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      바람과 파랑 관측 자료의 통계정보 분석 = Statistical Analysis on the Wind and Wave Monitoring Data

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      https://www.riss.kr/link?id=A101823056

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      다국어 초록 (Multilingual Abstract)

      The analysis of the circular data having direction components like wind and wave data should be done using the directional statistics method because the characteristics of direction data are far different from the characteristics of linear data. Diverse statistical methods on the direction data have been suggested. The application of the methods, however, is limited because of the usability and accessibility. In this study, a variety of direction data-based statistical analysis of the wind and wave data sets are carried out to test the performance of the methods. The data used in this study is the wind and wave data of the Pohang buoy operated by the KMA and the analysis are carried by using the R packages. The analysis are focused on the estimation
      of the basic statistics and correlation coefficients between the data and the optimal smoothing of the data to identify the global variation patterns. The estimation results show that the basic statistics and correlations using linear and circular data sets computed with ease using the R functions supported by the R directional (or circular) data statistics packages. In addition, the optimal smoothing methods can be regarded as the suitable and reasonable methods to identify the typical variation patterns with optimum concept.
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      The analysis of the circular data having direction components like wind and wave data should be done using the directional statistics method because the characteristics of direction data are far different from the characteristics of linear data. Diver...

      The analysis of the circular data having direction components like wind and wave data should be done using the directional statistics method because the characteristics of direction data are far different from the characteristics of linear data. Diverse statistical methods on the direction data have been suggested. The application of the methods, however, is limited because of the usability and accessibility. In this study, a variety of direction data-based statistical analysis of the wind and wave data sets are carried out to test the performance of the methods. The data used in this study is the wind and wave data of the Pohang buoy operated by the KMA and the analysis are carried by using the R packages. The analysis are focused on the estimation
      of the basic statistics and correlation coefficients between the data and the optimal smoothing of the data to identify the global variation patterns. The estimation results show that the basic statistics and correlations using linear and circular data sets computed with ease using the R functions supported by the R directional (or circular) data statistics packages. In addition, the optimal smoothing methods can be regarded as the suitable and reasonable methods to identify the typical variation patterns with optimum concept.

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      목차 (Table of Contents)

      • 제목없음
      • 1. 서론
      • 2. 사용자료 및 분석방법
      • 3. 통계분석 결과 및 토의
      • 4. 결론 및 제언
      • 제목없음
      • 1. 서론
      • 2. 사용자료 및 분석방법
      • 3. 통계분석 결과 및 토의
      • 4. 결론 및 제언
      • 감사의 글
      • References
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      참고문헌 (Reference)

      1 정원무, "포항 연안 바람자료의 특성분석" 한국해안,해양공학회 27 (27): 190-196, 2015

      2 Breckling, J., "The analysis of directional time series: Applications to wind speed and direction" Springer-Verlag 238-, 1989

      3 Fisher, N. I., "Statistical analysis of circular data" Cambridge University Press 277-, 1993

      4 R Core Team, "R: A Language and Environment for Statistical Computing" R Foundation for Statistical Computing

      5 Agostinelli, C., "R package 'circular': Circular Statistics"

      6 "Korea Meteorological Administration"

      7 Wand, M.P., "Kernel Smoothing" Chapman & Hall/CRC 212-, 1995

      8 Wand M., "KernSmooth: Functions for Kernel Smoothing, R package"

      9 고동휘, "HeMOSU-1호 관측 자료를 이용한 해상풍속 산정오차 분석" 한국해안,해양공학회 24 (24): 326-332, 2012

      10 Bowers, J. A., "Directional statistics of the wind and waves" 22 : 13-30, 2000

      1 정원무, "포항 연안 바람자료의 특성분석" 한국해안,해양공학회 27 (27): 190-196, 2015

      2 Breckling, J., "The analysis of directional time series: Applications to wind speed and direction" Springer-Verlag 238-, 1989

      3 Fisher, N. I., "Statistical analysis of circular data" Cambridge University Press 277-, 1993

      4 R Core Team, "R: A Language and Environment for Statistical Computing" R Foundation for Statistical Computing

      5 Agostinelli, C., "R package 'circular': Circular Statistics"

      6 "Korea Meteorological Administration"

      7 Wand, M.P., "Kernel Smoothing" Chapman & Hall/CRC 212-, 1995

      8 Wand M., "KernSmooth: Functions for Kernel Smoothing, R package"

      9 고동휘, "HeMOSU-1호 관측 자료를 이용한 해상풍속 산정오차 분석" 한국해안,해양공학회 24 (24): 326-332, 2012

      10 Bowers, J. A., "Directional statistics of the wind and waves" 22 : 13-30, 2000

      11 Gaile, G.L., "Concepts and Techniques in Modern Geography No.25" Geo Abstracts 39-, 1980

      12 Barthelmie, J.P., "Coastal wind speed modelling for wind energy applications" 62 : 213-236, 1996

      13 Berens, P, "CircStat: A MATLAB toolbox for circular statistics" 31 (31): 1-21, 2009

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      유사연구자 (20) 활용도상위20명

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2022 평가예정 재인증평가 신청대상 (재인증)
      2019-04-24 학술지명변경 외국어명 : JCDP -> Journal of Coastal Disaster Prevention KCI등재
      2019-01-01 평가 등재학술지 선정 (계속평가) KCI등재
      2017-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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