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Calculation and Measurement of Tide Height for the Navigation of Ship at High Tide Using Artificial Neural Network

机译:利用人工神经网络计算船舶航行潮高度的计算与测量

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Accurate tide height is crucial for the safe navigation of large deep-draft ships when they enter and leave the port. We have proposed an accurate forecasting method for the tide heights from the observation data and neural networks, which can easily calculate the tidal window period of large deep-draft shipsa?? navigation through long channels at high tide. Moreover, an artificial neural network is established for the tide height from the observation of tide heights before their current time node. For an ideal forecast, the neural network was optimized for one year with the tide height data of Huanghua Port. In case of large ships, their tidal characteristics of channels for are complex. A new method is proposed for the observation of multiple stations and artificial neural networks of each observation station. When ships are navigating through the port, the tide height is predicted from the observed data and forecast tide heights of multiple observation stations. Thus, a valid tidal window period is secured when the ships enter the port. Comparative analysis of the shipa??s tidal window period with that of the measured one can lead us to conclude that the forecasted data has a strong correlation with the measurement. So, our proposed algorithm can accurately predict the tide height and calculate the node timing when the ship enters and depart the port. Finally, these results can be applied for the safe navigation of large deep-draft ships when the port is at high tide.
机译:当他们进入并离开港口时,精确的潮汐高度对于大型船舶的安全导航至关重要。我们已经提出了一种精确的潮汐高度从观察数据和神经网络的预测方法,这很容易计算大型船舶的潮汐窗口时期?在高潮中通过长渠道导航。此外,从当前时间节点之前的潮汐高度观察到潮汐高度建立人工神经网络。对于理想的预测,通过黄花港的潮汐高度数据进行了一年的优化了神经网络。在大船的情况下,它们的潮汐特性是复杂的。提出了一种新方法,用于观察每个观察站的多个站和人工神经网络。当船舶通过端口导航时,从观察站的观察到的数据和预测潮汐高度预测潮汐高度。因此,当船舶进入端口时确保有效的潮汐窗口周期。船舶的比较分析与测量的潮汐窗口时期可以引导我们得出结论,预测数据与测量有很强的相关性。因此,我们所提出的算法可以准确地预测潮汐高度,并在船进入并离开端口时计算节点定时。最后,当端口处于高潮时,这些结果可以应用于大型船舶的安全导航。

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