• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
• /
• pp.97-101
• /
• 1997

In recent years, there have been a number of applications of fuzzy logic in fuzzy reasoning system. The main objective of these applications is to approximate a decision making using the fuzzy reasoning system. This paper designs a fuzzy reasoning model for the decision making of registration fee at a private school, implements it applying for linguistic variables and fuzzy rules, and evaluates the practical availability of the model. The system accepts fuzzy rules, the type of membership functions, the domain of fuzzy sets and hedge, and fuzzifies the linguistic variables to generates fuzzy sets. The fuzzy sets generated are combined to constructs a solution fuzzy set. Finally, the system defuzzifies the solution fuzzy set to calculate a scalar value which is used for decision making.

• 한국지능시스템학회논문지
• /
• 제19권5호
• /
• pp.695-698
• /
• 2009

본 논문에서는 퍼지 r-열린 집합을 일반화 시킨 퍼지 r-일반 열린 집합의 개념과 성질을 소개한다. 그리고 퍼지 r-일반 연속함수, 퍼지 r-일반 열린함수, 퍼지 r-일반 닫힌 함수의 개념과 특성을 연구한다.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제6권3호
• /
• pp.255-263
• /
• 2006

In this paper, we introduce the concepts of ${\gamma}$-fuzzy feebly open and ${\gamma}$-fuzzy feebly closed sets in Sostak's fuzzy topological spaces and by using them, we explain the notions of ${\gamma}$-fuzzy F-closed spaces. Also, we give some characterization of ${\gamma}$-fuzzy F-closedness in terms of fuzzy filterbasis and ${\gamma}$-fuzzy feebly-${\theta}$-cluster points.

• Journal of applied mathematics & informatics
• /
• 제8권2호
• /
• pp.551-560
• /
• 2001

In this paper, we investigate the continuity if addition and scalar multiplication on the space F(R/sup p/) of upper semicontinuous fuzzy sets in R/sup p/ under the Shorokhod metric.

• 한국지능시스템학회논문지
• /
• 제17권2호
• /
• pp.149-153
• /
• 2007

본 논문에서 우리는 Wang와 Li(1998)와 Turksen(1986)에 의해 소개된 구간치 퍼지집합을 생각하고 구간치 퍼지집합상에서 쇼케이적분에 의해 정의된 엔트로피를 조사한다. 더욱이, 이러한 엔트로피와 관련된 성질들을 토의하고 간단한 예들을 알아본다. 이 공식은 구간치 퍼지집합상의 결정이론 및 정보이론과 같은 응용 영역에서 중요한 역할을 한다.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
• /
• pp.358-363
• /
• 1998

An algorithm for representing the cubic spline interpolation of differentiable functions by a fuzzy system is presented in this paper. The cubic B-spline functions which form a basis for the interpolation function are used as the fuzzy sets for input fuzzification. The ordinal number of the coefficient cKL in the list of the coefficient cij's as sorted in increasing order, is taken to be the output fuzzy set number in the (k, l) th entry of the fuzzy rule table. Spike functions are used for the output fuzzy sets, with cij's as support boundaries after they are sorted. An algorithm to compute the support boundaries explicitly without solving the matrix equation involved is included, along with a few properties of the fuzzy rule matrix for the designed fuzzy system.

• Kyungpook Mathematical Journal
• /
• 제45권1호
• /
• pp.13-19
• /
• 2005

In this paper we introduce the notions of g-regularity and g-normality in fuzzy topological spaces. We obtain some characterizations and several preservation theorems of such spaces.

• East Asian mathematical journal
• /
• 제29권3호
• /
• pp.269-278
• /
• 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.

• 충청수학회지
• /
• 제25권2호
• /
• pp.217-225
• /
• 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.

• International Journal of Control, Automation, and Systems
• /
• 제4권2호
• /
• pp.187-196
• /
• 2006

A new GA-based methodology using information granules is suggested for the construction of fuzzy classifiers. The proposed scheme consists of three steps: selection of information granules, construction of the associated fuzzy sets, and tuning of the fuzzy rules. First, the genetic algorithm (GA) is applied to the development of the adequate information granules. The fuzzy sets are then constructed from the analysis of the developed information granules. An interpretable fuzzy classifier is designed by using the constructed fuzzy sets. Finally, the GA is utilized for tuning of the fuzzy rules, which can enhance the classification performance on the misclassified data (e.g., data with the strange pattern or on the boundaries of the classes). To show the effectiveness of the proposed method, an example, the classification of the Iris data, is provided.