• Journal of applied mathematics & informatics
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• 제33권5_6호
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• pp.607-625
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• 2015

Recently, Wang et al. [Computers and Mathematics with Ap-plications 57 (2009) 1232-1248.] and Wang and Watada [Information Sci-ences 179 (2009) 4057-4069.] studied the renewal process and renewal reward process with fuzzy random inter-arrival times and rewards under the T-independence associated with any continuous Archimedean t-norm. But, their main results do not cover the classical theory of the random elementary renewal theorem and random renewal reward theorem when fuzzy random variables degenerate to random variables, and some given assumptions relate to the membership function of the fuzzy variable and the Archimedean t-norm of the results are restrictive. This paper improves the results of Wang and Watada and Wang et al. from a mathematical per-spective. We release some assumptions of the results of Wang and Watada and Wang et al. and completely generalize the classical stochastic renewal theorem and renewal rewards theorem.

• 한국학교수학회논문집
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• 제6권1호
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• pp.27-43
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• 2003

본 논문은 자데교수에 의해 소개된 퍼지집합을 정의하면서 시작된 퍼지이론과 도이거넌과 팔마건에 의해 발전된 지식공간의 수학교육의 교수학습에 효과적으로 적용될 수 있는 모색하고자 하는 의도로 새로운 이론을 소개한다. 특히, 위 두 이론은 평가부분에서 현재의 평가방법이 해결할 수 없는 부분을 접근하여 수학 학습 평가의 새로운 장을 열 것으로 기대한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권2호
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• pp.147-153
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• 2013

Previously, Park et al. (2005) defined an intuitionistic fuzzy metric space and studied several fixed-point theories in this space. This paper provides definitions and describe the properties of type(${\beta}$) compatible mappings, and prove some common fixed points for four self-mappings that are compatible with type(${\beta}$) in an intuitionistic fuzzy metric space. This paper also presents an example of a common fixed point that satisfies the conditions of Theorem 4.1 in an intuitionistic fuzzy metric space.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.42.1-42
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• 2002

A model to predict population by sex, age and district over a long-range period is proposed based on fuzzy theories. First, a fuzzy model is described. Second, a method to estimate the social increase by sex and age in each district is proposed based on a fuzzy clustering method for dealing with long-range socioeconomic changes in population migration. By the proposed methods, it became possible to predict the population by sex, age and district over a long-range period. Third, the structure and characteristics of the three models of employment model, time distance model, and land use model constructed to predict various socioeconomic indicators, which are require...

• Journal of applied mathematics & informatics
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• 제20권1_2호
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• pp.401-408
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• 2006

Fixed point theory is one of famous theories from theoretical and numerical point of views. Banach fixed point theorem plays a main role in this theory. In this article, Grabiec's fuzzy Banach contraction theorem [3] and Vasuki's theorem [12] for a complete fuzzy metric space, in the sense of Song [11] (or George and Veeramani), is proved by an extra condition.

• 한국지능시스템학회:학술대회논문집
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• 한국지능시스템학회 2008년도 춘계학술대회 학술발표회 논문집
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• pp.333-334
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• 2008

모든 이론에는 철학적인 전제가 있기 마련이다. 퍼지논리의 경우도 예외는 아니다. 본 논문은 역사적인 접근을 통해 퍼지논리가 상대주의와 다원주의적 세계관을 반영하고 있음을 보이는 것이 목적이다.

• 전자공학회논문지B
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• 제31B권6호
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• pp.43-52
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• 1994

A design method of rule-based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of ``IF....,THEN...', using the theories of optimization theory , linguistic fuzzy implication rules and fuzzy c-means clustering. Three kinds of method for fuzzy modeling presented in this paper include simplified inference (type I), linear inference (type 2), and modified linear inference (type 3). In order to identify premise structure and parameter of fuzzy implication rules, fuzzy c- means clustering and modified complex method are used respectively and the least sequare method is utilized for the identification of optimum consequence parameters. Time series data for gas furance and those for sewage treatment process are used to evaluate the performance of the proposed rule-based fuzzy modeling. Comparison shows that the proposed method can produce the fuzzy model with higher accuracy than previous other studies.

• 대한조선학회논문집
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• 제40권1호
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• pp.69-73
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• 2003

Neuro-Fuzzy System is to combine merits of fuzzy inference system and neural networks. The neuro-fuzzy system applies a information about given input-output data to fuzzy theories and deals these fuzzy values with neural networks, e.g. first, redefines normalized input-output data as membership functions and then executes thses fuzzy information with backpropagation neural networks. This paper describes an innovative application of the Taguchi method for the determination of these parameters to meet the training speed and accuracy requirements. Results drawn from this research show that the Taguchi method provides an effective means to enhance the performance of the neuro-fuzzy system in terms of the speed for learning and the accuracy for recall.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.307-312
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• 1994

The authors have been devoted to researches on fuzzy theories and their applications, especially control theory and application problems, for recent years. In this paper, the authors present results on a comparison of optimal solutions between ones of an ordinary-typed mathematical linear programming problem(O.M.I.P. problem) and ones of a Zimmerman-typed fuzzy mathematical linear programming problem (F.M.L.P. problem), and comment about the sensitivity (differences and fuzziness on between O.M.L.P. problem and F.M.L.P. problem) on optimal solutions of these mathematical linear programming problems.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.240-245
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• 1998

Fuzzy information retrieval which uses the concept of fuzzy relation is able to retrieve documents in the way based on not morphology but semantics, dissimilar to traditional information retrieval theories. Fuzzy information retrieval logically consists of three sets : the set of documents, the set of terms and the set of queries. It maintains a fuzzy relational matrix which describes the relationship between documents and terms and creates a thesaurus with fuzzy relational product. It also provides the user with documents which are relevant to his query. However, there are some problems on building a thesaurus with fuzzy relational product such that it has big time complexity and it uses fuzzy values to be processed with flating-point. Actually, fuzzy values have to be expressed and processed with floating-point. However, floating-point operations have complex logics and make the system be slow. If it is possible to exchange fuzzy values with binary values, we could expect sp eding up building the thesaurus. In addition, binary value expressions require just a bit of memory space, but floating -point expression needs couple of bytes. In this study, we suggest a new method of building a thesaurus, which accelerates the operation of the system by pre-applying an ${\alpha}$-cut. The experiments show the improvement of performance and reliability of the system.