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An elastic graph dynamic link model for tropical cyclone pattern recognition

机译:用于热带气旋模式识别的弹性图动态链接模型

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In this paper, an elastic graph dynamic link model (EGDLM) is proposed to automate the satellite interpretation process (Dvorak technique) and provide an objective analysis for tropical cyclones. The method integrates dynamic link architecture (DLA) for neural dynamics and the active contour model (ACM) for contour extraction of tropical cyclone (TC) patterns. Using satellite pictures provided by National Oceanic and Atmospheric Administration (NOAA), 145 tropical cyclone cases from the period between 1990 to 1998 were extracted for the study. An overall correct rate for TC classification was found to be above 95%. For hurricanes with distinct "eye" formation, the model reported a deviation within 3 km from the "actual eye" location, which was obtained from the aircraft measurement of minimum surface pressure by reconnaissance.
机译:本文提出了一种弹性图动态链接模型(EGDLM)来自动化卫星解释过程(Dvorak技术),并为热带气旋提供客观的分析。该方法集成了用于神经动力学的动态链接体系结构(DLA)和用于热带气旋(TC)模式轮廓提取的活动轮廓模型(ACM)。利用美国国家海洋和大气管理局(NOAA)提供的卫星图片,提取了1990年至1998年之间的145个热带气旋病例用于研究。发现TC分类的总体正确率高于95%。对于具有明显“眼”形的飓风,该模型报告了距“实际眼”位置3公里以内的偏差,这是通过侦察飞机对最小表面压力的测量得出的。

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