RISS 학술연구정보서비스

검색
다국어 입력

http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.

변환된 중국어를 복사하여 사용하시면 됩니다.

예시)
  • 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
  • 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
닫기
    인기검색어 순위 펼치기

    RISS 인기검색어

      검색결과 좁혀 보기

      선택해제

      오늘 본 자료

      • 오늘 본 자료가 없습니다.
      더보기
      • 무료
      • 기관 내 무료
      • 유료
      • A Novel Algorithm for Tracking and Forecasting Convective Cells Using Satellite Image Sequences

        Jia Liu,Chuancai Liu,Chao Ma,Danyu Qin,Furong Peng 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.2

        Accurate storm tracking and forecasting are essential parts of severe weather warning operations. The main problem of existing tracking and forecasting algorithms is unphysical split and merger of cloud clusters within the life cycle of Mesoscale Convective System (MCS). To address this issue, an automatic algorithm called TFCC (Tracking and Forecasting Convective Cells) is proposed for tracking and forecasting convective cells using infrared (IR) image sequences from geostationary meteorology satellite. In this paper, convective cells are utilized for tracking and forecasting instead of MCS because convective cells are stable portion in MCS. TFCC algorithm utilizes overlapping technique and uses a dynamic constraint technique based combinatorial optimization method. Moreover, displacement of the geometrical centroid is utilized to forecast the movement of convective cells. Case studies show that convective cells are tracked and forecasted efficiently in different phases of MCS lifecycle including genesis, maturity and dissipation using TFCC algorithm. Categorical statistics and contingency tables method applied to various case studies over China show that TFCC algorithm efficiently and accurately.

      연관 검색어 추천

      이 검색어로 많이 본 자료

      활용도 높은 자료

      해외이동버튼