基于BP神经网络和三次样条插值法的感潮河段水位预报OA
Water level forecast of tidal river sections based on the BP neural network and cubic spline interpolation method
针对常熟水利枢纽外江侧为感潮河段,提出一种基于BP神经网络和三次样条插值结合的感潮河段水位预报方法.结果表明,潮位预报预见期为1d与2d时,模型绝对误差分别为0.06 m与0.18 m,合格率分别为87.5%与70.9%,满足《水文情报预报规范》所规定的发布正式预报要求;预见期为3d时,模型绝对误差与合格率分别为0.28 m与61.4%,满足参考性预报要求.水位预报预见期为1d时,模型绝对误差为0.07 m,适用于枢纽的精细化调度;预见期为2d与…查看全部>>
A water level prediction method for tidal river sections on the outer river side of Changshu Water Conservancy Hub is proposed based on a combination of BP neural network and cubic spline interpolation.The results show that when the forecast period for tidal level forecast is 1 day and 2 days,the absolute errors of the model are 0.06 m and 0.18 m,respectively,and the qualification rates are 87.5%and 70.9%,meeting the requirements for issuing formal forecasts…查看全部>>
季俊杰;徐瑶瑶;闻昕;纪凯文;马晶洁
江苏省河道管理局,江苏南京 210029江苏省太湖地区水利工程管理处,江苏苏州 215100河海大学水利水电学院,江苏南京 210098河海大学水利水电学院,江苏南京 210098河海大学水利水电学院,江苏南京 210098
水利科学
感潮河段水位预报水利枢纽
tidal river sectionwater level forecastwater conservancy hub
《江苏水利》 2024 (7)
33-37,46,6
江苏省水利科技项目(2020065)
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