메뉴 건너뛰기




Volumn 36, Issue 1-2, 2011, Pages 26-39

Real time wave forecasting using wind time history and numerical model

Author keywords

Artificial neural networks; Genetic programming; Model trees; Numerical wave prediction; Wave prediction

Indexed keywords

ARTIFICIAL NEURAL NETWORK; COST EFFECTIVE; EAST COAST; HINDCASTING; LEAD TIME; MODEL TREES; NUMERICAL MODELS; NUMERICAL WAVE PREDICTION; OPERATIONAL ACTIVITY; REAL TIME; REAL-TIME PREDICTION; SITE-SPECIFIC INFORMATION; STRUCTURAL REPAIRS; TIME DURATION; TIME HISTORY; TIME SERIES MODELING; TIME SERIES MODELS; TIME STEP; WAVE DATA; WAVE FORECASTING; WAVE PREDICTION; WIND DIRECTIONS; WIND SPEED;

EID: 78649956822     PISSN: 14635003     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ocemod.2010.07.006     Document Type: Article
Times cited : (45)

References (41)
  • 1
    • 64249091422 scopus 로고    scopus 로고
    • Spectral characteristics of near shore waves off Paradip, India during monsoon and extreme events
    • Aboobacker V.M., Vethamony P., Sudheesh K., Rupali S.P. Spectral characteristics of near shore waves off Paradip, India during monsoon and extreme events. Natural Hazards 2009, 49:311-323.
    • (2009) Natural Hazards , vol.49 , pp. 311-323
    • Aboobacker, V.M.1    Vethamony, P.2    Sudheesh, K.3    Rupali, S.P.4
  • 2
    • 12144264770 scopus 로고    scopus 로고
    • Neural networks and M5 model trees in modeling water level-discharge relationship
    • Bhattacharya B., Solomatine D.P. Neural networks and M5 model trees in modeling water level-discharge relationship. Neurocomputing 2005, 381-396.
    • (2005) Neurocomputing , pp. 381-396
    • Bhattacharya, B.1    Solomatine, D.P.2
  • 3
    • 33744831397 scopus 로고    scopus 로고
    • A data mining approach to modeling sediment transport. In: Liong, Phoon, Babovic (Eds.), 6th International Conference on Hydroinformatics.
    • Bhattacharya, B., Price, R.K., Solomatine, D.P., 2004. A data mining approach to modeling sediment transport. In: Liong, Phoon, Babovic (Eds.), 6th International Conference on Hydroinformatics. pp. 1303-1310.
    • (2004) , pp. 1303-1310
    • Bhattacharya, B.1    Price, R.K.2    Solomatine, D.P.3
  • 4
    • 34247282207 scopus 로고    scopus 로고
    • Nearshore swell estimation from a global wind-wave model spectral process, linear and artificial neural network models
    • Browne M., Castelle B., Strauss D., Tomilnson R., Blumenstein M., Lane C. Nearshore swell estimation from a global wind-wave model spectral process, linear and artificial neural network models. Coastal Engineering 2007, 54:445-460.
    • (2007) Coastal Engineering , vol.54 , pp. 445-460
    • Browne, M.1    Castelle, B.2    Strauss, D.3    Tomilnson, R.4    Blumenstein, M.5    Lane, C.6
  • 5
    • 78649918928 scopus 로고    scopus 로고
    • Neural Network Toolbox User's guide. The Mathworks INC.
    • Demuth, H., Beai, E.M., Hagrn, M., 1998. Neural Network Toolbox User's guide. The Mathworks INC.
    • (1998)
    • Demuth, H.1    Beai, E.M.2    Hagrn, M.3
  • 6
    • 78649975377 scopus 로고    scopus 로고
    • Discipulus Owner's Manual, RML Technologies Inc.
    • Discipulus Owner's Manual, 1998. RML Technologies Inc.
    • (1998)
  • 7
    • 78649958026 scopus 로고    scopus 로고
    • Application of neural networks and genetic programming to rainfall runoff modeling. Danish Hydraulic Institute (Hydro-Informatics Technologies). HIT, 1999, June, D2K-0699-1.
    • Drecourt, J.P., 1999. Application of neural networks and genetic programming to rainfall runoff modeling. Danish Hydraulic Institute (Hydro-Informatics Technologies). HIT, 1999, June, D2K-0699-1.
    • (1999)
    • Drecourt, J.P.1
  • 8
    • 2442496535 scopus 로고    scopus 로고
    • Solving the ocean color problem using genetic programming
    • Fonlupt C. Solving the ocean color problem using genetic programming. Journal of Applied Soft Computing 2001, 1:63-72.
    • (2001) Journal of Applied Soft Computing , vol.1 , pp. 63-72
    • Fonlupt, C.1
  • 9
    • 46749107461 scopus 로고    scopus 로고
    • Real time wave forecasting using genetic programming
    • Elsevier
    • Gaur S., Deo M.C. Real time wave forecasting using genetic programming. Ocean Engineering 2008, 35:1166-1172. Elsevier.
    • (2008) Ocean Engineering , vol.35 , pp. 1166-1172
    • Gaur, S.1    Deo, M.C.2
  • 10
    • 51149105489 scopus 로고    scopus 로고
    • Gunaydin The estimation of monthly mean significant wave heights by using artificial neural network and regression methods
    • Gunaydin The estimation of monthly mean significant wave heights by using artificial neural network and regression methods. Ocean Engineering 2008, 35:1406-1415.
    • (2008) Ocean Engineering , vol.35 , pp. 1406-1415
  • 11
    • 0000504914 scopus 로고
    • Wave forecasting for moving and stationary targets
    • Balkema, Hamburg, O.C. Zienkiewicz, B.Y. Schrefler (Eds.)
    • Holthuijsen H.L., de Boer S. Wave forecasting for moving and stationary targets. Computer Modeling in Ocean Engineering 1988, 231-234. Balkema, Hamburg. O.C. Zienkiewicz, B.Y. Schrefler (Eds.).
    • (1988) Computer Modeling in Ocean Engineering , pp. 231-234
    • Holthuijsen, H.L.1    de Boer, S.2
  • 13
    • 34748925008 scopus 로고    scopus 로고
    • Real time wave forecasts off western Indian coast
    • Elsevier
    • Jain Pooja, Deo M.C. Real time wave forecasts off western Indian coast. Applied Ocean Research 2007, 29:72-79. Elsevier.
    • (2007) Applied Ocean Research , vol.29 , pp. 72-79
    • Jain, P.1    Deo, M.C.2
  • 14
    • 70349731388 scopus 로고    scopus 로고
    • Artificial intelligence tools to forecast ocean waves in real time
    • Bentham Science
    • Jain Pooja, Deo M.C. Artificial intelligence tools to forecast ocean waves in real time. The Open Ocean Engineering Journal 2008, 1:13-21. Bentham Science.
    • (2008) The Open Ocean Engineering Journal , vol.1 , pp. 13-21
    • Jain, P.1    Deo, M.C.2
  • 15
    • 78649967810 scopus 로고    scopus 로고
    • Real time wave and wind forecasting system for the Indian coastline. In: Fifth International Conference on Asian and Pacific Coasts, APAC 2009 October 13-16. Singapore, APAC011.
    • Jain Pooja, Deo, M.C., Latha, G., Rajendran, V., Charhate, S.B., Londhe, S.N., 2009. Real time wave and wind forecasting system for the Indian coastline. In: Fifth International Conference on Asian and Pacific Coasts, APAC 2009 October 13-16. Singapore, APAC011.
    • (2009)
    • Jain Pooja Deo, M.C.1    Latha, G.2    Rajendran, V.3    Charhate, S.B.4    Londhe, S.N.5
  • 16
    • 39549110229 scopus 로고    scopus 로고
    • Genetic programming for retrieving missing information in wave records along the west coast of India
    • Kalra Ruchi, Deo M.C. Genetic programming for retrieving missing information in wave records along the west coast of India. Applied Ocean Research 2007, 29:99-111.
    • (2007) Applied Ocean Research , vol.29 , pp. 99-111
    • Kalra, R.1    Deo, M.C.2
  • 17
    • 85144998533 scopus 로고    scopus 로고
    • Ocean wave forecasting in the gulf of Thailand during typhoon Linda 1997: WAM and neural network approaches
    • Kanbua W., Supharatid S., Tang I. Ocean wave forecasting in the gulf of Thailand during typhoon Linda 1997: WAM and neural network approaches. Science Asia Journal 2005, 31:243-250.
    • (2005) Science Asia Journal , vol.31 , pp. 243-250
    • Kanbua, W.1    Supharatid, S.2    Tang, I.3
  • 18
    • 22144443524 scopus 로고    scopus 로고
    • Application of fuzzy inference system in the prediction of wave parameters
    • 1709-1725
    • Kazeminezhad M.H., Etemad-Shahidi A., Mousavi S.J. Application of fuzzy inference system in the prediction of wave parameters. Ocean Engineering 2005, 32:14-15. 1709-1725.
    • (2005) Ocean Engineering , vol.32 , pp. 14-15
    • Kazeminezhad, M.H.1    Etemad-Shahidi, A.2    Mousavi, S.J.3
  • 21
    • 0036373412 scopus 로고    scopus 로고
    • A neural network technique to improve computational efficiency of numerical oceanic models. Ocean Modeling 4
    • Kransnopolsky, V.M., Chalikov, D.V., Tolman, H.L., 2002. A neural network technique to improve computational efficiency of numerical oceanic models. Ocean Modeling 4, 363-383.
    • (2002) , pp. 363-383
    • Kransnopolsky, V.M.1    Chalikov, D.V.2    Tolman, H.L.3
  • 23
    • 1842843640 scopus 로고    scopus 로고
    • Improving wave predictions with artificial neural networks
    • Makarynskyy O. Improving wave predictions with artificial neural networks. Ocean Engineering 2004, 31:709-724.
    • (2004) Ocean Engineering , vol.31 , pp. 709-724
    • Makarynskyy, O.1
  • 24
    • 34250759987 scopus 로고    scopus 로고
    • Wave prediction and data supplementation using artificial neural networks
    • Makarynskyy O., Makarynska D. Wave prediction and data supplementation using artificial neural networks. Journal of Coastal Research 2006, 22:146-155.
    • (2006) Journal of Coastal Research , vol.22 , pp. 146-155
    • Makarynskyy, O.1    Makarynska, D.2
  • 25
    • 38849097226 scopus 로고    scopus 로고
    • Wave hindcasting by coupling numerical model and artificial neural networks
    • Malekmohamadi I., Ghiassi R., Yazdanpanah M.J. Wave hindcasting by coupling numerical model and artificial neural networks. Ocean Engineering 2008, 35:417-425.
    • (2008) Ocean Engineering , vol.35 , pp. 417-425
    • Malekmohamadi, I.1    Ghiassi, R.2    Yazdanpanah, M.J.3
  • 26
    • 78649966356 scopus 로고    scopus 로고
    • Mike21 User's Manual, Danish Hydraulics Institute, Denmark.
    • Mike21 User's Manual, 2007. Danish Hydraulics Institute, Denmark.
    • (2007)
  • 27
    • 0001495905 scopus 로고
    • Learning with continuous classes. In: Proceedings od the Australian Joint Conference on AI. World Scientific, Singapore
    • Quinlan, J.R., 1992. Learning with continuous classes. In: Proceedings od the Australian Joint Conference on AI. World Scientific, Singapore, pp. 343-348.
    • (1992) , pp. 343-348
    • Quinlan, J.R.1
  • 28
    • 78649977321 scopus 로고    scopus 로고
    • Modeling wave characteristics in north Indian Ocean. International Conference in Ocean Engineering. IIT Madras, Chennai, India, February 1-5
    • Rajesh, P.R., Jossia, Joseph K., Roy Choudhury, R., 2009. Modeling wave characteristics in north Indian Ocean. International Conference in Ocean Engineering. IIT Madras, Chennai, India, February 1-5, pp. 346-355.
    • (2009) , pp. 346-355
    • Rajesh, P.R.1    Jossia Joseph, K.2    Roy Choudhury, R.3
  • 29
    • 39449115775 scopus 로고    scopus 로고
    • Siek, Flexible and optimal M5 model trees with applications to flow predictions. In: Liong, Phoon, Babovic (Eds.), 6th International Conference on Hydroinformatics.
    • Solomatine, D.P., Siek, 2004. Flexible and optimal M5 model trees with applications to flow predictions. In: Liong, Phoon, Babovic (Eds.), 6th International Conference on Hydroinformatics. pp. 1719-1726.
    • (2004) , pp. 1719-1726
    • Solomatine, D.P.1
  • 30
    • 0037565156 scopus 로고    scopus 로고
    • Model tree as an alternative to neural network in rainfall-runoff modeling
    • Solomatine D.P., Dulal K.N. Model tree as an alternative to neural network in rainfall-runoff modeling. Hydrological Sciences Journal 2003, 48(3):399-412.
    • (2003) Hydrological Sciences Journal , vol.48 , Issue.3 , pp. 399-412
    • Solomatine, D.P.1    Dulal, K.N.2
  • 31
    • 10244261532 scopus 로고    scopus 로고
    • M5 model trees compared to neural networks: application to flood forecasting in the upper reach of the Huai River in China
    • Solomatine D.P., Xue Y. M5 model trees compared to neural networks: application to flood forecasting in the upper reach of the Huai River in China. ASCE Journal of Hydrologic Engineering 2004, 9(4):491-501.
    • (2004) ASCE Journal of Hydrologic Engineering , vol.9 , Issue.4 , pp. 491-501
    • Solomatine, D.P.1    Xue, Y.2
  • 32
    • 78649946496 scopus 로고    scopus 로고
    • Application of the M5 machine learning method for the development of the low flow forecasting model. In: 7th International conference on Hydroinformatics, HIC, Nice, France
    • Stravs, L., Brilly, M., 2006. Application of the M5 machine learning method for the development of the low flow forecasting model. In: 7th International conference on Hydroinformatics, vol. 2. HIC, Nice, France, pp. 863-878.
    • (2006) , vol.2 , pp. 863-878
    • Stravs, L.1    Brilly, M.2
  • 33
    • 78649956932 scopus 로고    scopus 로고
    • Assessment of wave modeling results with buoy and altimeter deep water waves for a summer monsoon. In: Third Indian National Conference on Dock and Harbor Engineering. NIO Goa, December 7-9
    • Sudheesh, K., Vethamony, P., Babu, M.T., Jayakumar, S., 2004. Assessment of wave modeling results with buoy and altimeter deep water waves for a summer monsoon. In: Third Indian National Conference on Dock and Harbor Engineering. NIO Goa, December 7-9, pp. 184-192.
    • (2004) , pp. 184-192
    • Sudheesh, K.1    Vethamony, P.2    Babu, M.T.3    Jayakumar, S.4
  • 34
    • 42149162803 scopus 로고    scopus 로고
    • Filling up gaps in wave data with genetic programming
    • Elsevier
    • Ustoorikar K., Deo M.C. Filling up gaps in wave data with genetic programming. Marine Structures 2008, 21:177-195. Elsevier.
    • (2008) Marine Structures , vol.21 , pp. 177-195
    • Ustoorikar, K.1    Deo, M.C.2
  • 37
    • 0035105632 scopus 로고    scopus 로고
    • Modeling Rainfall-Runoff using genetic programming. Mathematical and Computer Modeling Canberra, Australia
    • Whigham, P.A., Crapper, P.F., 2001. Modeling Rainfall-Runoff using genetic programming. Mathematical and Computer Modeling Canberra, vol. 33. Australia, pp. 707-721.
    • (2001) , vol.33 , pp. 707-721
    • Whigham, P.A.1    Crapper, P.F.2
  • 41
    • 33745627084 scopus 로고    scopus 로고
    • An adjoint sensitivity technique for dynamic neural network modeling and design of high-speed interconnect. International Journal on RF and Microwave CAE
    • Zhang, Q.J., Cao, Y., Xu, J.J., V.K., Ding, R.T., 2006. An adjoint sensitivity technique for dynamic neural network modeling and design of high-speed interconnect. International Journal on RF and Microwave CAE, vol. 16, No. 4. pp. 385-399.
    • (2006) , vol.16 , Issue.4 , pp. 385-399
    • Zhang, Q.J.1    Cao, Y.2    Xu, J.J.V.K.3    Ding, R.T.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.