• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1215-1217
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• 1993

In this paper, we reason about the fuzzy dynamic equation based on L-R type fuzzy number, analyze and solve the fuzzy dynamic property and the fuzzy dynamic response of singledegree of freedom system. Specific expressions of fuzzy dynamic response are response.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.2
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• pp.115-118
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• 2001

본 논문에서는 L-R 퍼지수의 집합-이론적 연산의 개념을 정의하고, 이들 개념의 성질들을 조사한다. 이들 연산들의 결과들을 이용하여 제2형 퍼지집합의 기수개념에 관하여 연구한다.

• Communications of the Korean Mathematical Society
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• v.18 no.2
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• pp.385-392
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• 2003

The sum Of L - R fuzzy numbers With Unbounded Supports based on Archimedean continuous f-norm T is considered. Results are more simple than those of the case for bounded supports.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.7
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• pp.87-97
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• 1992

Fuzzy controllers have been successfully applied to many cases to which conventional control algorithms are difficult to be applied. Even though the representations and the processings of data and information in the fuzzy controller are quite different from those in other control algorithms, the information processing operation that it caries out is basically a function ∫: $A{\subset}R^n{\to}R^m$, from a bounded subset A of an n-dimensional Euclidean space to a bounded subset f[A] of an m-dimensional Euclidean space, where n and m are the number of measured states and the number of control inputs of the controlled system, respectively. Under the assumptions of Mamdani's direct reasoning method and C.O.G.(center of gravity) defuzzification method, the fuzzy controllers are proven to perform the mapping of any given functions f with appropriately defined fuzzy sets. The mapping capabilities of fuzzy controllers are analyzed in detail for two cases, ∫: $R^{1}{\to}R^{1}$ and g: $R^{2}{\to}R^{1}$. Also, it will be shown that the results can be extended to multiple dimensional cases.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.489-491
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• 1993

Many optimization problem or multiple attribute, multiple alternative decision making problem may have fuzzy evaluation factors. In this case, fuzzy number operation technique is needed to evaluate and compare object functions which become fuzzy sets. Generally, fuzzy number operations can be defined by extension principle of fuzzy set theory, but it is tedious to do fuzzy number operations by using extension principle when the membership functions are defined by complex functions. Many fast methods which approximate the membership functions such as triangle, trapezoidal, or L-R type functions are proposed. In this paper, a fast fuzzy number operation method is proposed which do not simplify the membership functions of fuzzy numbers.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.353-356
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• 2001

In this paper, we study the existence of fuzzy solution for the following differential system with fuzzy coefficient using the different two methods: (equation omitted), where a, b is the fuzzy natural number generated by fuzzy number l . The a-level set of the fuzzy number (equation omitted). The -level set of a is (equation omitted) and -level set of b is (equation omitted).

• 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.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.8
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• pp.1047-1052
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• 2004

The genomes of Chinese native chicken populations were screened using microsatellites as molecular markers. A total of, 528 individuals comprisede12 Chinese native chicken populations were typed for 7 microsatellite markers covering 5 linkage groups and genetic variations and genetic distances were also determined. In the 7 microsatellite loci, the number of alleles ranged from 2 to 7 per locus and the mean number of alleles was 4.6 per locus. By using fuzzy cluster, 12 Chinese native chicken populations were divided into three clusters. The first cluster comprised Taihe Silkies, Henan Game Chicken, Langshan Chicken, Dagu Chicken, Xiaoshan Chicken, Beijing Fatty Chicken and Luyuan Chicken. The second cluster included Chahua Chicken, Tibetan Chicken, Xianju Chicken and Baier Chicken. Gushi Chicken formed a separate cluster and demonstrated a long distance when comparing with other chicken populations.