Wave forecasts using wind information and genetic programming

Ocean Engineering

Volumn 54, Issue , 2012, Pages 61-69

  Nitsure, S P ^a   Londhe, S N ^a   Khare, K C ^b  

^a VISHWAKARMA INSTITUTE OF INFORMATION TECHNOLOGY   (India)

^b SINHGAD COLLEGE OF ENGINEERING   (India)

Author keywords

Artificial neural networks; Genetic programming; Kurtosis; Significant wave height; Wave forecasting

Indexed keywords

ENERGY BALANCE EQUATIONS; EXTREME EVENTS; FORECAST ACCURACY; KURTOSIS; LEAD TIME; MARITIME ACTIVITIES; MODELING PROCEDURE; NORTH AMERICAN; PEAK WAVE HEIGHT; PHYSICS-BASED MODELS; SIGNIFICANT WAVE HEIGHT; SOFTCOMPUTING TECHNIQUES; WAVE FORECAST; WAVE FORECASTING; WAVE HEIGHTS;

GENETIC PROGRAMMING; HIGHER ORDER STATISTICS; NEURAL NETWORKS; SOFT COMPUTING; WATER WAVES;

FORECASTING;

ARTIFICIAL NEURAL NETWORK; ENERGY BALANCE; FORECASTING METHOD; HURRICANE; OCEAN WAVE; SIGNIFICANT WAVE HEIGHT;

EID: 84865782500     PISSN: 00298018     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.oceaneng.2012.07.017     Document Type: Article

References (46)

1. J.D. Agrawal, and M.C. Deo Online wave prediction Mar. Struct. 15 2002 57 74
2. V. Babovic, and M. Keijzer Genetic programming as a model induction engine J. Hydroinformatics 2 1 2000 35 61
3. W. Banzhaf, P. Nordin, R.E. Keller, and F.D. Francone Genetic Programming-An Introduction on the Automatic Evolution of Computer Programs and its Applications 1997 Morgan Kaufmann Germany 978-1-55860-510-7
4. W. Banzhaf, P. Nordin, R.E. Keller, and F.D. Francone Genetic Programming 1998 Morgan Kauffman San Francisco, CA
5. Bhattacharya, B.; Deibel, I.K.; Karstens, S.A.M.; Solomatine, D.P.; 2003. Neural networks in sedimentation modeling for the approach channel of the port area of Rotterdam. Proceedings of the 7th International Conference on Near Shore and Estuarine Cohesive Sediment Transport Processes (INTERCOH). Virginia Institute of Marine Science, Virginia, USA.
6. N. Booij, R.C. Ris, and L.H. Holthuijsen A third-generation wave model for coastal regions, 1. Model Description and validation J. Geophys. Res. C104 1999 7649 7666
7. G.E.P. Box, and G.M. Jenkins Time Series Analysis: Forecasting and Control 1976 Holden- Day Inc. Oakland (Revised Edition)
8. Brameier, M.; 2004. On Linear Genetic Programming. Ph.D. Thesis. University of Dortmund.
9. S.B. Charhate, M.C. Deo, and V. Sanilkumar Soft and hard computing approaches for real time prediction of currents in a tide dominated area J. Eng. Marit. Environ.; Proc. Inst. Mech. Eng.; London Part M 221 2007 147 163
10. S.B. Charhate, M.C. Deo, and S.N. Londhe Inverse modeling to derive wind parameters from wave measurements Appl. Ocean Res. 30 2008 2008 120 129 (Elsevier)
11. Mansi Daga, and M.C. Deo Alternative data driven methods to estimate wind from waves by inverse modeling Nat. Hazards 49 2008 293 310 (Springer, Number 2/May 2009)
12. C.W. Dawson, and R.L. Wilby Hydrological modeling using artificial neural networks Prog. Phys. Geogr. 25 1 2001 80 108
13. M.C. Deo, and C.S. Naidu Real time wave forecasting using neural networks Ocean Eng. 26 1999 191 203
14. M.C. Deo, A. Jha, A.S. Chaphekar, and K. Ravikant Neural network for wave forecasting Ocean Eng. 28 2001 889 898
15. Francone, F.D.; Markus, C.; Banzhaf, W.; Nordin, P.; 1999. Homologous Crossover in Genetic Programming. Proceedings of Genetic and Evolutionary Computation Conference, 1999, vol. 2, pp. 1021-1026.
16. F.D. Francone Discipulus: Fast Genetic Programming Based on AIM Learning Technology - Owner's Manual 2004 Register Machine Learning Technologies, Inc. Littleton, Colorado
17. S. Gaur, and M.C. Deo Real-time wave forecasting using genetic programming Ocean Eng. 35 2008 1166 1172
18. M.A. Ghorbani, R. Khatibi, A. Aytek, O. Makarynskyy, and J. Shiri Sea water level forecasting using genetic programming and comparing the performance with artificial neural networks J. Comput. Geosci. 36 2010 620 627
19. O. Giustolisi, and D.A. Savic A symbolic data-driven technique based on evolutionary polynomial regression J. Hydroinformatics 8 3 2006 207 222
20. A. Guven Linear genetic programming for time-series modelling of daily flow rate J. Earth Syst. Sci. 118 2 2009 137 146
21. P. Jain, and M.C. Deo Neural networks in ocean engineering Int. J. Ships Offshore Struct. 1 2006 25 35
22. P. Jain, and M.C. Deo Real-time wave forecasts off the western Indian coast Appl. Ocean Res. 29 2007 72 79
23. P. Jain, and M.C. Deo Artificial intelligence tools to forecast ocean waves in real time Open Ocean Eng. J. 1 2008 13 21 (Bentham Science)
24. Ruchi Kalra, and M.C. Deo Genetic programming to retrieve missing information in wave records along the west coast of India Appl. Ocean Res. 29 3 2007 99 111 (Elsevier)
25. A.R. Kambekar, and M.C. Deo Wave simulation and forecasting using wind time history and data driven methods Int. J. Ships Offshore Struct. 5 3 2010 253 266 (Taylor and Francis)
26. A.R. Kambekar, and M.C. Deo Wave prediction using genetic programming and model trees J. Coastal Res. 2010 10.2112/JCOASTRES-D-1-10-00052.1 (Coastal Research and Education Foundation, USA)
27. B. Kamranzad, A. Etemad-Shahidi, and M.H. Kazeminezhad Wave height forecasting in Dayyer, the Persian Gulf Ocean Eng. 38 2011 2011 248 255
28. M. Keijzer, and V. Babovic Dimensionally aware genetic programming W. Banzhaf, Proceedings of GECCO 1999 Morgan Kaufmann 99
29. Keijzer, M.; Babovic, V.; 2000. Genetic Programming, Ensemble Methods and the Bias/Variance Tradeoff. In: Proceedings of EuroGP 2000, Springer.
30. Koza Genetic Programming - On the Programming of Computers by Means of Natural Selection 1992 MIT Press 0-262-11170-5 840 p
31. S.N. Londhe, and V. Panchang One-day wave forecasts based on artificial neural networks J. Atmos. Ocean Technol. 23 2006 1593 1603
32. S.N. Londhe Soft computing approach for real-time estimation of missing wave heights Ocean Eng. 35 2008 2008 1080 1089
33. J. Mahjoobi, A. Etemad-Shahidi, and M.H. Kazeminezhad Hindcasting of wave parameters using different soft computing methods Appl. Ocean Res. 30 2008 28 36
34. O. Makarynskyy Improving wave predictions with artificial neural networks Ocean Eng. 31 2004 709 724
35. S. Mandal, and N. Prabaharan Ocean wave forecasting using recurrent neural networks Ocean Eng. 33-10 2006 1401 1410
36. J.P. Nordin Evolutionary Program Induction of Binary Machine Code and its Application 1997 Krehl Verlag Muenster, Germany
37. M. Ozger, and Z. Sen Prediction of wave parameters by using fuzzy logic approach Ocean Eng. 34 3-4 2007 460 469
38. V.G. Panchang, and D. Li Large waves in the Gulf of Mexico caused by hurricane Ivan Bull. Am. Meteorological Soc. v87 4 2006 481 489
39. G. Reikard, P. Pinson, and J.R. Bidlot Forecasting ocean wave energy: the ECMWF wave model and time series methods Ocean Eng. 38 10 2011 1089 1099
40. Tolman, H.L.; 2002. User manual and system documentation of WAVEWATCH III version 2.22. Technical note 222, NOAA/NWS/NCEP/MMAB. 133 pp.
41. C.P. Tsai, C. Lin, and J.N. Shen Neural network for wave forecasting among multi-stations Ocean Eng. 29 2002 1683 1695
42. US Army Corps of Engineers Coastal Engineering Manual Part-II, Chapter II Meteorology and Wave Climate, Engineer Manual 1110-2-1100 2008 US Army Corps of Engineers Washington, DC
43. K. Ustoorikar, and M.C. Deo Filling up gaps in wave data with genetic programming Marine Struct. 21 2008 2008 177 195 (Elsevier)
44. WAMDI Group The WAM model - a third generation wave prediction model J. Phys. Oceanogr. 18 1988 1775 1810
45. J. Wu Wind stress coefficients over sea surface from breeze to hurricane J. Geophys. Res. 87 C12 1982 9704 9706
46. A. Zamani, D. Solomatine, A. Azimian, and A. Heemink Learning from data for wind-wave forecasting Ocean Eng. 35 2008 953 962