• 조명전기설비학회논문지
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• 제24권8호
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• pp.94-100
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• 2010

접지시스템은 전기설비의 기준 전위점을 확보할뿐만 아니라 낮은 대지저항으로 고장전류나 과도 전류를 흐르게 한다. 접지임피던스는 주파수에 대한 함수로 고장이나 과도전류가 넓은 범위의 주파수 성분을 포함하기 때문에 접지성능을 평가하는데 중요한 역할을 한다. 본 논문에서는 스테인리스강판 접지전극의 접지특성을 파악하기 위하여 3점 전위강하법으로 접지저항, 접지임피던스와 과도접지임피던스를 측정하였다. 측정된 데이터를 이용하여 접지임피던스와 과도접지임피던스의 등가 전달함수 모델은 ARMA 기법으로 모델링 되었고, 규약접지임피던스로 비교하여 평가하였다.

• International Journal of Quality Innovation
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• 제3권2호
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• pp.174-182
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• 2002

System identification and controller formulation are essential in dynamic process control. In system identification, data for system identification are obtained, and then they are analyzed so that the system model of the process is built, identified, and diagnosed. In controller formulation, the control equation is derived based on the result of the system identification. There has been much theoretical research on system identification and controller formulation. These theories are very useful when they are appropriately applied. To our regret, however, these theories are not always effectively applied in practice because the engineers and the operators who manage the process often do not have the necessary understanding of required time series analysis methods. On the other hand, because of widespread use of statistical packages, system identification such as estimating ARMA models can be done with little understanding of time series analysis methods. Therefore, it might be said that the most theoretically difficult part in practice is the controller formulation. In this paper, lists of control equations are proposed as a useful tool for practitioners to use. The tool supports bridging the gap between theory and practice in dynamic process control. Also, for some models, the generalized control equations are obtained.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.20-20
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• 2018

다년동안 지속되는 가뭄현상이 빈번하게 발생하고 있지만, 우리나라에서는 지금까지 장기 가뭄보다 단기 가뭄에 초점을 맞춰 연구가 진행되어 왔다. 다년 가뭄을 반영하지 않고 댐의 저수용량을 평가할 경우, 저수용량이 과소평가될 수 있기 때문에 다년간의 가뭄을 반영한 시계열 모형을 통해 다양한 시나리오를 생성하고 분석해야 한다. 본 연구에서는 2015년부터 2017년까지 장기 가뭄이 발생한 보령댐의 1998년-2017년까지의 관측 월평균 유입량 자료를 바탕으로 Autoregressive Moving Average(ARMA)시계열 모형과 Hurst Coefficient를 추가하여 장기지속성을 반영하도록 개발된 시계열 모형인 Autoregressive Fractionally Integreated Moving Average(ARFIMA)를 사용하여 보령댐 500년 기간의 유입량 자료를 생성하였다. Hurst Coefficient는 Hurst가 제안한 Rescaled Range(R/S)방법 외에도 경험식, 이론식을 모두 사용하여 산정하였다. 생성된 자료가 관측 자료의 장기지속성을 잘 반영하는지에 대한 검증을 위해 관측자료의 누적유입량으로부터 선형 이동평균방법을 사용하여 가뭄기준을 산정하고, 생성한 유입량 자료가 장기가뭄을 반영하고 있는지 판단하였다. 그 결과 가뭄의 장기지속성을 잘 반영하는 시계열 모형을 선정하였으며, 향후 연구를 통해 미래 기후변화 시나리오를 반영한 장기가뭄 분석을 수행할 예정이다.

• 수산경영론집
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• 제53권4호
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• pp.15-26
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• 2022

This paper analyzed the price stabilization before and after the fisheries outlook project for seaweed, flatfish, and abalone. First, the stabilization effect was analyzed through the price variation coefficient before and after the observation project. In terms of the variation coefficient, there was no effect that the price was stabilized through the seaweed outlook project. However, it can be seen that flatfish and abalone have a price-stabilizing effect. Second, as a result of analyzing the price stabilization effect through the improved ARMA-T-GARCH model, it was confirmed that seaweed was not statistically significant while flatfish and abalone had a price stabilization effect by statistically significantly reducing volatility of real prices after the introduction of the fisheries outlook project. Third, as a result of analyzing the factors affecting price stability, it was found that the price of seaweed was stabilized after the WTO, but the Japanese earthquake expanded the price volatility. In the case of flatfish, it was analyzed that the price stabilized after the WTO and the Great Japanese Earthquake. Finally, the price of abalone has stabilized since the WTO and the Great Japanese Earthquake.

• 한국국방경영분석학회지
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• 제8권1호
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• pp.71-76
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• 1982

A procedure is established for combining a regression model and a time series model to fit to a set of autocorrelated data. This procedure is based on an iterative method to compute regression parameter estimates and time series parameter estimates simultaneously. The time series model which is discussed is basically AR(p) model, since MA(q) model or ARMA(p,q) model can be inverted to AR({$\infty$) model which can be approximated by AR(p) model. The procedure discussed in this articled is applied in general to any combination of regression model and time series model.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1419-1422
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• 1997

This paper deals with the Appliation of robust fault detection problem in uncertain linear systems, having both model mismatch and noise. A robust fault detection method presented by Kwon et al.(1994) for SISO uncertain systems. Here we experimented this method to the diesel engine systems described by difference ARMA models. The model mismatch includes here linearization error as well as undermodeling. Comparisons are made with alternative fault detection method which do not account noise. The new method is shown to have good performance.

• 전자공학회논문지B
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• 제31B권7호
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• pp.58-65
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• 1994

A recursive on-line algorithm for orthogonal ARMA identification is proposed for linear MIMO systems with unknown parameters time delay and order. This algorithm is based on the Gram-Schmidt orthogonalization of basis functions, and extended to a recursiveform by using new functions of two dimensional autocorrelations and crosscorrelations of inputs and outputs. This proposed algorithm can also cope with slowly time-varying or order-varying systems. Various simulations reveal the performance of the algorithm.

• 대한산업공학회지
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• 제14권1호
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• pp.51-56
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• 1988

A spectrum analysis method is presented with an example as an aid to Box and Jerkins' model identification procedure, where the theoretical spectrum of ARMA model and its confidence intervals derived by chi-square distribution are compared. An APL (A Programming Language) program for the method is developed for the 16-bit personal computer.

• 한국정보과학회논문지:소프트웨어및응용
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• 제28권4호
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• pp.338-345
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• 2001

본 연구에서는 시계열자료를 예측하기 위해 적용한 n$\times$n$\times$1 신경망 구조에서 초기값의 시각적인 선택을 통한 개선된 학습과정을 제안한다. 적용된 Easton[1]의 제어상자는 시각적인 면과 실용적인 적용측면에서 다차원 구조를 논의하기에는 제한적이지만, 적은 개수의 은닉노드를 갖는 단순한 신경망구조에서는 초기 가중값들의 동적인 선택을 통하여 가능한 빨리 효과적인 학습이 이루어질 수 있게 할 수 있다. 신경망 학습의 오차 판단기준은 기존의 평균제곱오차(MSE)를 고려한다. 실증연구에는 모의생성된 ARMA(1,0) 자료와 담배생산량 자료를 이용한다.

• Journal of the Korean Statistical Society
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• 제30권1호
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• pp.115-125
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• 2001

We consider the threshold autoregressive moving average(TARMA) process and find a sufficient condition for strict stationarity of the proces. Given region for stationarity of TARMA(p,q) model is the same as that of TAR(p) model given by Chan and Tong(1985), which shows that the moving average part of TARMA(p,q) process does not affect the stationarity of the process. We find also a sufficient condition for the existence of kth moments(k$\geq$1) of the process with respect to the stationary distribution.