Beach profile simulation under sediment transport at shore lines of the Baltic Sea by neural networks and discrete models

通过神经网络和离散模型模拟波罗的海海岸沉积物输送下的海滩剖面

• 批准号: 5369349
• 负责人: Professor Dr.-Ing. Klaus-Peter Holz
• 金额: --
• 依托单位: Laboratory for Mathematical Modelling of Environmental and Technological Processes
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2002
• 资助国家: 德国
• 起止时间: 2001-12-31 至 2006-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/5369349?language=en
• 关键词: Beach; profile; simulation; under; sediment

Protection of shorelines and islands is of great economic interest and still a major challenge in coastal engineering. Engineering decisions on maintenance and improvement of beach profiles strongly depend on the quality of models for understanding the processes and forecasting evolution over years. Models at hand are either parametric or deterministic, the latter solved by discrete numerical methods in one or two dimensions. Data-driven models based on neural networks and fuzzy methods are lacking in this field though quite succesfully being applied to forecast floods in rivers, hydrology and control. The project aims at expanding the data-driven approach to simulating beach profile evolution by long and cross-shore sediment transport at coastal profiles in the Baltic Sea. Data are available. Comparisons with deterministic one-dimensional numerical models (in long and cross-shore direction) will be made.

保护海岸线和岛屿具有巨大的经济利益，仍然是海岸工程的一个重大挑战。维护和改善海滩剖面的工程决策在很大程度上取决于了解过程和预测多年演变的模型的质量。现有的模型要么是参数型的，要么是确定型的，后者通过一维或二维的离散数值方法求解。基于神经网络和模糊方法的数据驱动模型虽然在河流洪水预报、水文预报和控制预报等方面得到了成功的应用，但在这一领域还比较缺乏。该项目旨在扩大数据驱动的方法，通过波罗的海沿海剖面的长距离和跨海岸沉积物迁移模拟海滩剖面演变。数据可用。将与确定性一维数值模型（在长和跨海岸方向）进行比较。