• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3381-3388
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• 2012

This research is to find out the method appropriate for the forecasting of passennger demand using seasonal ARIMA model and efficient operation in Jeju National Airport. Time series monthly data for the investigation were collected ranging from January 2003 to December 2011. A total of 108 observations were used for data analysis. Research findings showed that the multiplicative seasonal ARIMA(0.1.2)(0.1.1)12 model is appropriate model. The number of passengers in Jeju National Airport will continue to rise, it was expected to surpass 20 million people.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.14-14
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• 2018

세계의 여러 국가에서 과거 발생했던 강수의 통계적 특성에서 벗어나는 극치사상이 빈번하게 관측되고 있다. 이와 같은 현상에 가장 큰 영향을 미치고 있는 요인중 하나는 지구온난화이며 실제 산업화 이후 온실가스의 증가와 더불어 극한 기상현상의 발생 빈도가 증가하였다. 현재 예상치 못한 수문사상의 발생으로 인해 수자원관리에 있어서 많은 어려움을 겪고 있으며, 특히 호우사상은 막대한 인명 및 사회적 피해를 야기하고 있다. 우리나라의 경우 계절적 특징으로 여름철에 강수가 집중되는 양상을 보이고 있으며 따라서 여름철 강수량을 예측하여 호우에 대한 대비책을 마련해야한다. 계절강수 예측은 수문, 산림, 식품, 등을 포함한 사회 경제적 파급 효과가 매우 크지만 아직 신뢰성 있는 예측은 어려운 상태이다. 또한, 발생 강도와 빈도가 큰 극한 강우는 주로 짧은 시간에 걸쳐 발생하기 때문에 예측하기가 어렵다. 최근 다양한 분야의 연구에서 AO, NAO, ENSO, PDO등과 같은 외부적 요인이 수문학적 빈도를 변화시킨다고 알려지고 있어 본 연구에서는 Bayesian 통계기법을 이용한 비정상성 빈도해석모형을 토대로 외부 기상인자에 의한 변동성을 고려할 수 있는 계절강수량 예측모형을 구축한 후 산정된 결과를 입력 자료로 하여 극치강수량을 추정할 수 있는 비정상성 Four - Parameter (4P)-Beta분포를 이용한 알고리즘을 개발하여 직접적으로 일단위 이하의 극치강수량을 상세화 시킬 수 있는 모형으로 확장하여 이를 통해 기상변동성을 다양한 시간규모에서 고려하기 위한 정보로 활용하고자 하였다.

• Convergence Security Journal
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• v.22 no.3
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• pp.79-86
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• 2022

Voice phishing is a cyber crime in which fake financial institutions, the Public Prosecutor's Office, and the National Police Agency are impersonated to find out an individual's Certification number and credit card number or withdraw a deposit. Recently, voice phishing has been carried out in a subtle and secret way. Analyzing the trend of voice phishing that occurred in '18~'21, it was found that there is a seasonality that occurs rapidly at a time when the movement of money is intensifying in the trend of voice phishing, giving ambiguity to time series analysis. In this research, we adjusted seasonality using the X-12 seasonality adjustment methodology for accurate prediction of voice phishing occurrence trends, and predicted the occurrence of voice phishing in 2022 using the ARIMA model.

• 한국생태학회:학술대회논문집
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• 1999.05a
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• pp.67.1-67.1
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• 1999

• Proceedings of the Korea Air Pollution Research Association Conference
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• 1988.12a
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• pp.33-34
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• 1988

• 대한지구과학교육학회:학술대회논문집
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• 2010.08a
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• pp.21-21
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• 2010

• Water for future
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• v.50 no.8
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• pp.70-82
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• 2017

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.287-288
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• 2004

• Proceedings of the Zoological Society Korea Conference
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• 1999.10b
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• pp.128.2-128
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• 1999

• Journal of the Korean Geographical Society
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• v.43 no.1
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• pp.36-51
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• 2008

As the global warming has influenced on various sectors including agriculture, forestry, fisheries and health, it is essential to project more accurate future climate for an assessment of climate change impact and adaptation strategy. This study examines spatial distribution of onset dates and durations of season decomposed by applying a lowpass filtering using observed 30-year (1971-2000) data and projected 2090s data based on the IPCC SRES A1B emission scenario in South Korea. In general, the distributions of spring and winter onset date are affected by latitudes, topography and proximity to oceans. However, onset dates of summer and autumn are a little affected by proximity to oceans and topography than by latitudes. In the 2090s (2091-2100), the onset dates of spring begin about 40 days earlier and the onset dates of summer begin 25-30 days earlier as compare with present time. On the other hand, the onset dates of winter begin about 50 days later in the southern and eastern coastal area and in the southern inland. The onset dates of autumn begin about 20 days later. In the 2090s, summer duration is longer and winter duration is shorter as compare with present time at southern and eastern coastal area.