• 한국물환경학회지
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• 제33권1호
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• pp.40-50
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• 2017

We were interested in the long-term temporal and spatial variability trends of water quality. Trend tests such as the Seasonal and Regional Kendall tests and LOWESS (LOcally WEighted Scatter plot Smoother) have been recommended as outstanding tools for trend detection. In this study, we conducted four types of nonparametric trend tests (Seasonal and Regional Kendall tests, LOWESS, and flow-adjusted Seasonal Kendall). We aimed to identify water quality trends using the monthly data for five variables (BOD, COD, TN, TP, and flow) collected from 24 sites in the Nakdong River from August 2004 to December 2013. According to the Regional Kendall test, BOD, COD, and TN increased but TP decreased trend. The Seasonal Kendall test showed that BOD, TN, and TP remained constant at 62.5-83.3% of the sites. COD remained constant at 58.3% of the sites. LOWESS showed that TP gradually increased between 2007 and 2008, then decreased slowly at the Gumi, Geumhogang6, Daeam-1 and Milyanggang3 sites. BOD increased slightly between 2008 and 2009, and then decreased slowly at the Namgang4-1 site. Lastly, a flow-adjusted Seasonal Kendall test was conducted. There were different results between Seasonal Kendall and flow-adjusted Seasonal Kendall tests at 11 of the 24 sites. According to the results from six of the eleven sites, BOD increased at one site, showed no trends at three sited, and decreased at two sites. Each of COD, TN increased at two, one site. but TP decreased at two sites.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.581-585
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• 2010

This study introduced a Bayesian based frequency analysis in which the statistical trend seasonal analysis for hydrologic extreme series is incorporated. The proposed model employed Gumbel and GEV extreme distribution to characterize extreme events and a fully coupled bayesian frequency model was finally utilized to estimate design rainfalls in Seoul. Posterior distributions of the model parameters in both trend and seasonal analysis were updated through Markov Chain Monte Carlo Simulation mainly utilizing Gibbs sampler. This study proposed a way to make use of nonstationary frequency model for dynamic risk analysis, and showed an increase of hydrologic risk with time varying probability density functions. In addition, full annual cycle of the design rainfall through seasonal model could be applied to annual control such as dam operation, flood control, irrigation water management, and so on. The proposed study showed advantage in assessing statistical significance of parameters associated with trend analysis through statistical inference utilizing derived posterior distributions.

• Communications for Statistical Applications and Methods
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• 제7권2호
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• pp.513-523
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• 2000

The X-12-ARIMA program was utilized on the analysis of the time series trend on 76 Korean industrial activities data in order to ensure that the trading day effect adjustment as well as the seasonal effect adjustment is needed to extract the fundamental trend-cycle factors from various economic time series data. The trading day effect is strongly correlated with the activity of production and shipping but not with the activity of inventory. Furthermore, the industrial activities were classified with respect to the sensitivity on the tranding day effect.

• 한국농공학회논문집
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• 제57권6호
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• pp.153-162
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• 2015

In this study, we analyzed the trends of water quality along the main stream in Nakdong river basin using the recent data and seasonal Mann-Kendall test. Monthly averaged values of DO, BOD, SS, COD, TN, and TP from 1989 to 2014 for 14 stations (including 2 TMDLs stations) were used in the study. The trend analysis results showed that BOD and TP at most stations has decreasing temporal trend except a few stations while COD and SS showed increasing trend at most stations. Temporal trends in TN at 8 stations were found to be statistically significant and 5 of them showed increasing temporal trend. Temporally averaged BOD, COD, TN and TP were generally increasing as going downstream and the worst water quality were found at Goryeong and Hyunpung station. Overall, water quality of Nakdong river especially in COD, SS, and TN getting worse in time at most stations and as going downstream.

• 대한지리학회지
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• 제46권2호
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• pp.152-167
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• 2011

이 연구에서는 서울의 1941~1970년(가 기간)과 1971~2000년(나 기간)의 일 평년 기온에 조화분석을 적용하여 계절 추이를 산출, 이의 변화 양상을 살피고, 계절 추이와 변화에 영향을 미치는 요인을 조사하였다. 그 결과 겨울철의 가장 낮은 기온이 가 기간에는 1월초 중순에 나타났으나 나 기간에는 1월 하순~2월 초순에 나타나 계절 추이가 변화되었음을 나타냈다. 이러한 변화는 12월 27일~1월 20일(전기)의 기온이 보다 많이 상승한 반면 1월 21일~2월 9일(후기)의 기온이 보다 적게 상승하였기 때문에 나타났다. 가 기간의 일 평년값에 대한 전기와 후기의 기온 펀치는 1970년 이전에는 큰 차이가 없었으나 1971년 이후에 차이가 컸다. 전기의 경우 시베리아 고기압이 근래에 뚜렷하게 약화되면서 우리나라 부근의 북풍이 약화되어 서울의 기온이 많이 상승하였다. 반면 후기의 경우 시베리아 고기압이 근래에 약화되었으나 알류샨 저기압이 발달하여 우리나라 부근의 북풍은 크게 약화되지 않아 서울 기온이 많이 상승하지 않았다.

• 지능정보연구
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• 제19권1호
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• pp.1-17
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• 2013

본 연구에서는 시계열 예측을 위해 선형 모형과 비선형 모형의 하이브리드 모형 및 순수 모형의 성과를 비교 평가하였다. 이를 위해 5가지 서로 다른 패턴을 가지는 데이터를 생성하여 시뮬레이션을 진행하였다. 본 연구에서 고려한 선형 모형은 AR(autoregressive model)과 SARIMA(seasonal autoregressive integrated moving average model)이고 비선형 모형은 인공신경망(artificial neural networks model)과 GAM(generalized additive model)이다. 특히, GAM은 여러 장점에도 불구하고 시계열 예측을 위한 비선형 모형으로 기존 연구들에서는 거의 쓰이지 않았던 모형이다. 시뮬레이션 결과, seasonality를 가지는 시계열에 대해서는 AR 및 AR-AR 모형이, trend를 가지는 시계열에 대해서는 SARIMA 및 SARIMA와 다른 모형의 하이브리드 모형이 다른 모형에 비해 높은 성과를 보였다. 한편, 인공신경망과 GAM을 비교하면, 트렌드와 계절성이 더해진 시계열에 대해 SARIMA와 GAM의 하이브리드 모형이 거의 모든 노이즈(noise) 수준에 대해 높은 성과를 보인 반면, 노이즈 수준이 미미한 경우에 한해 SARIMA와 인공신경망의 하이브리드 모형이 높은 성과를 보였다.

• 한국물환경학회지
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• 제24권4호
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• pp.480-487
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• 2008

Spatial and temporal analyses of water qualities were performed for 11 monitoring stations located in Mangyung watershed in order to analyze the trends of monthly water quality data of Biochemical Oxygen Demand (BOD), Total Nitrogen (TN) and Total Phosphorus (TP) measured from 1995 to 2004. The long-term trends were analyzed utilizing Seasonal Mann-Kendall test, LOWESS and three-dimensional graphs were constructed with respect to distance and time. The graph can visualize spatial and temporal trend of the long-term water quality in a large river system. The results of trend analysis indicated that water quality of BOD and TN showed the downward trend. This quantitive and quantitative analysis is the useful tool to analyze and display the long-term trend of water quality in a large river system.

• 한국정보전자통신기술학회논문지
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• 제17권4호
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• pp.183-189
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• 2024

본 연구는 시계열 데이터를 효과적으로 예측하기 위해 데이터를 Seasonal-Trend Decomposition on Loess 을 통해 추세, 계절성, 잔차 성분으로 분해한 후 추세 성분에는 ARIMA, 계절성 성분에는 Fourier Series Regression, 잔차 성분에는 XGBoost를 적용하는 하이브리드 예측 모델을 제안하였다. 또한, ARIMA, XGBoost, LSTM, EMD-ARIMA, CEEMDAN-LSTM 모델을 포함한 성능 비교 실험을 수행하여 각 모델의 예측 성능을 평가하였다. 실험 결과, 제안된 하이브리드 모델은 MAPE, MAAPE, RMSE 지표에서 각각 3.8%, 3.5%, 0.35로 가장 좋은 평가 지표 값을 보이며 기존의 단일 모델보다 우수한 성능을 보였다.

• 한국환경과학회지
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• 제25권2호
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• pp.295-310
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• 2016

In this study, changes in daily temperature range were investigated using daily maximum and minimum temperatures of Busan and Daegu for last 81 years (1934-2014), and also characteristics of daily temperature range and seasonal fluctuations by urbanization were examined. First, elapsing changes showed a lower decreasing trend in Busan ($0.32^{\circ}C$) than Daegu ($1.28^{\circ}C$) for last 81 years. Daily temperature range showed the highest rise in winter in both Busan and Daegu. Second, daily temperature range due to urbanization showed that Busan had a pronounced decreasing trend before urbanization meanwhile Daegu showed the same trend after urbanization. On seasonal changes, the results of Busan showed a decreasing trend in summer before urbanization, and in autumn after urbanization. For Daegu, the results showed a decreasing trend in spring before urbanization, and in winter after urbanization. Seasonal fluctuations of Busan showed little difference in the pre and post-urbanization, except in winter and summer. There was large difference in daily temperature range in winter after urbanization, and in summer before the urbanization. The results in Daegu showed that there was decreasing trend of daily temperature range in all seasons after urbanization.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.183-183
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• 2017

Pan evaporation (Epan) is an important indicator of water and energy balance. Despite global warming, decreasing annual Epan has been reported across different continents over last decades, which is claimed as pan evaporation paradox. However, such trend is not necessarily found in seasonal data because the level of contributions on Epan vary among meteorological components. This study investigates long-term trend in seasonal pan evaporation from 1908 to 2016 across South Korea. Meteorological variables including air temperature (Tair), wind speed (U), vapor pressure deficit (VPD), and solar radiation (Rs) are selected to quantify the effects of individual contributing factor to Epan. We found overall decreasing trend in Epan, which agrees with earlier studies. However, mixed tendencies between seasons due to variation of dominant factor contributing Epan were found. We also evaluated the reference evapotranspiration based on Penman-Monteith method and compared this with Epan to better understand the physics behind the evaporation paradox.