Optimal Inversion of Open Boundary Conditions Using BPNN Data-Driven Model Combined with Tidal Model

  • Authors:

  • Mingchang Li;Guangyu Zhang;Bin Zhou;Shuxiu Liang;Zhaochen Sun

  • Affiliations:

  • Laboratory of Environmental Protection in Water Transport Engineering, Tianjin Research Institute of Water Transport Engineering, Tianjin, China 300456;Laboratory of Environmental Protection in Water Transport Engineering, Tianjin Research Institute of Water Transport Engineering, Tianjin, China 300456;Laboratory of Environmental Protection in Water Transport Engineering, Tianjin Research Institute of Water Transport Engineering, Tianjin, China 300456;State Key Laboratory of Coastal and Offshore Engineering, DUT, Dalian, China 116024;State Key Laboratory of Coastal and Offshore Engineering, DUT, Dalian, China 116024

  • Venue:
  • ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
  • Year:
  • 2009

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Abstract

One of major difficulties with numerical tidal models is accurate inversion of open boundary conditions. A data-driven model based on artificial neural network is developed to retrieve open boundary values. All training data are calculated by numerical tidal model, so the tidal physics are not disturbed. The basic idea is to find out the relationship between open boundary values and the values of interior tidal stations. Case testes are carried out with a real ocean bay named Liaodong Bay, part of the Bohai Sea, China. Four major tidal constituents, M2 , S2 , O1 and K1 , are considered in coupled inversion method. Case studies show that the coupled inversion for open boundary conditions can make a more satisfactory inversion for a practical problem.