• 환경영향평가
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• 제24권1호
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• pp.66-77
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• 2015

본 연구는 2001년 1월부터 2011년 12월까지 국가산단인 여수시 인구집단을 대상으로 일일 사망자료와 환경측정자료 및 기상자료를 이용하여 대기오염 물질 중 미세먼지($PM_{10}$)와 이산화황($SO_2$)이 일별 총 사망과 심혈관계 사망에 미치는 영향을 추정하였다. 대기오염과의 상관성분석은 S-Plus 프로그램을 이용한 generalized additive models(GAM)을 적용하여 시계열(Time-Series) 분석법을 실시하였다. 총 사망의 위해도는 65세 이상에서 $SO_2$의 농도가 11.67ppb(IQR) 증가함에 따라 5.0% 증가하였고, 심혈관계 사망의 위해도는 전체연령에서 8.6% 증가하는 것으로 나타났다. 지연효과는 총 사망과 심혈관계 사망의 모든 연령 그룹에서 사망 당일부터 7일 전 $SO_2$농도와 가장 관련성이 높은 것으로 분석되었다.

• The Journal of Asian Finance, Economics and Business
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• 제8권3호
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• pp.1113-1119
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• 2021

This study aims to determine the impact of the news coverage of the COVID-19 pandemic on the composite stocks' movement (IHSG) in Indonesia. This study used secondary data of daily time series with an observation range of March 2020-June 2020. This study used three main variables, namely, COVID-19 news, the daily price of a composite stock market index (IHSG), and interest rate. This study clarifies pandemic news into two forms to facilitate quantitative analysis, namely, good news and bad news. Both pandemic news conditions, which have been clarified, are then processed into the index and reprocessed along with two other variables using vector autoregressive (VAR). The results showed that the good news have a dominant effect on developing the composite stock price index (IHSG) in Indonesia during the COVID-19 pandemic. Although the good news dominates the composite stock price index (IHSG) movement in Indonesia, the bad news must also be anticipated. By implementing a series of macroeconomic policies that follow the conditions of the composite stock price index (IHSG) movements on the stock exchange floor, the bad news response can decrease the potential for a decline in investor confidence, so that the financial system's macroeconomic stability is maintained.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.18-21
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• 2005

The impact of the interannual climatic variability on the vegetation sensitively appears in the timing of phenological events such as green-up, mature, and senescence. Therefore, an accurate and temporally high-resolution NDVI dataset will be required for analysis on the interannual variability of the climate-vegetation relationship. We constructed a daily 8km NDVI dataset over Eurasia based on the 8km tiled data of Pathfinder A VHRR Land (PAL) Global daily product. Cloud contamination was successfully reduced by Temporal Window Operation (TWO), which is a method to find optimized upper envelop line of the NDVI seasonal change. Based on the daily NDVI time series from 1982 to 2000, an accurate (daily) interannual change of the phenological events will be analyzed.

• 응용통계연구
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• 제24권6호
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• pp.995-1006
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• 2011

A time series can be decomposed into simple components with a multiscale method. Empirical mode decomposition(EMD) is a recently invented multiscale method in Huang et al. (1998). It is natural to apply a classical prediction method such a vector autoregressive(AR) model to the obtained simple components instead of the original time series; in addition, a prediction procedure combining a classical prediction model to EMD and Hilbert spectrum is proposed in Kim et al. (2008). In this paper, we suggest to adopt principal component analysis(PCA) to the prediction procedure that enables the efficient selection of input variables among obtained components by EMD. We discuss the utility of adopting PCA in the prediction procedure based on EMD and Hilbert spectrum and analyze the daily worm account data by the proposed PCA adopted prediction method.

• 응용통계연구
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• 제29권3호
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• pp.505-512
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• 2016

본 연구에서는 금융시계열의 일간 변동성 측정을 위해 가중 융합 방법을 제안하고 있다. 고빈도(high frequency)자료에 기반을 둔 조정된 실현변동성을 계산하고 이를 참 값으로 간주하여 제안된 가중 융합 변동성에서 최적 가중치를 결정하는 과정을 서술하였다. 국내 KOSPI200자료의 1분 단위 고빈도 주가로부터 조정된 실현변동성을 구한 후 최적의 가중 융합 변동성을 제안해 보았다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권3호
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• pp.163-172
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• 2016

Electric load forecasting is essential for effective power system planning and operation. Complex and nonlinear relationships exist between the electric loads and their exogenous factors. In addition, time-series load data has non-stationary characteristics, such as trend, seasonality and anomalous day effects, making it difficult to predict the future loads. This paper proposes a locally-weighted polynomial neural network (LWPNN), which is a combination of a polynomial neural network (PNN) and locally-weighted regression (LWR) for daily shortterm peak load forecasting. Model over-fitting problems can be prevented effectively because PNN has an automatic structure identification mechanism for nonlinear system modeling. LWR applied to optimize the regression coefficients of LWPNN only uses the locally-weighted learning data points located in the neighborhood of the current query point instead of using all data points. LWPNN is very effective and suitable for predicting an electric load series with nonlinear and non-stationary characteristics. To confirm the effectiveness, the proposed LWPNN, standard PNN, support vector regression and artificial neural network are applied to a real world daily peak load dataset in Korea. The proposed LWPNN shows significantly good prediction accuracy compared to the other methods.

• 응용통계연구
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• 제22권6호
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• pp.1203-1214
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• 2009

본 논문에서는 시계열자료의 군집분석을 위해 시간영역과 진동수영역에서의 군집 방법들을 소개하고 각 방법들의 장단점에 대해 논의하였다. KOSPI 200에 속한 15개 기업의 일별 주가자료률 이용한 비교분석 결과 비모수적인 방법인 웨이블릿을 이용한 군집분석이 가장 좋은 결과를 보였다. 비정상 시계열자료의 경우 차분 보다는 EMD를 이용하여 추세를 제거하는 방법이 스펙트럼 밀도함수를 이용한 군집분석에 더 효율적이었다.

• Journal of the Korean Data and Information Science Society
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• 제25권1호
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• pp.155-167
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• 2014

본 연구는 기후파생상품의 가격결정 연구를 위한 중간과정으로서 우리나라 일별 평균기온에 대한 연속형 시계열 모형을 추정한다. 6개 광역도시를 대상으로 1954년 1월 1일부터 2010년 12월 31일까지의 57년간 일별 기온 시계열을 추세, 계절성, 불규칙 변동으로 구분하여 분석하였다. 특히 불규칙 성분은 연속형 자기회귀모형을 적용하였다. 분석결과, (1) 57년의 비교적 장기간 온도 시계열을 적용함으로써, 우리나라 선행연구의 결과와는 다르게 추세 성분이 통계적 유의성을 갖는 것으로 나타났다. 특히 추세성분의 기울기가 양의 부호를 가짐으로써 지구온난화의 추이가 우리나라에서 진행 중임을 보였다. (2) 추세와 계절성분이 제거된 불규칙성분에 대해 단위근 검정을 적용한 결과, 6개 광역시 모두에 대해 단위근이 없는 안정적인 것으로 나타났다. (3) 불규칙 성분에 대해 연속형 모형인 CAR모형을 적용한 결과, 차수가 3인 CAR(3)가 적합한 것으로 나타났으며 이러한 결과는 국외문헌의 결과와도 일치한다. 파생상품의 가격결정에는 기초자산의 연속형 시계열 모형의 개발이 가장 중요하므로 본 연구의 결과는 기후파생상품의 가격결정 연구에 활용될 수 있을 것이다.

• 여성건강간호학회지
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• 제12권2호
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• pp.142-149
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• 2006

Purpose: The purpose was to test the effects of self-hand massage with aroma oil on daily cigarette use, smoking craving, and depression of female high school student smokers who are attempting to quit smoking. Method: A convenience sampling of a non-equivalent control group time series was used. Female high school student smokers were assigned either to smoking cessation lecture only or to an intervention that involved a smoking cessation lecture and self -hand massage with aroma oil for 4 weeks. Lavender, Peppermint, and Bergamotte essence oils were used for massage. Result: There was a significant change in daily cigarette use and depression between the groups at three different times. Conclusion: It is promising that self-hand massage with aroma oil can be an effective adjunctive to decrease daily cigarette use and depression of female high school student smokers who are attempting to quit smoking.

• 농촌계획
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• 제22권1호
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• pp.13-23
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• 2016

There is a need to analyze unconfined groundwater behavior since the demand of groundwater use has been increasing. While unconfined groundwater temperature is tend to be affected by air temperature, it is hard to find an empirical study in South Korea. In this research, we try to determine the relationship between daily average air temperature and daily average groundwater temperature by time-sequential analysis of groundwater monitoring wells in Galshin basin in Yesan-Gun, Chungcheongnam-Do. In addition, models to estimate groundwater temperature from air temperature were developed. In this research 101-day moving average method with measured air temperature is used to estimate groundwater temperature. To verify the developed model, estimated values of average groundwater temperature with 101 moving average are compared to the measured data from September 10 2007 to September 9 2008. And, Nash-Stucliff Efficiency and Coefficient of Determination were 0.970 and 0.976, therefore it was concluded that the model allowing groundwater temperature estimation from air temperature is with reasonable applicability.