• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.140-144
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• 2005

In this paper, an almost everywhere convergence theorem for seminormed fuzzy co-integrals is showed provided that the fuzzy measure is null-additive.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.262-266
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• 2004

In general, the fuzzy integral lacks some important properties that Lebesgue integral possesses. One of them is linearity. In this paper, we introduce fuzzy linearity in which we use the supremum and the infimum instead of additon and scalar multiplication in the expression of linearity and show that the fuzzy linearity of the seminormed fuzzy integrals of interval-valued functions when the fuzzy measure g is fuzzy additive, the continuous t-seminorm is saturated and measurable functions satisfy the condition[Max].

• Journal of the Korean Society of Marine Environment & Safety
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• v.11 no.2 s.23
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• pp.27-32
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• 2005

This paper suggests an evaluation of risk level for damage of marine accidents in SRRs. This paper intoduces a concept of fuzzy logic with the plenty of related literature riview, fuzzy measure t-seminormed fuzzy integral and in the Korean SRRs of RCC and RSC. The methodology of this paper is max. min composition of fuzzy extensive principle, defuzzifiation is centroid of gravity methods. And final evaluation value using t-seminormed fuzzy integral. At the result, the evaluation of risk level is especially over serious for marine accident of Mokpo, Tongyoung, Yeosu SRRs.. This paper recommends that many rescue vessels and equipments need to the reduction of risk level about those.

• Proceedings of KOSOMES biannual meeting
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• 2004.11a
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• pp.83-88
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• 2004

This paper suggests on evaluation of risk level for damage of marine accidents in SRRs. This paper intoduces a concept of fuzzy logic with the plenty of related literature riview, fuzzy measure t-seminormed fuzzy integral and in the Korean. SRRs of RCC and RSC. The methodology of this paper is max$\cdot$min composition of fuzzy extensive principle, defuzzifiation is centroid of gravity methods. And final evaluation value using t-seminormed fuzzy integral. At the result, the evaluation of risk level is especially over Serious for marine accident of Mokpo, Tongyoung, Busan SRRs. This paper recommends tint many Rescue Vessels and Equipments need to the reduction of risk level about those.

• The Journal of the Korea Contents Association
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• v.2 no.4
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• pp.99-103
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• 2002

In this paper, we investigate for how to define a fuzzy measure by using the semi-normed fuzzy integral of a given measurable function with respect to another given fuzzy measure when t-seminorm is continuous. Let (X, F, g) be a fuzzy measure space, h$\in$L$^\circ$(X), and $\top$ be a continuous t-seminorm.. Then the set function $\nu$ defined by $\nu$(A)=$\int _A$h$\top$g for any $A\in$F is a fuzzy measure on (X, F).

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.2
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• pp.87-93
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• 2009

Intrusion tolerant system enables essential services to maintain for a period of time under system failure, malicious attacks and is gaining more importance in national defense, communication infrastructure, and financial sector. However, few objective evaluation criteria for companies and agencies to introduce an appropriate system are available. This paper proposes a suitability evaluation method, using Analytic hierarchy process and fuzzy integral, for intrusion tolerant system, along with evaluation criteria which considers the characteristics and costs of systems in addition to other factors.

• 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.