Soft and hard computing approaches for real-time prediction of currents in a tide-dominated coastal area

Proceedings of the Institution of Mechanical Engineers Part M: Journal of Engineering for the Maritime Environment

Volumn 221, Issue 4, 2007, Pages 147-165

  Charhate, S B ^a   Deo, M C ^a   Sanil Kumar, V ^b  

^a INDIAN INSTITUTE OF TECHNOLOGY BOMBAY   (India)

^b NATIONAL INSTITUTE OF OCEANOGRAPHY   (India)

Author keywords

Current measurements; Genetic programming; Harmonic analysis; Neural networks; Tidal currents

Indexed keywords

COASTAL ENGINEERING; GENETIC PROGRAMMING; HARMONIC ANALYSIS; HYDRODYNAMICS; NEURAL NETWORKS; TIDES; COASTAL ZONES; COMPLEX NETWORKS; ELECTRIC CURRENT MEASUREMENT; FORECASTING; GENETIC ALGORITHMS; HARMONIC FUNCTIONS; OCEAN CURRENTS; SOFT COMPUTING; STATISTICAL METHODS; STOCHASTIC SYSTEMS; TIME SERIES;

CURRENT MEASUREMENTS; TIDAL CURRENTS;

REAL TIME CONTROL; TIME SERIES ANALYSIS;

HYDRODYNAMIC MODEL; MATHEMATICAL APPROACH; NUMERICAL SOLUTION; REAL-TIME PREDICTION; SOFT COMPUTING TOOLS; TEMPORAL INFORMATION; TIDAL CURRENTS; UNIVARIATE TIME SERIES;

EID: 37649004389     PISSN: 14750902     EISSN: None     Source Type: Journal    
DOI: 10.1243/14750902JEME77     Document Type: Article

References (44)

1. Owen, A. A three-dimensional model of the Bristol Channel. J. Phys. Oceanogr., 1980, 10, 1290-1302.
2. Zigic, S., Zapata, M., Isaji, T., King, B., and Lemchert, C. Modelling of Moreton Bay using an ocean/coastal circulation model. In Proceedings of the Coasts and Ports Australasian Conference, Auckland, New Zealand, 9-12 September 2003, paper 170.
3. Gaythwaite, J. The marine environment and structural design, 1981. (Van Nost - and Rheinhold, New York).
4. Gerwick, B. C. Construction of offshore structures, 1996 (John Wiley, New York).
5. Church, J. A., John, C. A., and Boland, F. M. Tidal currents in the central Great Barrier Reef. Continental Shelf Res., 1998, 4(5), 515-531.
6. John, V. Harmonic tidal current constituents of the Western Arabian Gulf from moored current measurements. Coastal Engng, 1992, 17, 145-151.
7. Burrage, D. M., Black, I. P., and Ness, K. F. Long-term current prediction in the central Great Barrier Reef. Continental Shelf Res., 1994, 14(7-8), 803-809.
8. Nayak, R. K. and Shetye, S. R. Tides in the Gulf of Khambhat, west coast of India, estuarine. Coastal and Shelf Sci., 2003, 57, 249-254.
9. Sanil Kumar, V. and Ashok Kumar, K. Waves and currents in a tide dominated location off Dahej, Gulf of Khambhat, west coast of India. J. Coastal Res., 2007 (submitted for publication).
10. Deo, M. C. and Naidu, C. S. Real time wave forecasting using neural networks. Ocean Engng, 1999, 26(3), 191-203.
11. Tsai, C., Lin, C., and Shert, J. Neural network for wave forecasting among multi-stations. Ocean Engng, 2002, 29(13), 1683-1695.
12. Makarynskyy, O. Improving wave predictions with artificial neural networks. Ocean Engng, 2004, 31, 709-724.
13. Altunkaynak, A. and Ozger, M. Temporal significant wave height estimation from wind speed by perceptron Kalman filtering. Ocean Engng, 2004, 31(10), 1245-1255.
14. Tolman, H. L., Krasnopolsky, V. M., and Chalikov, D. V. Neural network approximations for nonlinear interactions in wind wave spectra: direct mapping for wind seas in deep water. Ocean Modeling, 2005, 8, 253-278.
15. Deo, M. C., Gondane, D. S., and Sanil Kumar, V. Analysis of wave directional spreading using neural networks. J. Waterway, Port, Coastal, Ocean Engng, 2002, 128(1), 30-37.
16. Deo, M. C. and Ghaudhari, G. Tide prediction using neural networks. J. Computer-Aided Civil Infrastruct. Engng, 1998, 13, 113-120.
17. Lee, T. L. Back-propagation neural network for long-term tidal predictions. Ocean Engng, 2004, 31(2), 225-238.
18. Vaziri, M. Predicting Caspian Sea surface water levels by ANN and ARIMA models. J. Waterway, Port, Coastal, Ocean Engng, 1997, 123(4), 158-162.
19. Cox, D. T., Tissot, P., and Michaud, P. Water level observations and short-term predictions including meteorological events for entrance of Galveston Bay, Texas. J. Waterway, Port, Coastal, Ocean Engng, 2002, 128(1), 21-29.
20. More, A. and Deo, M. C. Forecasting wind with neural networks. Mar. Structs, 2003, 16(1), 35-49.
21. Lee, T. L. and Jeng, D. S. Application of artificial neural networks in tide forecasting. Ocean Engng, 2002, 29(1), 1003-1022.
22. Grubert, J. P. Prediction of estuarine instabilities with artificial neural networks. J. Computing Civil Engng, 1995, 9(4), 226-274.
23. Babovic, V., Kanizares, R., Jenson, H. R., and Klinting, A. Neural networks as routine for error updating of numerical models. J. Hydraul. Engng, 2001, 127(3), 181-193.
24. All, M. M., Swain, D., and Weiler, R. A. Estimation of ocean, subsurface thermal structure from surface parmeters: a neural network approach. Geophys. Res. Lett., 31, 2004, L20308.
25. Refaat, H. A. Utilizing artificial neural networks for predicting shoreline changes behind offshore break-waters. J. Engng Appl. Sci., 2001, 48(2), 263-279.
26. Jain, P. and Deo, M. C. Neural networks in ocean engineering. Int. J. Ships Offshore Structs, 2006, 1(1), 25-35.
27. The ASCE Task Committee on Application of Artificial Neural Networks in Hydrology. Artificial neural networks in hydrology. I: preliminary concepts. J. Hydrologic Engng, 2000, 5(2), 115-123.
28. The ASCE Task Committee on Application Neural Networks in Hydrology, Artificial neural networks in hydrology. II. Hydrologic applications. J. Hydrologic Engng, 2000, 5(2), 124-137.
29. Govindaraju, R. S. and Rao, A. R. Artificial neural networks in hydrology, 2002 (Kluwer, Dordrecht).
30. Koza, J. R. Genetic programming: on the programming of computers by means of natural selection, 1992 (MIT Press, Boston, Massachusetts).
31. Soh, C. K. and Yang, Y. Genetic programming based approach for structural optimization. J. Computing in Civil Engng, 2000, 14(1), 31-37.
32. Whigham, P. A. and Crapper, P. F. Modeling rainfall-runoff using genetic programming. Math. Computer Modeling, 2001, 33, 707-721.
33. Babovic, V., Jean-Philippe Drecourt, J.-P., Keijzer, M., and Hansen, P. F. A data mining approach to modeling of water supply assets. Urban Water, 2002, 4, 401-414.
34. Hong, Y. S. and Rao, B. Evolutionary self-organizing modeling of a municipal wastewater treatment plant. Water Res., 2003, 37, 1199-1212.
35. Ashour, A. F., Alvarez, L. F., and Toropov, V. V. Empirical modeling of shear strength of RC deep beams by genetic programming. Computers Structs Sci. Direct, 2003, 81, 331-338.
36. Li, C. Study of applying macro evolutionary genetic programming to concrete strength estimation. J. Computing Civil Engng, 2003, 17(4), 290-294.
37. Yang, C. X., Tham, L. G., Feng, X. T., Wang, Y. J., and Lee, P. K. K. Two-stepped evolutionary algorithm and its application to stability analysis of slopes. J. Computing Civil Engng, 2004, 18(2), 145-153.
38. Bell, C., Vassie, J. M., and Woodworth, P. L. POL/PSMSL tidal analysis software kit 2000 (TASK-2000), permanent service for mean sea level, CCMS, Proudman Oceanographic Laboratory, Bidston Observatory, Birkenhead, Merseyside, 2000.
39. Kalra, R., Deo, M. C., Kumar, R., and Agarwal, V. K. RBF neural network for spatial mapping of wave heights. Marine Structs, 2005, 18, 289-300.
40. Kosko, B. Neural networks and fuzzy systems, 1992 (Prentice-Hall, Englewood Cliffs, New Jersey).
41. Wu, J. K. Neural networks and simulation methods, 1994 (Marcel Dekker, New York).
42. Bose, N. K. and Liang, P. Neural network fundamentals with graphs, algorithms and applications, 1998 (Tata McGraw-Hill, Delhi).
43. Londhe, S. and Panchang, V. One-day wave forecast based on artificial neural network. J. Atmospheric Oceanic Technol., 2006, 23(11), 593-1603.
44. Agrawal, J. D. and Deo, M. C. Online wave prediction. Marine Structs, 2002, 15(1), 57-74.