江苏水利Issue(7)：33-37,46,6.
基于BP神经网络和三次样条插值法的感潮河段水位预报
Water level forecast of tidal river sections based on the BP neural network and cubic spline interpolation method
摘要
Abstract
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 as stipulated in the"Hydrological Information Forecasting Specification";When the forecast period is 3 days,the absolute error and qualification rate of the model are 0.28 m and 61.4%,respectively,meeting the reference forecast requirements.When the forecast period for water level is 1 day,the absolute error of the model is 0.07 m,which is suitable for the refined scheduling of the hub;When the forecast period is 2 days and 3 days,the absolute errors of the model are 0.13 m and 0.18 m,respectively,which can provide water level information reference for the operation of the hub.关键词
感潮河段/水位预报/水利枢纽Key words
tidal river section/water level forecast/water conservancy hub分类
建筑与水利引用本文复制引用
季俊杰,徐瑶瑶,闻昕,纪凯文,马晶洁..基于BP神经网络和三次样条插值法的感潮河段水位预报[J].江苏水利,2024,(7):33-37,46,6.基金项目
江苏省水利科技项目(2020065) （2020065）
