• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Natural hazards and earth system sciences >Hybrid neural networks in rainfall-inundation forecasting based on a synthetic potential inundation database
【24h】

Hybrid neural networks in rainfall-inundation forecasting based on a synthetic potential inundation database

机译：基于综合潜在淹没数据库的混合神经网络在降雨淹没预测中的应用

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This study attempts to achieve real-time rainfall-inundation forecasting in lowland regions, based on a synthetic potential inundation database. With the principal component analysis and a feed-forward neural network, a rainfall-inundation hybrid neural network (RiHNN) is proposed to forecast 1-h-ahead inundation depth as hydrographs at specific representative locations using spatial rainfall intensities and accumulations. A systematic procedure is presented to construct the RiHNN, which combines the merits of detailed hydraulic modeling in flood-prone lowlands via a two-dimensional overland-flow model and time-saving calculation in a real-time rainfall-inundation forecasting via ANN model. Analytical results from the RiHNNs with various principal components indicate that the RiHNNs with fewer weights can have about the same performance as a feed-forward neural network. The RiHNNs evaluated through four types of real/synthetic rainfall events also show to fit inundation-depth hydrographs well with high rainfall. Moreover, the results of real-time rainfall-inundation forecasting help the emergency manager set operational responses, which are beneficial for flood warning preparations.
机译：本研究试图基于合成的潜在淹没数据库，实现低地地区的实时降雨淹没预报。通过主成分分析和前馈神经网络，提出了一种降雨-淹没混合神经网络（RiHNN），可以利用空间降雨强度和累积量，在特定的代表性位置以水文图形式预报提前1小时的淹没深度。提出了一个系统的程序来构造RiHNN，该程序结合了通过二维陆上水流模型在洪水多发的低地进行详细水力建模的优点以及在通过ANN模型进行的实时降雨淹没预测中节省的时间。具有各种主要成分的RiHNN的分析结果表明，权重较小的RiHNN可以具有与前馈神经网络大致相同的性能。通过四种实际/合成降雨事件进行的RiHNN评估也表明，高降雨条件下的淹没深度水文图非常合适。此外，实时降雨淹没预报的结果有助于紧急情况管理人员制定操作响应，这对于洪水预警的准备工作是有利的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号