首页    期刊浏览 2025年04月30日 星期三
登录注册

文章基本信息

  • 标题:Combination of XGBoost and PPLK method for improving the precipitation nowcasting
  • 本地全文:下载
  • 作者:Xiongfa Mai ; Haiyan Zhong ; Ling Li
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2022
  • 卷号:355
  • 页码:1-5
  • DOI:10.1051/matecconf/202235503039
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:The Precipitation nowcasting can provide high-resolution forecasts of rainfall and hydrometeors in 2 hours and play an important role in risk management for flash flood and debris flow events, but it is a very challenge work. This study proposed a new method which combine of XGBoost method and the PPLK model for precipitation nowcasting (XGB-PPLK). The proposed method was assessed in four different types of storms, and the experimental results show that the XGB-PPLK can improve the probability of detection (POD), as while as reducing the normalized mean square error (NMSE), and maintain the basically equivalent false-alarm ratio (FAR).
  • 关键词:XGBoost;PPLK;Precipitation Nowcasting
国家哲学社会科学文献中心版权所有