Modular Tidal Level Short-Term Forecasting based on BP Neural Networks

摘要：

　　Accurate and real-time tidal level forecasting information is significant for ensuring safety of navigation and port operation.The conventional method for tidal level forecasting is the harmonic analysis method which only considers the effect of celestial bodies to tidal level.However,the cause of tidal level change is intricate which can be also influenced by environmental factors such as wind,rainfall and air pressure.Therefore the harmonic method alone can not adapt all parts well.In order to improve the precision of tidal level prediction,a modular prediction mechanism is proposed which contains the harmonious analysis module for predicting time-varying portion causing by celestial bodies and the BP neural network module for predicting the residual portion causing by other elements.To further determine whether the modular prediction mechanism model possess good effectiveness and efficiency for tidal level forecasting,tidal level data of Port Isabel have been chosen as the test sample,and the prediction results adapt well with the field data.

关键词： Tidal level forecasting BP neural network harmonious analysis modular prediction mechanism

作者: ZHANG Anran YIN Jianchuan HU Jiangqiang YU Chao

作者单位: Navigation College,Dalian Maritime University,Dalian Liaoning 116026,P.R.China

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 5037-5042

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）