• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.352-357
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• 1987

The Auto Tuning Controller is designed using Fuzzy set theory. And to verify its validity it is Applied to the Auto Tuner of hydraulic Control System. Fuzzy Tuning Procedures are written by linguistic model and translated into C language formation by preprocessor. Then it is executed with state feedback controller in real time, Fuzzy Logic Controller adjusts state feedback gain by proper tuning logic in each step to satisfy the desired maximum overshoot and settling time.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1998.10a
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• pp.64-68
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• 1998

This paper discusses the potential application of fuzzy set theory to the decision-making in the area of radioactive waste management. the approach proposed in this study is based on the concepts of fuzzy set theory and the hierarchical structure analysis. The linguistic variables and fuzzy numbers are used to aggregate the decision maker's subjective assessments of the decision criteria and of the decision alternatives with respect to these criteria. For each alternative, the fuzzy appropriateness index is evaluated to obtain the final score. Using total integral value method, one of methods for ranking fuzzy numbers, the fuzzy appropriateness indices are ranked. As a case problem, selection of the most suitable option for spent fuel storage is illustrated.

• Journal of the Chungcheong Mathematical Society
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• v.23 no.3
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• pp.511-521
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• 2010

In this paper, we define the one-sided fuzzy set and we calculate the mean value and variance, defined by C. Carlsson and R. $Full{\acute{e}}r$, of this fuzzy set. And we obtain a result that, in some special case, the mean of the product of two fuzzy sets is the product of means of each fuzzy sets. This result can be considered as the similar result which is well-known in the independence of events in probability theory.

• Journal of the Korean School Mathematics Society
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• v.6 no.1
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• pp.27-43
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• 2003

This paper introduces some theories that can be effectively applied for the development of teaching and learning mathematics using fuzzy theory developed by Zadeh who defined fuzzy set and knowledge space by Doignon and Falmagne. Especially, we expect that two theories mentioned above are expected to solve the situation that could not be taken care of the present evaluation method.

• Journal of applied mathematics & informatics
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• v.42 no.3
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• pp.521-538
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• 2024

In this paper, using the notion of the imprecise set, the idea of an imprecise group is introduced including some examples. The two key rules of classical set theory are obeyed by this extended version of fuzzy sets, which the existing complement definition of a fuzzy set failed to do. With the support from general group theory, the paper also provides some fundamental properties of an imprecise group here. Additionally, it includes a few characteristics of imprecise subgroups, and abelian imprecise group.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.735-739
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• 2001

This paper describes a research work of developing computer-aided design of a product with bending and piercing for progressive working. An approach to the system for progressive working os based on the knowledge-based rules. Knowledge for the system is formulated from plasticity theorise, experimental results and the empirical knowledge of field experts. the system has been written in AutoLISP on the AutoCAD with a personal computer and is composed of three main modules, which are input and shape treatment, flat pattern layout and strip layout modules. Strip layout of the system is designed by using fuzzy set theory. Process planning is determinated by fuzzy value according to several rules. Strip layout drawing generated in strip layout module is presented in 3-D graphic forms, including bending sequences and piercing processes with punch profiles divided into for external area. Results obtained using the modules enable the manufacturer for progressive working of electric products to be more efficient in this field.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.394-398
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• 2012

Based on the theory of a bipolar fuzzy set, the notion of a bipolar fuzzy subring/ideal of a Near ring is introduced and related properties are investigated. Characterizations of a bipolar fuzzy subnear ring and a bipolar fuzzy ideal in near ring are established. Relations between a bipolar fuzzy ideal and a level cut are discussed. Using bipolar fuzzy ideals, we discuss characterizations of Noetherian Near ring.

• International Journal of Quality Innovation
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• v.5 no.1
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• pp.52-67
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• 2004

Successful implementation of statistical process control techniques requires for operational definitions and precise measurements. Nevertheless, very often analysts can dispose of process data available only by linguistic terms, that would be a waste to neglect just because of their intrinsic vagueness. Thus a hybrid approach, which integrates fuzzy set theory and common statistical tools, sounds useful in order to improve effectiveness of statistical process control in such a case. In this work, a fuzzy approach is adopted to manage linguistic information, and the use of a Chi-squared control chart is proposed to monitor process performance.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.9
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• pp.1055-1063
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• 1999

This paper present a conceptual possibilistic approach using fuzzy set theory to manage the uncertainties in the given reliability input date of the practical power system. In this paper, an algorithm is introduced to calculate the possibilstic reliability indices according to the degree of uncertainty in the given data. The probability distribution function can be transformed into an appropriate possibilstic representation using the probability-Possibility Consistency principle(PPCP) algorithm. In this the algorithm, the transformation is performation by making a compromise between the transformation consistency and the human updating experience. Fuzzy classifcation theory is applied to reduced the number of load data. The fuzzy classification method determines the closeness of load data points by assigning them to various clusters and then determening the distance between the clusters. The IEEE-RTS with 32-generating units is used to demonstrate the capability of the proposed algorithm.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1529-1532
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• 2007

Failure Mode, Effects, and Criticality Analysis (FMECA) is an extension of FMEA which includes a criticality analysis. The criticality analysis is used to chart the probability of failure modes against the severity of their consequences. The result highlights failure modes with relatively high probability and severity of consequences, allowing remedial effort to be directed where it will produce the greatest value. However, there are several limitations. Measuring severity of failure consequences is subjective and linguistic. Since The result of FMECA only gives qualitative and quantitative informations, it should be re-analysed to prioritize critical units. Fuzzy set theory has been introduced by Lotfi A. Zadeh (1965). It has extended the classical set theory dramatically. Based on fuzzy set theory, fuzzy logic has been developed employing human reasoning process. IF-THEN fuzzy rule based assessment approach can model the expert's decision logic appropriately. Fault tree analysis (FTA) is one of most common fault modeling techniques. It is widely used in many fields practically. In this paper, a simple fault tree analysis is proposed to measure the severity of components. Fuzzy rule based assessment method interprets linguistic variables for determination of critical unit priorities. An rail-way transforming system is analysed to describe the proposed method.