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海洋中,在周期性潮流动力条件下,区域间的水体交换可近似认为满足马尔科夫性,利用该性质,可以快速有效地预测区域间的水交换问题。该文以渤海辽河口为研究区域,通过粒子跟踪方法得到区域间的概率传输矩阵,根据马尔科夫性,利用概率传输矩阵对辽河口水交换进行预测。研究表明,利用概率传输矩阵预测得到的水交换结果不仅与直接数值模拟吻合良好,还可极大缩减水体交换的计算模拟时间,因此对于长周期的预测,马尔科夫传输矩阵法比直接数值模拟更合理。
In the ocean, the exchange of water between regions can be approximately considered to be Markovian under the condition of periodic tidal momentum. With this property, the water exchange between regions can be predicted quickly and effectively. In this paper, the Liaohe Estuary in Bohai Sea is taken as the research area, and the probability transmission matrix between regions is obtained by the particle tracking method. According to the Markov property, the Liaohe Estuary water exchange is predicted by using the probability transfer matrix. The results show that the water exchange results predicted by the Probabilistic Transfer Matrix not only match well with the direct numerical simulation but also greatly reduce the computational simulation time of water exchange. Therefore, for long-period prediction, the Markov transfer matrix method is better than the direct numerical simulation More reasonable.