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计算机工程 ›› 2009, Vol. 35 ›› Issue (19): 263-265. doi: 10.3969/j.issn.1000-3428.2009.19.088

• 开发研究与设计技术 • 上一篇    下一篇

基于数据场的SVM技术在雷暴预报中的应用

马 婕,樊 玮,袁红玉   

  1. (中国民航大学计算机科学与技术学院,天津 300300)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-10-05 发布日期:2009-10-05

Application of SVM Technology Based on Data Field in Thunderstorm Report

MA Jie, FAN Wei, YUAN Hong-yu   

  1. (College of Computer Science and Technology, Civil Aviation University of China, Tianjin 300300)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-10-05 Published:2009-10-05

摘要: 针对天气预报中样本不平衡造成漏报率高的问题,提出一种基于数据场的C加权支持向量机(SVM)技术。该技术对不平衡天气数据进行分类,采用叠加数据场势值作为数据重采样依据,筛选出最利于SVM分类器学习的样本作为训练样本,结合C加权方法进行训练。实验结果证明,在样本数量较多且不平衡性显著的雷暴天气中,该技术能缩减训练集规模,减少漏报,提升预报系统的g-means值。

关键词: 支持向量机, 数据场, 不平衡数据集, 雷暴预报

Abstract: Aiming at decreasing the rate of missing report caused by the imbalanced samples in weather report, this paper proposes a C weighted Support Vector Machine(SVM) technology based on data field. The technology classifies the imbalanced weather data, uses superimpose data filed potential value according as the data sample, the best samples for the SVM learning are filtered for training C weighted SVM. Experimental result proves that it can shrink the scale of training set, decrease the rate of missing report, boost the g-means in thunderstorm weather which has too many numbers of sample and prominent imbalanced property.

Key words: Support Vector Machine(SVM), data field, imbalanced dataset, thunderstorm report

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