基于粗糙集理论的强对流回波识别

Zhiying Lu, Jian-Pei Wang
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引用次数: 1

摘要

本文采用雷达反射率图像、一系列天气条件和图像处理技术,从雷达图像中提取强对流回波(冰雹、暴雨)特征。获取面积、垂直整合液态水(VIL)、垂直整合液态水密度(VTLD)等特征,构建特征数据库。利用粗糙集理论挖掘有用的规则,形成知识库,从而建立了识别强对流天气的客观模型。最后利用客观模型对冰雹和暴雨进行了识别和预报。试验结果表明,冰雹和暴雨的3个特征属性具有有效的识别效果,预测精度为76.25%,满足初步分类的要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Strong convective echoes identification based on rough set theory
In this paper radar reflectivity image, a range of weather conditions, and image processing technology were applied to extract features of strong convective echoes (hail, torrential rain) from the radar images. Area, vertically integrated liquid water (VIL), vertically integrated liquid water density (VTLD) and other features were obtained to construct the characteristic database. Rough set theory was used to dig out useful rules that can form the knowledge base, thereby the objective model of identifying strong convection weather was established. Finally the objective model was used to identify and forecast hail and torrential rain. Test results indicated that the three features properties of hail and torrential rain had effective recognition results, and prediction accuracy was 76.25% which meets the requirements of preliminary classification.
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