江河涌潮与海洋潮汐相比较，其潮位和潮时有着与海洋潮汐规律相同的一面，但它与海洋潮汐所不同的是，其更容易受到天文、气象等因素的影响，有着异于海洋潮汐的不稳定性。涌潮的潮位值变化就是各种因素综合结果的表现。通过借助 BP 神经网络可以逼近任意非线性函数的能力和特点，构建一个用于短期预测潮水潮位的模型，利用一小部分潮位的历史数据作为训练样本对构建出的 BP 神经网络模型进行样本训练，用其它的潮位历史数据对模型进行了预测验证。模型验证结果表明，这个 BP 神经网络预测模型能够对潮水潮位进行有效的短期预测，其性能指标符合要求。

In comparison between the tide bore of rivers and the tide of ocean, the occurrence  time and height of the river tide bore has the same feature as the ocean tide ； but the river tide bore is influenced more easily by astronomy, weather and other factors, so it has the instability that is different from the ocean tide ； the tide level of the tidal bore is the comprehensive result influenced by all kinds of factors. Since the BP neural network can approach any non-linear function, a short-term prediction model of the tidal height has been constructed. Some historical tidal data, as a training sample, are used to train the model, and others are used to predict the tidal data. Finally, the validity and the feature of the prediction model have been verified.