응용통계연구 (The Korean Journal of Applied Statistics)

  • 제29권7호
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  • Pages.1445-1458
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  • 2016
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  • 1225-066X(pISSN)
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  • 2383-5818(eISSN)
한국통계학회 (The Korean Statistical Society)
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DCCA 방법으로 연결된 한반도의 기온 네트워크 분석

Temperature network analysis of the Korean peninsula linking by DCCA methodology

  • Min, Seungsik (Department of Natural Science, Korea Naval Academy)
  • 투고 : 2016.11.14
  • 심사 : 2016.12.23
  • 발행 : 2016.12.31
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초록

본 논문에서는 1976년부터 2015년까지 40년 간, 59개 지역 기온 시계열을 대상으로 degrended cross-correlation analysis(DCCA) 방법을 이용한 상관 계수를 도출하였다. 4년 단위의 평균기온, 최고기온, 최저기온 시계열을 분석하여 상관계수 값이 0.9 이상이면 단위 기간 동안 두 지역의 온도 상관성이 존재하는 것으로 판단하고, 두 지역 간의 연결선을 만드는 방식으로 네트워크를 구축하였다. 이후 네트워크 이론을 바탕으로 평균 경로 길이, 결집 계수, 유사성, 모듈성 등의 값들을 도출하였다. 그 결과, 기온 네트워크는 좁은 세상 성질을 만족하고, 유사성과 모듈성이 높은 네트워크임을 알 수 있었다.

This paper derives a correlation coefficient using detrended cross-correlation analysis (DCCA) method for 59 regional temperature series for 40 years from 1976 to 2015. The average temperature, maximum temperature, and minimum temperature series for 4 year units are analyzed; consequently, we estimated that a temperature correlation exists between the two regions during the unit period where the correlation coefficient is greater than or equal to 0.9; subsequently, we construct a network linking the two regions. Based on network theory, average path length, clustering coefficient, assortativity, and modularity were derived. As a result, it was found that the temperature network satisfies a small-worldness property and is a network having assortativity and modularity.

키워드

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