• Journal of the Chungcheong Mathematical Society
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• v.12 no.1
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• pp.63-72
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• 1999

We introduce a concept of fuzzy linearity: A function $F:L^0(X){\rightarrow}\mathbb{R}$ is fuzzy linear if $F[({\alpha}{\wedge}f){\vee}(b{\wedge}g)]=[a{\wedge}F(f)]{\vee}[b{\wedge}F(g)]$ for $f,g{\in}L^0(X)$ and a, b > 0. We show that a fuzzy integral is fuzzy linear if the measure is fuzzy c-additive.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.200-205
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• 2008

For data analysis, fuzzy entropy is introduced as the measure of fuzziness, similarity measure is also constructed to represent similarity between data. Similarity measure between fuzzy membership functions is constructed through distance measure, and the proposed similarity measure are proved. Application of proposed similarity measure to the example of reliable data selection is also carried out. Application results are compared with the previous results that is obtained through fuzzy entropy and statistical knowledge.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.146-150
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• 2008

In this paper, we consider concepts of subsethood measure introduced by Fan et al. [2]. Based on this, we give various subsethood measure defined by Choquet integral with respect to a fuzzy measure on fuzzy sets which is often used in information fusion and data mining as a nonlinear aggregation tool and discuss some properties of them. Furthermore, we introduce simple examples.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.145-149
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• 2008

The similarity measure is constructed for non-convex fuzzy membership function using well known Hamming distance measure. Comparison with convex fuzzy membership function is carried out, furthermore characteristic analysis for non-convex function are also illustrated. Proposed similarity measure is proved and the usefulness is verified through example. In example, usefulness of proposed similarity is pointed out.

• The Journal of the Korea Contents Association
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• v.2 no.2
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• pp.91-97
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• 2002

Let (X, F, g) be a fuzzy measure space. Then for any h$\in$ $L^{0}$ (X) , a$\in$[0 , 1] , and $A\in$F ∫$_{A}$aㆍh($\chi$)┬g＝aㆍ∫$_{A}$h($\chi$)┬g with the t-seminorm ┬(x, y)= xy. And we prove that the Seminormed fuzzy integral has some linearity properties only for ｛0,1｝-classes of fuzzy measure as follow, For any f, h$\in$ $L^{0}$ ($\chi$), any a, b$\in$R+: af＋bh$\in$ $L^{0}$ ($\chi$)⇒ ∫$_{A}$(af＋bh)┬g＝a∫$_{A}$f┬g＋b∫$_{A}$h┬g; if and only if g is a probability measure fulfilling g(A) $\in$｛0, 1｝ for all $A\in$F.n$F.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.2
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• pp.113-117
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• 2011

In this paper, we consider fuzzy complex valued fuzzy measures and Choquet integrals with respect to a fuzzy measure of real-valued measurable functions. In doing so, we investigate some basic properties and convergence theorems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.365-369
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• 2006

Interval-valued fuzzy sets were suggested for the first time by Gorzalczang(1983) and Turken(1986). Based on this, Wang and Li extended their operations on interval-valued fuzzy numbers. Recently, Hong(2002) generalized results of Wang and Li and extended to interval-valued fuzzy sets with Riemann integral. Using interval-valued Choquet integrals with respect to a fuzzy measure instead of Riemann integrals with respect to a classical measure, we studied some characterizations of interval-valued Choquet distance(2005). In this paper, we define Choquet distance measure for fuzzy number-valued fuzzy numbers and investigate some algebraic properties of them.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.549-551
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• 1998

For a fuzzy system modeled by a fuzzy hypergraph, two fuzzy similarity measures are proposed : one for the fuzzy similarity between fuzzy sets and the other between elements in fuzzy sets. The propose measures can represent the realistic similarities which can not be given by the existing measures. With and example, it is shown that it can be used in the behavior analysis in an organization.

• Journal of the Korean Society of Safety
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• v.20 no.2 s.70
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• pp.50-55
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• 2005

This Paper Presents assessment of fuzzy measure Possibility far the electromagnetic field according to voltage fluctuation of the Jechon Area. To cope with substantial electromagnetic analysis, the safety assessment were analyzed the double 154kV T/L, 345kV T/L, Jechon-Ichon Jechon-Youngju, respectively. As the results of case study, in case of 345kV T/L, the electric field value was 11.4927kV/m, magnetic field value was 0.4622G at the Point about 7m away from the line in severest case. Tn assessment of fuzzy measure Possibility for the electromagnetic field, this paper use probability of fuzzy and measure of fuzziness technique.

• Journal of the Korean Society of Safety
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• v.16 no.3
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• pp.45-52
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• 2001

This paper presents a study on the assessment of fuzzy measure possibility for the electromagnetic field of unbalanced system. It takes into account m untransposed transmission line and unbalanced load. A three phase load flow program was developed which employs a Newton-Raphson method as a tool to analyze system unbalanced. This research presents a method of handling two coupled three phase transmission system unbalance analysis and unbalanced power demand as a function of voltages. In assessment of fuzzy measure possibility for the electromagnetic field, this paper use probability of fuzzy and measure of fuzziness technique.