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Study of tide prediction method influenced by nonperiodic factors based on support vector machines
作者姓名:HE Shijun  ZHOU Wenjun  ZHOU Ruyan  HUANG Dongmei
作者单位:College of information, Shanghai Ocean University, Shanghai 201306, China;College of information, Shanghai Ocean University, Shanghai 201306, China;College of information, Shanghai Ocean University, Shanghai 201306, China;College of information, Shanghai Ocean University, Shanghai 201306, China
基金项目:The Shanghai Committee of Science and Technology of China under contract No.10510502800;the Graduate Student Education Innovation Program Foundation of Shanghai Municipal Education Commission of China;the National Key Science Foundation Research “973” Project of the Ministry of Science and Technology of China under contract No.2012CB316200.
摘    要:Harmonic analysis, the traditional tidal forecasting method, cannot take into account the impact of noncyclical factors, and is also based on the BP neural network tidal prediction model which is easily limited by the amount of data. According to the movement of celestial bodies, and considering the insufficient tidal characteristics of historical data which are impacted by the nonperiodic weather, a tidal prediction method is designed based on support vector machine (SVM) to carry out the simulation experiment by using tidal data from Xiamen Tide Gauge, Luchaogang Tide Gauge and Weifang Tide Gauge individually. And the results show that the model satisfactorily carries out the tide prediction which is influenced by noncyclical factors. At the same time, it also proves that the proposed prediction method, which when compared with harmonic analysis method and the BP neural network method, has faster modeling speed, higher prediction precision and stronger generalization ability.

关 键 词:tidal  prediction  support  vector  machines  celestial  motion  law  harmonic  analysis  BP  neural  network  nonperiodic  factors
收稿时间:2011/8/15 0:00:00
修稿时间:2012/3/30 0:00:00

Study of tide prediction method influenced by nonperiodic factors based on support vector machines
HE Shijun,ZHOU Wenjun,ZHOU Ruyan,HUANG Dongmei.Study of tide prediction method influenced by nonperiodic factors based on support vector machines[J].Acta Oceanologica Sinica,2012,31(5):160-164.
Authors:HE Shijun  ZHOU Wenjun  ZHOU Ruyan and HUANG Dongmei
Institution:College of information, Shanghai Ocean University, Shanghai 201306, China
Abstract:Harmonic analysis,the traditional tidal forecasting method,cannot take into account the impact of noncyclical factors,and is also based on the BP neural network tidal prediction model which is easily limited by the amount of data.According to the movement of celestial bodies,and considering the insufficient tidal characteristics of historical data which are impacted by the nonperiodic weather,a tidal prediction method is designed based on support vector machine (SVM) to carry out the simulation experiment by using tidal data from Xiamen Tide Gauge,Luchaogang Tide Gauge and Weifang Tide Gauge individually.And the results show that the model satisfactorily carries out the tide prediction which is influenced by noncyclical factors.At the same time,it also proves that the proposed prediction method,which when compared with harmonic analysis method and the BP neural network method,has faster modeling speed,higher prediction precision and stronger generalization ability.
Keywords:tidal prediction  support vector machines  celestial motion law  harmonic analysis  BP neural network  nonperiodic factors
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