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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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References

  1. Abbott, M.B.: Range of Tidal Flow Modeling. Journal of Hydraulic Engineering 123, 255–277 (1997)

    Article  Google Scholar 

  2. Davies, A.M., Jones, J.E., Xing, J.: Review of Recent Developments in Tidal Hydrodynamic Modeling. Journal of Hydraulic Engineering 4, 278–292 (1997)

    Article  Google Scholar 

  3. Egbert, G.D., Bennett, A.F., Foreman, M.G.G.: TOPEX/POSEIDON Tides Estimated Using a Global Inverse Model. Journal of Geophysical Research 99, 24821–24852 (1994)

    Article  Google Scholar 

  4. Gerritsen, H., Vries, H., Philippart, M.: The Dutch Continental Shelf Model. Quantitative Skill Assessment for Coastal Ocean Models. Coastal Estuarine Studies 47, 425–468 (1995)

    Article  Google Scholar 

  5. Bennett, A.F., Mcintosh, P.C.: Open Ocean Modeling as an Inverse Problem: Tidal Theory. Journal of Physical Oceanography 12, 1004–1018 (1982)

    Article  Google Scholar 

  6. Hall, M.C.G., Cacuci, D.G., Schlesinger, M.E.: Sensitivity Analysis of a Radiative-Convective Model by Adjoint Method. Journal of Atmospheric Science 39, 2038–2050 (1982)

    Article  MathSciNet  Google Scholar 

  7. Cacuci, D.G.: The Forward and Adjoint Methods of Sensitivity Analysis. Uncertainty Analysis 282 (1988)

    Google Scholar 

  8. Panchang, V.G., O’Brien, J.J.: On the Determination of Hydraulic Model Parameter Using tThe Adjoint Stste Formulation. Modeling Marine System 1, 5–18 (1989)

    Google Scholar 

  9. Larder: Optimal Control of Open Boundary Conditions for a Numerical Tidal Model. Computer Methods in Applied Mechanics and Engineering 102, 367–387 (1993)

    Article  Google Scholar 

  10. Seiler: Estimation of Open Boundary Conditions with the Adjoint Method. Journal of Geophysical Research 98, 22855–22870 (1993)

    Article  Google Scholar 

  11. Zhu, J., Zeng, Q., et al.: Estimation of Coastal Ocean Model Open Boundary Conditions from Nearshore Tide Gauge Station Using Adjoint Method. Science In China (Series D) 27(5), 462–468 (1997)

    Google Scholar 

  12. Vogeler, A., Schroeter, J.: Fitting a Regional Ocean Model with Adjustable Open Boundaries to TOPEX/POSEIDON data. Journal of Geophysical Research 104, 20789–20799 (1999)

    Article  Google Scholar 

  13. Zhang, K.Q., Marotzke, J.: The Importance of Open-Boundary Estimation for an Indian Ocean GCM-data Synthesis. Journal of Marine Research 57, 305–334 (1999)

    Article  Google Scholar 

  14. Han, G., He, B., Ma, J., et al.: Optimizing Open Boundary Conditions of Nonlinear Tidal Model Using Adjoint Method: The Establishment of Adjoint Model and Twin-Experiment. ACTA Oceanologica SINICA 22(6), 27–33 (2000)

    Google Scholar 

  15. Han, G., Fang, G., Ma, J., et al.: Optimizing Open Boundary Conditions of Nonlinear Tidal Model Using Adjoint Method. Assimilation Experiment for Tide in the Huanghai Sea and the East China Sea. ACTA Oceanologica SINICA 23(2), 25–31 (2001)

    Google Scholar 

  16. Lv, X., Fang, G.: Inversion of the Tides on the Open Boundary of the BOHAI SEA by Adjoint Method. Oceanologia ET Limnologia Sinica 33, 113–120 (2002)

    Google Scholar 

  17. Heemink, A.W., Mouthaan, E.E.A., Roest, M.R.T., Vollebregt, E.A.H., Robaczewska, K.B., Verlaam, M.: Inverse 3D Shallow Water Flow Modeling of the Continental Shelf. Continental Shelf Research 22, 465–484 (2002)

    Article  Google Scholar 

  18. Zhang, A.I., Wei, E., Parker, B.: Optimal Estimation of Tidal Open Boundary Conditions Using Predicted Tides and Adjoint Data Assimilation Technique. Continental Shelf Research 23, 1055–1070 (2003)

    Article  Google Scholar 

  19. Ayoub, N.: Estimation of Boundary Values in a North Atlantic Circulation Model Using an Adjoint Method. Ocean Modelling 12, 319–347 (2006)

    Article  Google Scholar 

  20. Ayoub, N., Stammer, D., Wunsch, C.: Estimating the North Atlantic Circulation with Nesting and Open-boundary Conditions Using an Adjoint Model. ECCO Report, No.10, Scripps Institution of Oceanography (2001), www.ecco-group.org

  21. Foreman, M.G.G., Sutherland, G., Cummins, P.F.: M 2 Tidal Dissipation Around Vancouver Island: an Inverse Approach. Continental Shelf Research 24, 2167–2185 (2004)

    Article  Google Scholar 

  22. Gebbie, G.A.: Subduction in an Eddy-resolving State Estimate of the Northeast Atlantic Ocean. MIT/WHOI PhD Thesis 198 (2004)

    Google Scholar 

  23. Ma, Z., Jing, A.: Data Assimilation Method Applied in Marine Science–Its Significance, System Configuration and Development Situation. Coastal Engineering 24, 83–99 (2005)

    Google Scholar 

  24. Blumberg, A.F., Mellor, G.L.: A Description of a Three-dimensional Coastal Ocean Circulation Model. In: Heaps, N.S. (ed.) Coastal and Estuarine Sciences 4: Three-Dimensional Coastal Ocean Models, Amer. Geophys. Union, pp. 1–16 (1987)

    Google Scholar 

  25. Solomatine, D.P.: Data-Driven Modelling: Paradigm, Methods, Experiences. In: Proc. 5th Int. Conference on Hydroinformatics, Cardiff, UK, pp. 757–763 (2002)

    Google Scholar 

  26. Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning Representations by Back Propagating Errors. Nature 323, 533–536 (1986)

    Article  MATH  Google Scholar 

  27. Hornik, K.: Approximation Capabilities of Multilayer Feedforward Networks. Neural Networks 2, 359–366 (1991)

    Article  Google Scholar 

  28. Li, M.C., Liang, S.: Application of Artificial Neural Networks to Tide Forecasting. Journal of Dalian University of Technology 47, 101–105 (2007)

    Google Scholar 

  29. Friedrichs, M.A.M.: A Data Assimilative Marine Ecosystem Model of the Central Equatorial Pacific: Numerical Twin Experiments. Journal of Marine Research 59, 859–894 (2001)

    Article  Google Scholar 

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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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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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