摘要
介绍了BP人工神经网络的枯水径流预报方法,编制了锦屏一级水电站枯水径流预报方案。根据枯水径流预报方案的预报精度评定成果,总结了应用BP人工神经网络进行枯水径流预报的特点。研究表明基于BP人工神经网络的枯水径流预报方案能够满足水文情报预报规范,具有较好的实用性和可行性。
This paper introduced the low-flow forecasting method of BP artificial neural network and made a low-flow forecasting scheme for Jinping-Ⅰ Hydropower Station. According to the precision evaluation of the low-flow forecasting scheme, the characteristics to apply BP artificial neural network in the low-flow forecasting was summarized. The study show that the low-flow forecasting scheme based on BP artificial neural network can satisfy the hydrological forecasting standard, with its good practicability and feasibility.
出处
《水文》
CSCD
北大核心
2008年第3期33-36,13,共5页
Journal of China Hydrology
关键词
神经网络
水文预报
径流
枯水期
非线性
neural network
hydrological forecasting
runoff
low-flow period
nonlinear
