【摘要】 海洋环境中,精确预测潮汐是关系到建筑物和人类活动的重要工作.利用人工神经网络进行单测站潮位和多测站对应潮位预测,并结合潮汐现象的特点,提出了在预测之前有针对性的数据处理分析方法——周期分析概念,并将其应用到实际的潮位预测当中,实例证明这种方法可以解决潮位预测中存在的时滞问题,提高了预测的精度.同时根据不同测站潮汐数据之间的相关性,以及潮汐数据规律性较强这一特点,进行了不同潮位测站之间的对应潮位预测,取得了很好的结果.更多还原

【Abstract】 In ocean environment,accurate tide forecasting is a kind of significant work for constructions and human activities.Artificial neural networks(ANN) model is presented for forecasting the tidal-level using limited field data of one site or multi-sites.Based on the characteristics of tide time series,a new conception-the periodicity analysis on tide data is proposed and applied to the testing of the performance of ANN model.The numerical results indicate that this method is efficient to solve the time lag problem existing in previous ANN models.Based on the pertinence of tidal-level data among different tidal gauge stations,a new tide forecasting method-site to site is developed,and the numerical results agree well with field data.更多还原