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

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Advances in Neural Networks – ISNN 2009 (ISNN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5551))

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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, O1and 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.

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Author information

Authors and Affiliations

  1. Laboratory of Environmental Protection in Water Transport Engineering, Tianjin Research Institute of Water Transport Engineering, Tianjin, 300456, China

    Mingchang Li, Guangyu Zhang & Bin Zhou

  2. State Key Laboratory of Coastal and Offshore Engineering, DUT, Dalian, 116024, China

    Shuxiu Liang & Zhaochen Sun

Authors
  1. Mingchang Li
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  2. Guangyu Zhang
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  3. Bin Zhou
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  4. Shuxiu Liang
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  5. Zhaochen Sun
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Editor information

Editors and Affiliations

  1. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

  2. Deptartment of Electrical and Computer Engineering, Stevens Institute of Technology, NJ 07030, Hoboken, USA

    Haibo He

  3. Dept. of Electrical and Computer Engineering, South Dakota School of Mines & Technology, 501 E. St. Joseph Street, Rapid City, SD 57701, USA

    Nian Zhang

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© 2009 Springer-Verlag Berlin Heidelberg

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Li, M., Zhang, G., Zhou, B., Liang, S., Sun, Z. (2009). Optimal Inversion of Open Boundary Conditions Using BPNN Data-Driven Model Combined with Tidal Model. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5551. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01507-6_1

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  • DOI: https://doi.org/10.1007/978-3-642-01507-6_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01506-9

  • Online ISBN: 978-3-642-01507-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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