• ALGAE
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• 제27권3호
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• pp.215-224
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• 2012

Growth dynamics of the seagrass, Zostera marina were examined at the two stations (Myungju and Dagu) in Jindong Bay on the southern coast of Korea. Eelgrass leaf productivities, underwater irradiance, water temperature, dissolved inorganic nitrogen (DIN) in water column and sediments, and tissue carbon (C) and nitrogen (N) content were monitored monthly from March 2002 to January 2004. Underwater irradiance fluctuated highly without a clear seasonal trend, whereas water temperature showed a distinct seasonal trend at both study stations. Water column DIN concentrations were usually less than $5{\mu}M$ at both study sites. Sediment pore water $NH_4{^+}$ and $NO_3{^-}+NO_2{^-}$ concentrations were higher at the Myungju site than at the Dagu site. Eelgrass leaf productivity at both study sites exhibited a distinct seasonality, increasing during spring and decreasing during summer. Seasonal variation of eelgrass productivity was not consistent with seasonal patterns of underwater irradiance, or water temperature. Eelgrass tissue C and N content at both study sites also showed significant seasonal variations. Relationships between tissue C and N content and leaf productivities exhibited usually negative correlations at both study sites. These negative correlations implied that the growth of Z. marina at the study sites was probably limited by C and N supplies during the high growth periods.

• 응용통계연구
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• 제29권1호
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• pp.193-203
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• 2016

본 논문은 ICT기반 시장에서의 수요관리시스템에서의 핵심 요소인 전력 수요 예측을 위하여, 전체 사용량을 기반으로 예측 하는 방식이 아닌, 시계열 기반 군집분석을 통한 군집별 예측량의 결합을 실시하였다. 시계열 군집 분석 방법으로서 Periodogram 기반의 정규화 군집분석, 예측 기반의 군집분석, DTW(Dynamic Time Warping)를 이용하여 군집화를 시도하였으며, 군집 별 수요예측 모형으로서 DSHW(Double Seasonal Holt-Winters) 모형, TBATS(Trigonometric, Box-Cox transform, ARMA errors, Trend and Seasonal components) 모형, FARIMA(Fractional ARIMA) 모형을 사용하여 예측을 실시하였다. 전체 사용량을 기반으로 예측 하는 방식이 아닌, 군집분석을 통한 군집별 예측량의 결합이 더 낮은 MAPE로 나타남에 따라 우수한 예측 방법으로 판단되었다.

• 한국환경보건학회지
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• 제22권2호
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• pp.124-129
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• 1996

In order to investigate the deposition chara.cteristics of water-soluble ionic components in dustfall in Kwangju city, dustfall samples were collected by deposit jar for one year from December 1992 to November 1993. The depositjon amount of dustfall and water-soluble ionic components ($SO_4^{2-}, NO_3^-, Cl^-, NH_4^+, Na^+, Ca^{2+}, Mg^{2+}, K^+$) were measured. The total deposition amount of dustfall was 10.0 ton/$km^2$/month and showed seasonal trend of Summer and Spring > Fall and Winter. The total deposition amounts of water-soluble components showed 2.41 ton/$km^2$/month and seasonal trend of Summer > Fall > Spring > Winter. Deposition amount of $SO_4^{2-}$ was 0.99 ton/$km^2$/month which makes up 41% of water-soluble components. The deposition amounts of dustfall and watersoluble components according to the sampling points were approximately similar to each other. From this result, it can be estimated that the deposition amounts of dustfall and water-soluble components in dustfall were more influenced by the seasonal variation than the regional emission characteristics of pollution source. The content of each ionic component to the deposition amount of water-soluble components showed in order of $SO_4^{2-} > Cl^- > NH_4^+ > Na^+ > Ca^{2+} = K^+ > NO_3^- > Mg^{2+}$ respectively.

• 한국대기환경학회지
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• 제19권2호
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• pp.231-245
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• 2003

Hourly PM$_{10}$ concentrations measured at 11 sites in Seoul and 10 sites in the large cities over South Korea for the period from March 1995 to February 2000 are analyzed to examine annual trend and monthly variations of the PM$_{10}$ concentrations. Further analysis has been carried out by using the one year data from March 1999 to February 2000 to see the seasonal variation, diurnal variation and weekly variation of the seasonally averaged PM$_{10}$ concentrations at each site. Weekly variations of the CO concentrations at the same sites for the same one year period are compared with that of the PM$_{10}$ concentration. There is no significant annual trend in the variation of the PM$_{10}$ concentration at all the sites analyzed. The seasonal and monthly mean concentrations show a minimum concentration in summer and alternative maximum concentration in spring and winter for most sites. The diurnal variation of the seasonally averaged mean PM$_{10}$ concentrations is strongly affected by traffic loads and meteorological conditions. The weekly variation of seasonal averaged concentrations of CO and PM$_{10}$ shows a high concentration for weekdays in spring, autumn and winter while high concentration for weekends in summer.nds in summer.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2015년도 추계 학술논문 발표대회
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• pp.192-193
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• 2015

Construction Cycle Trend Survey, which survey total value of orders and realized amounts monthly, is a valuable statistics that used to quick grasp or forecast the trend of domestic construction business. In recent periodical survey quality diagnoses, few professional users named a problem that Construction Cycle Trend Survey could not get together with the current state of the construction industry. This study examined weather Construction Cycle Trend Survey reflects the economic sentiment of construction business or not. Paired t test was performed between Construction Cycle Trend Survey and Construction Business Survey Index (CBSI), and significant differences were verified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4887-4907
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• 2017

Accurate traffic flow forecasting is critical to the development and implementation of city intelligent transportation systems. Therefore, it is one of the most important components in the research of urban traffic scheduling. However, traffic flow forecasting involves a rather complex nonlinear data pattern, particularly during workday peak periods, and a lot of research has shown that traffic flow data reveals a seasonal trend. This paper proposes a new traffic flow forecasting model that combines seasonal relevance vector regression with the hybrid chaotic simulated annealing method (SRVRCSA). Additionally, a numerical example of traffic flow data from The Transportation Data Research Laboratory is used to elucidate the forecasting performance of the proposed SRVRCSA model. The forecasting results indicate that the proposed model yields more accurate forecasting results than the seasonal auto regressive integrated moving average (SARIMA), the double seasonal Holt-Winters exponential smoothing (DSHWES), and the relevance vector regression with hybrid Chaotic Simulated Annealing method (RVRCSA) models. The forecasting performance of RVRCSA with different kernel functions is also studied.

• 한국수산과학회지
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• 제43권5호
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• pp.510-520
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• 2010

This study investigated the community structure and seasonal variation of the fish assemblages on Jangbong tidal flat, Incheon, Korea. Fish were collected monthly using a small otter trawl from November 1999 to January 2001. Thirty-six fish species were recorded, with a mean density of 185 individuals and biomass of 2,594.3 gWWt. The most abundant species by number were Johnius grypotus (23.7%), Acanthogobius hasta (17.8%), and Cynoglossus joyneri (10.7%), while the dominant species by catch weight were Acanthogobius hasta (21.2%), Sebastes schlegeli (16.2%), J. grypotus (14.0%), and C. joyneri (10.8%). Cluster analysis and non-metric multi-dimensional scaling (nMDS) were applied to assess the seasonal fluctuation in the fish assemblages. Based on the result of the cluster analysis and nMDS ordination, the faunal group could be divided into cold- and warm-water specialist groups. The cold-water specialists included A. hasta, Acanthogobius luridus, Triaenopogon barbatus, Tridentiger trigonocephalus, and Liza haematocheila. The warm-water specialists were J. grypotus, C. joyneri, S. schlegeli, and Hexagrammos otakii. In conclusion, the community structure showed a distinct seasonal trend, which seemed to be related to the seasonal fluctuations in water temperature.

• 응용통계연구
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• 제16권1호
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• pp.15-31
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• 2003

Lake Ontario에서 수년간 측정된 실제 생물학적 지표 자료의 각 변수에 대하여 관찰시점의 불규칙성과 의존성을 고려한 탐색적 분석모형의 수립과정에 대하여 연구하였다. 이 상점을 제거한 후 trend와 seasonal component를 수정 한 선형 모형으로부터 잔차를 계산하고 이로부터 variogram과 correlogram을 그려보았다.

• 한국수자원학회논문집
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• 제47권7호
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• pp.643-656
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• 2014

우리나라 전국 43개 기후관측지점을 대상으로 기후 건조지수 추세의 시간적(월별, 계절별, 연별) 동질성을 분석하였다. 또한 43개 기후관측지점을 9개 지역으로 구분하여 이들 각 지역과 전체 9개 지역을 대상으로 시간적 및 지역적인 기후 건조지수 추세의 동질성 유무와 추세정도를 파악하였다. 분석을 위해 43개 기후관측지점의 월별, 계절별 그리고 연별 건조지수를 강수량과 FAO Penman-Monteith식으로 계산된 잠재증발산량으로부터 산정하였다. 또한 산정된 지수를 이용하여 Mann-Kendall 추세분석을 실시하였고, 추세분석 결과(Z scores)를 이용하여 기후 건조지수 추세의 시간적 및 지역적 동질성 분석을 실시하였다. 분석결과에 의하면 9개 각 지역과 전체 9개 지역에서 기후 건조지수 추세는 시간적 및 지역적으로 동질성이 있는 것으로 나타났으나, 추세의 동질성 정도 및 추세정도는 시간적 및 지역적으로 다른 양상을 보였다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2001년도 추계학술대회 논문집
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• pp.111-116
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• 2001

This paper introduces how to adopt the X-12-ARIMA to decompose the railway passenger demand of the Korea National Railroad Especially, selecting on proper filters is focused. The trend filter is identical to the low pass filter in the signal Processing field, and so the seasonal filter is to band pass filter too. Some considerations, selecting a filter, are provided from the view-point of the spectrum analysis. The technique introduced in this paper will be adopted to the project that is to develope the forecasting system of Korea railway passenger demand which is a part of the high speed rail information system.