• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1999.11a
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• pp.119-124
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• 1999

A selection methodology of liquid levelmeters, especially, level sensors in non-nuclear category, to be installed in nuclear energy facilities is developed using linguistic fuzzy approaches such as fully-linguistic and semi-linguistic methods. Depending on defuzzification techniques, the linguistic fuzzy methodology leads to either linguistic (exactly, fully-linguistic) or cardinal (i.e., semi-linguistic) evaluation. For the linguistic method, for each alternative, fuzzy preference index is converted to linguistic utility value by means of a similarity measure determining the degree of similarity between fuzzy index and linguistic ratings. For the cardinal method, the index is translated to cardinal overall utility value. According to these values, alternatives of interest are linguistically or numerically evaluated and a suitable alternative can be selected. Under given selection criteria, the suitable selections out of some liquid levelmeters for nuclear facilities are dealt with using the linguistic fuzzy methodology proposed. Then, linguistic fuzzy evaluation results are compared with qualitative result available in the literature. It is found that as to a suitable option the linguistic fuzzy selection is in agreement with the qualitative selection. Additionally, the comparative study shows that the fully-linguistic method using adequate scale system facilitates linguistic interpretation regarding evaluation results.

• 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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.517-521
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• 1998

DEA(data envelopment analysis) is a non-parametric technique for measuring and evaluating the relative efficiencies of a set of entities with common crisp inputs and outputs. In fact, in a real evaluation problem input and output data of entities often flucturate. These fluctuating data can be represented as linguistic variables characterized by fuzzy numbers. Based on a fundamental CCR model, a fuzzy DEA model is proposed to deal with fuzzy input and output data, Furthermore, a model that extends a fuzzy DEA to a more general case is also proposed with considering the relation between DEA and RA (regression analysis) . the crisp efficiency in CCR modelis extended to an L-R fuzzy number in fuzzy DEA problems to reflect some uncertainty in real evaluation problems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.259-262
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• 2010

Study about fuzzy entropy and similarity measure on intuitionistic fuzzy sets (IFSs) were proposed, and analyzed. Unlike fuzzy set, IFSs contains uncertainty named hesistancy, which is contained in fuzzy membership function itself. Hence, designing fuzzy entropy is not easy because of ununified entropy definition. By considering different fuzzy entropy definitions, fuzzy entropy is designed and discussed their relation. Similarity measure was also presented and verified its usefulness to evaluate degree of similarity.

• Journal of the Chungcheong Mathematical Society
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• v.24 no.2
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• pp.253-266
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• 2011

We would like to generalize about trapezoidal fuzzy set and to calculate four operations based on the Zadeh's extension principle for two generalized trapezoidal fuzzy sets. And we roll up triangular fuzzy numbers and generalized triangular fuzzy sets into it. Since triangular fuzzy numbers and generalized triangular fuzzy sets are generalized trapezoidal fuzzy sets, we need no more the separate painstaking calculations of addition, subtraction, multiplication and division for two such kinds once the operations are done for generalized trapezoidal fuzzy sets.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.5
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• pp.158-167
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• 2008

In recent years, various information technologies including ubiquitous computing technology have been developed and deployed. The more ubiquitous services based on ubiquitous technology have widely been spread, the more evaluation methods of those services are required. In this study, we suggest a framework for evaluating ubiquitous services by identifying evaluation factors and their relative importances. Combining review of related works and experts' opinions on the evaluation, we calculate the factors affecting ubiquitous service evaluation and relative importances among those factors using fuzzy Analytical Hierarchy Process (AHP). We conduct a case study to illustrate the applicability and feasibility of the suggested framework.

• Earthquakes and Structures
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• v.3 no.5
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• pp.695-717
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• 2012

Seismic resiliency of new buildings has improved over the years due to better seismic codes and design practices. However, there is still large number of vulnerable and seismically deficient buildings. It is not economically feasible to retrofit and upgrade all vulnerable buildings, thus there is a need for rapid screening tool. Many factors contribute to the damageability of buildings; this makes seismic evaluation a complex multi-criteria decision making problem. Many of these factors are noncommensurable and involve subjectivity in evaluation that highlights the use of fuzzy-based method. In this paper, a risk-based framework earlier proposed by Tesfamariam and Saatcioglu (2008a) is extended using Fuzzy-TOPSIS method and applied to develop an evaluation and ranking scheme for steel buildings. The ranking is based on damageability that can help decision makers interpret the results and take appropriate decision actions. Finally, the application of conceptual model is demonstrated through a case study of 1994 Northridge earthquake data on seismic damage of steel buildings.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.22
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• pp.43-50
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• 1990

In conventional function analysis, the function values are evaluated by experts, which are treated as exact values. For many cases, it is often difficult to evaluate the function values of a certain subject because the criteria of evaluation are very vague. This paper presents a new function evaluation method using fuzzy set. The purpose of the method is to minimize the difference among experts by recognizing an intersection point of membership function as a representative value.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.487-487
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• 2000

The scheduling of real-time tasks needs both correctness and timeliness. But it is not easy to schedule real-time tasks having different characteristics in a single system. In this paper we solve the problem through an approach using the performance evaluation of real-time tasks through fuzzy-random variables. Using the performance evaluation through fuzzy-random variable, we can achieve flexible and efficient scheduling for real-time systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.3 no.1
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• pp.76-89
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• 1993

The evaluation of the Fuzzy Expected Value (FEV) as a typical value requires complete knowledge about the domain of the evaluation, and the distribution of the population in that domain [1]. Since in many situations it is not possible to gather complete knowledge regarding the domain, it is necessary to relax some of the restrictions involving the evaluation of FEV. In this paper we discuss solutions to this problem by using the concept of the Fuzzy Expected Interval (FEI).