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Volumn 43, Issue , 2015, Pages 44-53

Significant wave height and energy flux range forecast with machine learning classifiers

Author keywords

Flux of energy; Multi class classification; Ordinal classification; Significant wave height; Wave energy converters; Wave energy prediction

Indexed keywords

BUOYS; CLASSIFICATION (OF INFORMATION); CLASSIFIERS; FORECASTING; MACHINE LEARNING; METEOROLOGY; NUMERICAL MODELS; WATER WAVES;

EID: 84929861047     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2015.03.012     Document Type: Article
Times cited : (60)

References (55)
  • 1
    • 18144429815 scopus 로고    scopus 로고
    • Wave parameter estimation using neural networks
    • J.D. Agrawal, and M.C. Deo Wave parameter estimation using neural networks Mar. Struct. 17 2004 536 550
    • (2004) Mar. Struct. , vol.17 , pp. 536-550
    • Agrawal, J.D.1    Deo, M.C.2
  • 2
    • 84869865815 scopus 로고    scopus 로고
    • Assessment of wave energy resource of the Black Sea based on 15-year numerical hindcast data
    • A. Akpinar, and M.I. Kömürcü Assessment of wave energy resource of the Black Sea based on 15-year numerical hindcast data Appl. Energy 101 2013 502 512
    • (2013) Appl. Energy , vol.101 , pp. 502-512
    • Akpinar, A.1    Kömürcü, M.I.2
  • 4
    • 80053249249 scopus 로고    scopus 로고
    • Atlas of global wave energy from 10 years of reanalysis and hindcast data
    • R.A. Arinaga, and K.F. Cheung Atlas of global wave energy from 10 years of reanalysis and hindcast data Renew. Energy 39 2012 49 64
    • (2012) Renew. Energy , vol.39 , pp. 49-64
    • Arinaga, R.A.1    Cheung, K.F.2
  • 6
    • 79958107479 scopus 로고    scopus 로고
    • Generating electricity from the oceans
    • A.S. Bahaj Generating electricity from the oceans Renew. Sustain. Energy Rev. 15 2011 3399 3416
    • (2011) Renew. Sustain. Energy Rev. , vol.15 , pp. 3399-3416
    • Bahaj, A.S.1
  • 7
    • 0031217273 scopus 로고    scopus 로고
    • Ordinal logistic regression in medical research
    • R. Bender, and U. Grouven Ordinal logistic regression in medical research J. R. Coll. Physicians Lond. 31 5 2006 546 551
    • (2006) J. R. Coll. Physicians Lond. , vol.31 , Issue.5 , pp. 546-551
    • Bender, R.1    Grouven, U.2
  • 9
    • 34547698831 scopus 로고    scopus 로고
    • Learning to classify ordinal data the data replication method
    • J.S. Cardoso, and J.F.P. da Costa Learning to classify ordinal data the data replication method J. Mach. Learn. Res. 8 2007 1393 1429
    • (2007) J. Mach. Learn. Res. , vol.8 , pp. 1393-1429
    • Cardoso, J.S.1    Da Costa, J.F.P.2
  • 10
    • 84904214689 scopus 로고    scopus 로고
    • Performance of artificial neural networks in nearshore wave power prediction
    • A. Castro, R. Carballo, G. Iglesias, and J.R. Rabuñal Performance of artificial neural networks in nearshore wave power prediction Applied Soft Computing 23 2014 194 201 10.1016/j.asoc.2014.06.031
    • (2014) Applied Soft Computing , vol.23 , pp. 194-201
    • Castro, A.1    Carballo, R.2    Iglesias, G.3    Rabuñal, J.R.4
  • 11
    • 33847626350 scopus 로고    scopus 로고
    • Support vector ordinal regression
    • W. Chu, and S.S. Keerthi Support vector ordinal regression Neural Comput. 19 3 2007 792 815
    • (2007) Neural Comput. , vol.19 , Issue.3 , pp. 792-815
    • Chu, W.1    Keerthi, S.S.2
  • 12
    • 34249753618 scopus 로고
    • Support-vector networks
    • C. Cortes, and V. Vapnik Support-vector networks Mach. Learn. 20 3 1995 273 297
    • (1995) Mach. Learn. , vol.20 , Issue.3 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 14
    • 29644438050 scopus 로고    scopus 로고
    • Statistical comparisons of classifiers over multiple data sets
    • J. Demsar Statistical comparisons of classifiers over multiple data sets J. Mach. Learn. Res. 7 2006 1 30
    • (2006) J. Mach. Learn. Res. , vol.7 , pp. 1-30
    • Demsar, J.1
  • 16
    • 0344286516 scopus 로고    scopus 로고
    • Real time wave prediction using neural networks
    • M.C. Deo, and C.S. Naidu Real time wave prediction using neural networks Ocean Eng. 26 3 1998 191 203
    • (1998) Ocean Eng. , vol.26 , Issue.3 , pp. 191-203
    • Deo, M.C.1    Naidu, C.S.2
  • 17
    • 80055049085 scopus 로고    scopus 로고
    • Current developments and future prospects of offshore wind and ocean energy
    • M. Esteban, and D. Leary Current developments and future prospects of offshore wind and ocean energy Appl. Energy 90 2012 128 136
    • (2012) Appl. Energy , vol.90 , pp. 128-136
    • Esteban, M.1    Leary, D.2
  • 18
    • 74449090123 scopus 로고    scopus 로고
    • Wave energy utilization a review of the technologies
    • A.F.de O. Falcão Wave energy utilization a review of the technologies Renew. Sustain. Energy Rev. 14 2010 899 918
    • (2010) Renew. Sustain. Energy Rev. , vol.14 , pp. 899-918
    • Falcão, A.F.D.O.1
  • 21
    • 77955676119 scopus 로고    scopus 로고
    • Short-term wave prediction for real-time control of wave energy converters
    • F. Fusco, and J.V. Ringwood Short-term wave prediction for real-time control of wave energy converters IEEE Trans. Sustain. Energy 1 2 2010 99 106
    • (2010) IEEE Trans. Sustain. Energy , vol.1 , Issue.2 , pp. 99-106
    • Fusco, F.1    Ringwood, J.V.2
  • 25
    • 0036505670 scopus 로고    scopus 로고
    • A comparison of methods for multi-class support vector machines
    • C.W. Hsu, and C.J. Lin A comparison of methods for multi-class support vector machines IEEE Trans. Neural Netw. 13 2 2002 415 425
    • (2002) IEEE Trans. Neural Netw. , vol.13 , Issue.2 , pp. 415-425
    • Hsu, C.W.1    Lin, C.J.2
  • 26
    • 84859007933 scopus 로고    scopus 로고
    • Extreme learning machine for regression and multiclass classification
    • G.-B. Huang, H. Zhou, X. Ding, and R. Zhang Extreme learning machine for regression and multiclass classification IEEE Trans. Syst. Man Cybern. B 42 2 2012 513 529
    • (2012) IEEE Trans. Syst. Man Cybern. B , vol.42 , Issue.2 , pp. 513-529
    • Huang, G.-B.1    Zhou, H.2    Ding, X.3    Zhang, R.4
  • 28
    • 22144443524 scopus 로고    scopus 로고
    • Application of fuzzy inference system in the prediction of wave parameters
    • M.H. Kazeminezhad, A. Etemad-Shahidi, and S.J. Mousavi Application of fuzzy inference system in the prediction of wave parameters Ocean Eng. 32 14-15 2005 1709 1725
    • (2005) Ocean Eng. , vol.32 , Issue.14-15 , pp. 1709-1725
    • Kazeminezhad, M.H.1    Etemad-Shahidi, A.2    Mousavi, S.J.3
  • 30
    • 84875231713 scopus 로고    scopus 로고
    • An overview of the U.K. Marine energy sector
    • Lawrence, J., Sedgwick, J., Jeffrey, H., Bryden, I., 2013. An overview of the U.K. marine energy sector. Proc. IEEE 101(4), 876-890.
    • (2013) Proc. IEEE , vol.101 , Issue.4 , pp. 876-890
    • Lawrence, J.1    Sedgwick, J.2    Jeffrey, H.3    Bryden, I.4
  • 31
    • 84861176005 scopus 로고    scopus 로고
    • Reduction from cost-sensitive ordinal ranking to weighted binary classification
    • H.-T. Lin, and L. Li Reduction from cost-sensitive ordinal ranking to weighted binary classification Neural Comput. 24 5 2012 1329 1367
    • (2012) Neural Comput. , vol.24 , Issue.5 , pp. 1329-1367
    • Lin, H.-T.1    Li, L.2
  • 32
    • 81855173670 scopus 로고    scopus 로고
    • Offshore wave power measurements: A review
    • S. Lindroth, and M. Leijon Offshore wave power measurements: a review Renew. Sustain. Energy Rev. 15 2011 4274 4285
    • (2011) Renew. Sustain. Energy Rev. , vol.15 , pp. 4274-4285
    • Lindroth, S.1    Leijon, M.2
  • 33
    • 0024771475 scopus 로고
    • Pattern classification using neural networks
    • R.P. Lippmann Pattern classification using neural networks IEEE Trans. Neural Netw. 27 1989 47 64
    • (1989) IEEE Trans. Neural Netw. , vol.27 , pp. 47-64
    • Lippmann, R.P.1
  • 35
    • 63649164524 scopus 로고    scopus 로고
    • Prediction of significant wave height using regressive support vector machines
    • J. Mahjoobi, and E.A. Mosabbeb Prediction of significant wave height using regressive support vector machines Ocean Eng. 36 2009 339 347
    • (2009) Ocean Eng. , vol.36 , pp. 339-347
    • Mahjoobi, J.1    Mosabbeb, E.A.2
  • 36
    • 50649091344 scopus 로고    scopus 로고
    • Hindcasting of wave parameters using different soft computing methods
    • J. Mahjoobi, A. Etemad-Shahidi, and M.H. Kazeminezhad Hindcasting of wave parameters using different soft computing methods Appl. Ocean Res. 30 1 2008 28 36
    • (2008) Appl. Ocean Res. , vol.30 , Issue.1 , pp. 28-36
    • Mahjoobi, J.1    Etemad-Shahidi, A.2    Kazeminezhad, M.H.3
  • 39
    • 84929883327 scopus 로고    scopus 로고
    • National Data Buoy Center (NDBC) [Online]. Available at.
    • National Data Buoy Center (NDBC). Station 41013 (LLNR 815) - Frying Pan Shoals, NC Buoy. [Online]. Available at: (http://www.ndbc.noaa.gov/station-history.php?station=41013).
    • Station 41013 (LLNR 815) - Frying Pan Shoals, NC Buoy
  • 40
    • 84929933759 scopus 로고    scopus 로고
    • National Oceanic and Atmospheric Administration (NOAA), National Data Buoy Center (NDBC). [Online]. Available at.
    • National Oceanic and Atmospheric Administration (NOAA), National Data Buoy Center (NDBC). [Online]. Available at: (http://www.ndbc.noaa.gov).
  • 41
    • 84865782500 scopus 로고    scopus 로고
    • Wave forecasts using wind information and genetic programming
    • S.P. Nitsure, S.N. Londhe, and K.C. Khare Wave forecasts using wind information and genetic programming Ocean Eng. 54 2012 61 69
    • (2012) Ocean Eng. , vol.54 , pp. 61-69
    • Nitsure, S.P.1    Londhe, S.N.2    Khare, K.C.3
  • 42
    • 79151480963 scopus 로고    scopus 로고
    • Prediction of ocean wave energy from meteorological variables by fuzzy logic modeling
    • M. Özger Prediction of ocean wave energy from meteorological variables by fuzzy logic modeling Exp. Syst. Appl. 38 5 2011 6269 6274
    • (2011) Exp. Syst. Appl. , vol.38 , Issue.5 , pp. 6269-6274
    • Özger, M.1
  • 43
    • 84886600375 scopus 로고    scopus 로고
    • Integrating wave energy into the power grid simulation and prediction
    • G. Reikard Integrating wave energy into the power grid simulation and prediction Ocean Eng. 73 2013 168 178
    • (2013) Ocean Eng. , vol.73 , pp. 168-178
    • Reikard, G.1
  • 44
    • 79959999421 scopus 로고    scopus 로고
    • Forecasting ocean wave energy the ECMWF wave model and time series methods
    • G. Reikard, P. Pinson, and J.R. Bidlot Forecasting ocean wave energy the ECMWF wave model and time series methods Ocean Eng. 38 2011 1089 1099
    • (2011) Ocean Eng. , vol.38 , pp. 1089-1099
    • Reikard, G.1    Pinson, P.2    Bidlot, J.R.3
  • 45
    • 84871851345 scopus 로고    scopus 로고
    • Nonlinear model predictive control of a point absorber wave energy converter
    • M. Richter, M.E. Magaña, O. Sawodny, and T.K. Brekken Nonlinear model predictive control of a point absorber wave energy converter IEEE Trans. Sustain. Energy 4 1 2013 118 126
    • (2013) IEEE Trans. Sustain. Energy , vol.4 , Issue.1 , pp. 118-126
    • Richter, M.1    Magaña, M.E.2    Sawodny, O.3    Brekken, T.K.4
  • 47
    • 4043137356 scopus 로고    scopus 로고
    • A tutorial on support vector regression
    • A. Smola, and B. Schlkopf A tutorial on support vector regression Stat. Comput. 14 3 2004 199 222
    • (2004) Stat. Comput. , vol.14 , Issue.3 , pp. 199-222
    • Smola, A.1    Schlkopf, B.2
  • 49
    • 84876530927 scopus 로고    scopus 로고
    • NOAA/ESRL Physical Sciences Division. [Online]. Available at
    • The NCEP/NCAR Reanalysis Project. NOAA/ESRL Physical Sciences Division. [Online]. Available at: (http://www.esrl.noaa.gov/psd/data/reanalysis/reanalysis.shtml).
    • The NCEP/NCAR Reanalysis Project
  • 51
    • 84870840731 scopus 로고    scopus 로고
    • [Online]. Available at.
    • The Pelamis Wave Power Website. [Online]. Available at: (http://www.pelamiswave.com/).
    • The Pelamis Wave Power Website
  • 52
    • 0037036332 scopus 로고    scopus 로고
    • Neural network for wave forecasting among multi-stations
    • C-P. Tsai, C. Lin, and J-N. Shen Neural network for wave forecasting among multi-stations Ocean Eng. 29 13 2002 1683 1695
    • (2002) Ocean Eng. , vol.29 , Issue.13 , pp. 1683-1695
    • Tsai, C.-P.1    Lin, C.2    Shen, J.-N.3
  • 53
    • 84889930291 scopus 로고    scopus 로고
    • Unidata [Online]. Available at.
    • Unidata. Network Common Data Form (NetCDF). [Online]. Available at: (http://www.unidata.ucar.edu/software/netcdf/).
    • Network Common Data Form (NetCDF)
  • 54
    • 84856733680 scopus 로고    scopus 로고
    • Learning partial ordinal class memberships with kernel-based proportional odds models
    • J. Verwaeren, W. Waegeman, and B. De Baets Learning partial ordinal class memberships with kernel-based proportional odds models Comput. Stat. Data Anal. 56 4 2012 928 942
    • (2012) Comput. Stat. Data Anal. , vol.56 , Issue.4 , pp. 928-942
    • Verwaeren, J.1    Waegeman, W.2    De Baets, B.3
  • 55
    • 70350772525 scopus 로고    scopus 로고
    • A hybrid genetic algorithm-adaptive network-based fuzzy inference system in prediction of wave parameters
    • M. Zanaganeh, S. Jamshid-Mousavi, and A.F. Etemad-Shahidi A hybrid genetic algorithm-adaptive network-based fuzzy inference system in prediction of wave parameters Eng. Appl. Artif. Intell. 22 8 2009 1194 1202
    • (2009) Eng. Appl. Artif. Intell. , vol.22 , Issue.8 , pp. 1194-1202
    • Zanaganeh, M.1    Jamshid-Mousavi, S.2    Etemad-Shahidi, A.F.3


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