长江科学院院报2011，Vol.28Issue(1)：21-24,42,5.
一种基于BP神经网络的江河潮位短期预测
A Kind of Short-term Height-Prediction of Tidal Level of Rivers Based on BP Neural Network Model
何峰 1王瑞荣 1王建中 1薛安克 1谢发权 2何晓洪 2孙映宏2
作者信息
- 1. 杭州电子科技大学,杭州,310018
- 2. 杭州水文水资源监测总站,杭州,310014
- 折叠
摘要
Abstract
In comparison between the tide bore of rivers and the tide of ocean, the occurrence-time and height of the river tide bore has the same feature as the ocean tide; but the river tide bore is influenced more easily by astronomy, weather and other factors, so it has the instability that is different from the ocean tide; the tide level of the tidal bore is the comprehensive result influenced by all kinds of factors. Since the BP neural network can approach any non-linear function, a short-term prediction model of the tidal height has been constructed. Some historical tidal data, as a training sample, are used to train the model, and others are used to predict the tidal data. Finally,the validity and the feature of the prediction model have been verified.关键词
涌潮/BP神经网络/潮位/短期预测Key words
tide bore/ BP neural network/ tide level/ short-term prediction分类
地球科学引用本文复制引用
何峰,王瑞荣,王建中,薛安克,谢发权,何晓洪,孙映宏..一种基于BP神经网络的江河潮位短期预测[J].长江科学院院报,2011,28(1):21-24,42,5.
