• 한국지능시스템학회논문지
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• 제19권4호
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• pp.556-561
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• 2009

In this paper, we propose new method to calculate the distance between intuitionistic fuzzy sets(IFSs) based on the three dimensional representation of IFSs and analyze the relations of similarity measure and distance measure of IFSs. Finally, we apply the proposed measures to pattern recognitions.

• 한국지능시스템학회논문지
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• 제3권4호
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• pp.21-23
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• 1993

Under the maxmin compositional rule of inference which is used in applications while executing fuzzy algorithms, Pappis showed that the property of approximation is preserved. In this paper, we generalize a measure of proximity of fuzzy subsets on any set, without the restriction of finiteness. And it is shown that the same property of approximation if preserved under the supmin compositional rule of inference.

• 충청수학회지
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• 제29권3호
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• pp.453-464
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• 2016

In this paper, we investigate the solution of the following functional inequality $$N(f(x)+f(y)+f(z),t){\geq}N(f(x+y+z),mt)$$ for some fixed real number m with $\frac{1}{3}$ < m ${\leq}$ 1 and using the fixed point method, we prove the generalized Hyers-Ulam stability for it in fuzzy Banach spaces.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권1호
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• pp.57-65
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• 2014

In this paper, we investigate the properties of L-lower approximation operators as a generalization of fuzzy rough set in complete residuated lattices. We study relations lower (upper, join meet, meet join) approximation operators and Alexandrov L-topologies. Moreover, we give their examples as approximation operators induced by various L-fuzzy relations.

• Kyungpook Mathematical Journal
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• 제53권3호
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• pp.319-332
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• 2013

The sequence space $m(M,{\phi})^F$ of fuzzy real numbers is introduced. Some properties of this sequence space like solidness, symmetricity, convergence-free etc. are studied. We obtain some inclusion relations involving this sequence space.

• 대한수학회논문집
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• 제25권3호
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• pp.405-417
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• 2010

We prove the generalized Hyers-Ulam stability of the generalized quadratic functional equation $$f(rx\;+\;sy)\;=\;r^2f(x)\;+\;s^2f(y)\;+\;\frac{rs}{2}[f(x\;+\;y)\;-\;f(x\;-\;y)]$$ in fuzzy Banach spaces, where r, s are non-zero rational numbers with $r^2\;+\;s^2\;{\neq}\;1$.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 추계학술대회 학술발표 논문집 제16권 제2호
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• pp.141-144
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• 2006

In this paper, using the notion of generalized metric (or D-metric) due to Dhage [3], we give new definition of M-fuzzy metric spaces and prove a common fixed point theorem for two mappings under the condition of weak compatible and R-weakly commuting mappings in complete M-fuzzy metric spaces.

• 대한수학회논문집
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• 제21권1호
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• pp.27-36
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• 2006

In this paper, we establish a generalization of fundamental homomorphism theorem in BCK-algebras by using fuzzy BCK-filters. We prove that if ${\mu}$. (resp. v) is a fuzzy BCK-filter of abounded BCK-algebra X (resp. Y), then $\frac{X{\times}Y}{{\mu}{\times}v}{\approxeq}X/{\mu}{\times}Y/v;\;and\;if\;{\mu}$ and F is a BCK-filter in a bounded BCK-algebra X such that $F/{\mu}$ is a BCK-filter of $X/{\mu}$, then $\frac{X/{\mu}}{F/{\mu}}{\approxeq}X/F$.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 춘계학술대회 학술발표 논문집 제16권 제1호
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• pp.61-64
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• 2006

Based on the geometrical representation of a generalized intuitionistic fuzzy set, we take into account all three parameters describing generalized intuitionistic fuzzy set, propose a method to calculate the correlation coefficient for generalized intuitionistic fuzzy sets in finite set and probability space, respectively, and discuss some properties of correlation and correlation coefficient of generalized intuitionistic fuzzy sets.

• Communications for Statistical Applications and Methods
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• 제16권2호
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• pp.335-348
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• 2009

Fuzzy regression is used as a complement or an alternative to represent the relation between variables among the forecasting models especially when the data is insufficient to evaluate the relation. Such phenomenon often occurs in seasonal time series data which require large amount of data to describe the underlying pattern. Semiparametric model is useful tool in the case where domain knowledge exists about the function to be estimated or emphasis is put onto understandability of the model. In this paper we propose fuzzy semiparametric support vector regression so that it can provide good performance on forecasting of the seasonal time series by incorporating into fuzzy support vector regression the basis functions which indicate the seasonal variation of time series. In order to indicate the performance of this method, we present two examples of predicting the seasonal time series. Experimental results show that the proposed method is very attractive for the seasonal time series in fuzzy environments.