• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.567-572
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• 1991

This paper proposes an algorithm of fuzzy model modification which improves fuzzy relation matrix for multi-input/single output dynamic systems. Zadeh's possibility distribution plays an important role in the proposed algorithm and in the use of fuzzy models which are constructed by the proposed algorithm. The required computer capacity and time for implementing the proposed algorithm and resulting models are significantly reduced by introducing the concept of the referential fuzzy sets. A nonlinear system is given to show that the proposed algorithm can provide the fuzzy model with satisfactory accuracy.

• Journal of Bio-Environment Control
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• v.4 no.1
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• pp.89-95
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• 1995

퍼지 이론(fuzzy theory)은 정보의 애매성을 다루는 학문으로 과학에 주관성이 도입된 형태의 새로운 학문 분야이다. 인간의 사고를 수치화하고 이를 언어적으로 처리할 수 있는 퍼지 이론은 인공지능(artificial intelligence)의 한 분야로서, 1965년 Lofti Zadeh 교수에 의하여 창안되었다. 초기 기초 연구 중심의 단계에서 현재에는 첨단 전자공학의 발달과 함께 퍼지 제어기의 농업 및 산업 응용이 활발해지고 있으며, 퍼지 칩이나 퍼지 컴퓨터의 개발까지 연구가 진행되고 있다.(중략)

• Journal of the KSME
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• v.34 no.4
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• pp.277-284
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• 1994

퍼지이론은 1965년 Lefti Zadeh 교수에 의해 처음으로 제창되었으며 여러 분야에서 응용이 확 대되어 많은 좋은 성과를 얻고 있다. 그러나 전문가 시스템의 일종인 퍼지논리를 이용한 제어는 제어를 하고자 하는 시스템의 정성적인 특성에 대한 법칙의 추출이 어려운 문제로 남아 있다. 반면에 신경회로망을 이용한 제어는 스스로 지식을 축적할 수 있는 장점을 갖고 있으므로 최근에 많은 연구가 진행중에 있다. 특히 제어분야에서는 용접공정이나 조립공정 등의 공정제어와 로 봇제어의 분야에 이르기까지 응용분야가 확대되고 있다. 이 글에서는 이러한 인공지능 기법을 생산공정의 자동화에 적용한 사례 연구를 통해 이 기법의 유용함을 살펴보기로 한다.

• East Asian mathematical journal
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• v.29 no.3
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• pp.269-278
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• 2013

A fuzzy set A defined on a probability space (${\Omega}$, $\mathfrak{F}$, P) is called a fuzzy event. Zadeh defines the probability of the fuzzy event A using the probability P. We define the normal fuzzy probability on $\mathbb{R}$ using the normal distribution. We calculate the normal fuzzy probability for generalized trapezoidal fuzzy sets and give some examples.

• Journal of the Chungcheong Mathematical Society
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• v.22 no.2
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• pp.161-170
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• 2009

For various fuzzy numbers, many operations have been calculated. We generalize about triangular fuzzy number and calculate four operations based on the Zadeh's extension principle, addition A(+)B, subtraction A(-)B, multiplication A(${\cdot}$)B and division A(/)B for two generalized triangular fuzzy sets.

• Journal of applied mathematics & informatics
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• v.29 no.1_2
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• pp.327-335
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• 2011

Explicit formulas are given for the first and second Zagreb index, degree-distance and Wiener-type invariants of splice and link of graphs. As a consequence, the first and second Zagreb coindex of these classes of composite graphs are also computed.

• Journal of the Korean Mathematical Society
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• v.47 no.1
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• pp.123-134
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• 2010

The aim of this paper is to provide a proof for a version of the Morse inequalities for manifolds with boundary. Our main results are certainly known to the experts on Morse theory, nevertheless it seems necessary to write down a complete proof for it. Our proof is analytic and is based on the J. Roe account of Witten's approach to Morse Theory.

• Journal of the Chungcheong Mathematical Society
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• v.25 no.2
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• pp.217-225
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• 2012

A generalized quadratic fuzzy set is a generalization of a quadratic fuzzy number. Zadeh defines the probability of the fuzzy event using the probability. We define the normal fuzzy probability on $\mathbb{R}$ using the normal distribution. And we calculate the normal fuzzy probability for generalized quadratic fuzzy sets.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.133-138
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• 2009

We investigate the properties of meet preserving maps on strictly two-sided, commutative biquantales. Using the properties of meet preserving maps, we induce the Zadeh image and pre image operators.

• 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.