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基于数据驱动模型的潮位和潮流预测方法研究

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Date of Publication:2022-10-10

Journal:北京理工大学学报

Issue:7

Page Number:864-868

ISSN No.:1001-0645

Abstract:The insufficiency of tidal level and current data near the ocean engineering waters may bring uncertainty for ocean engineering design and numerical model construction. To solve this problem, some of necessary prediction models are developed, including one site tidal level or current (current velocity and current direction) prediction model, multi-site tidal level or current prediction model, and tidal level-current prediction model. The construction of those models is based on the back propagation (BP) artificial neural network (ANN) and the properties of self-correlation of single site and cross-correlation among multi-sites or between tidal level and current. Field data under complex geography and hydrodynamic condition are used to validate the performance of the presented data-driven models. It is indicated that the nonlinear mapping relation between tidal level and tidal current can be reproduced by those models. The comparison between the numerical results and field-data verifies that the developed models have the advantages of simple structure and good precision.

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