Study of tide prediction method influenced by nonperiodic factors based on support vector machines  

作　　者：HE Shi-jun ZHOU Wenjun ZHOU Ruyan HUANG Dongmei 

机构地区：[1]College of information,Shanghai Ocean University,Shanghai 201306,China

出　　处：《Acta Oceanologica Sinica》2012年第5期160-164,共5页海洋学报（英文版）

基　　金：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.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 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] P731.23[自动化与计算机技术—控制科学与工程]