期刊
EXPERT SYSTEMS
卷 30, 期 5, 页码 398-402出版社
WILEY-BLACKWELL
DOI: 10.1111/j.1468-0394.2012.00644.x
关键词
hydrological variable; BP computation; flood forecast; mapping
资金
- National Natural Science Foundation of China [41171430]
Mappings of the stimuli effects and the input and output estimates of artificial neural networks (ANN) are obtained via combinations of nonlinear functions. This approach offers the advantages of self-learning, self-organization, self-adaptation, and fault tolerance as well as the potential for use in flood forecasting applications. Furthermore, the ANN technology allows the use of multiple variables in both the input and output layers. This capability is very important for flood calculation because the stage, discharge, and other hydrological variables often are functions of many influential variables. Herein, we propose a flood forecasting system with related application, based on ANN. This method offers better performance and efficiency.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据