic Hierarchy Process) method was used to rank alternatives to find the most reasonable and efficient way of agricultural reservoir water resources assessment. 6 criteria and 10 subcriteria had been identified and compared to secure agricultural water resources. Fuzzy numbers and linguistic variables were presented to address inherently uncertain or imprecise data. Comparison analysis of decision making method was also carried out to find a way of suitable decision making and validity of FAHP was discussed.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.40-42
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• 2001

Most people have to deal with color and color problems occasionally. There are many strange things about color and color vision that most people do not notice. Even though color seems intuitive and simple it is not. In this paper, we modeled the color using fuzzy set theory. The proposed fuzzy color model is based on the Munsell color space. We defined several fuzzy color terminologies, and proposed a extended center of gravity defuzzification mthod for fuzzy color set. Finally, three distance measures between fuzzy colors were also formulated.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.10a
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• pp.192-192
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• 1998

• Proceedings of the Korean Nuclear Society Conference
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• 1999.10a
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• pp.317.2-317
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• 1999