• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.22-24
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• 2006

The installations of power quality monitoring system have increased drastically over the past several decades. These systems have been effectively used to monitor, analyze and diagnose the conditions of power system, and furthermore can be used to improve the present asset maintenance policy, scheduled (time-based) method, into the advanced, cost-effective and labor-effective maintenance methods, such as condition-based maintenance, predictive maintenance and reliability centered maintenance. As an approach to this, this paper introduces the statistical methods, three kinds of control charts (Shewhart chart, CUSUM chart and EWMA chart), and discusses the applicability of these methods to recognize the changing trends of power quality indices and to estimate the system's condition, using Matlab.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.560-570
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• 2006

This paper proposes a selectively cumulative sum (S-CUSUM) control chart with variable sampling intervals (VSI) for detecting shifts in the process mean. The basic idea of the VSI S-CUSUM chart is to adjust sampling intervals and to accumulate previous samples selectively in order to increase the sensitivity. The VSI S-CUSUM chart employs a threshold limit to determine whether to increase sampling rate as well as to accumulate previous samples or not. If a standardized control statistic falls outside the threshold limit, the next sample is taken with higher sampling rate and is accumulated to calculate the next control statistic. If the control statistic falls within the threshold limit, the next sample is taken with lower sampling rate and only the sample is used to get the control statistic. The VSI S-CUSUM chart produces an 'out-of-control' signal either when any control statistic falls outside the control limit or when L-consecutive control statistics fall outside the threshold limit. The number L is a decision variable and is called a 'control length'. A Markov chain model is employed to describe the VSI S-CUSUM sampling process. Some useful formulae related to the steady state average time-to signal (ATS) for an in-control state and out-of-control state are derived in closed forms. A statistical design procedure for the VSI S-CUSUM chart is proposed. Comparative studies show that the proposed VSI S-CUSUM chart is uniformly superior to the VSI CUSUM chart or to the Exponentially Weighted Moving Average (EWMA) chart with respect to the ATS performance.

• Journal of the Korean Data and Information Science Society
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• 제26권2호
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• pp.323-334
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• 2015

J. P. Morgan의 RiskMetrics을 기반으로 하는 현행 VaR 모형은 구조적으로 예측된 미래의 경기상황을 반영할 수가 없다. 본 연구에서는 주가의 변동요인인 워너 확률과정을 기업의 고유요인과 경기변동요인으로 구분한 원-팩터 (One-factor) 모형을 제안하여 미래 경기변동 공통요인을 미리 예측하여 반영함에 따라 장기적인 주식 보유기간에도 선제적인 리스크관리를 실시할 수 있도록 한다. 또한 미래 경기변동요인이 예측값으로 고정됨에 따라 포트폴리오를 구성하는 주가들이 서로 독립성을 만족하게 되여 포트폴리오의 분산을 최소화하는 각 주식의 투자금액을 결정하는 것은 물론 포트폴리오 VaR가 개별 VaR의 합으로 분해되어 목표로 하는 최대손실금액에 따른 포트폴리오의 구성을 효율적으로 실시할 수가 있다.