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Volumn 318, Issue 1-4, 2006, Pages 7-16

Multi-time scale stream flow predictions: The support vector machines approach

Author keywords

Multi scale; Sea surface temperature anomalies; Stream flow forecasting; Support vector machines

Indexed keywords

CLIMATOLOGY; OPTIMIZATION; WATER RESOURCES;

EID: 31044438334     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2005.06.001     Document Type: Article
Times cited : (250)

References (25)
  • 1
    • 0034174396 scopus 로고    scopus 로고
    • Artificial neural networks in hydrology. II: Hydrologic applications
    • Rao Govindaraju, and ASCE Task Committee on Application of Artificial Neural Networks in Hydrology Artificial neural networks in hydrology. II: hydrologic applications J. Hydrol. Eng. 5 2 2000 124 137
    • (2000) J. Hydrol. Eng. , vol.5 , Issue.2 , pp. 124-137
    • Govindaraju, R.1
  • 2
    • 10944257448 scopus 로고    scopus 로고
    • Support vector machines approximation of flow and transport models in initial groundwater contamination network design
    • T. Asefa, and M.W. Kemblowski Support vector machines approximation of flow and transport models in initial groundwater contamination network design Eos. Trans. AGU. 83 47 Fall Meet. Suppl. 2002 Abstract H72D-0882
    • (2002) Eos. Trans. AGU. , vol.83 , Issue.47 FALL MEET. SUPPL.
    • Asefa, T.1    Kemblowski, M.W.2
  • 3
    • 10944274219 scopus 로고    scopus 로고
    • Support vectors-based groundwater head observation networks design
    • 101029/2004WR003304
    • T. Asefa, M.W. Kemblowski, G. Urroz, M. McKee, and A. Khalil Support vectors-based groundwater head observation networks design Water Resour. Res. 40 2004 W11509 10.1029/2004WR003304
    • (2004) Water Resour. Res. , vol.40 , pp. 11509
    • Asefa, T.1    Kemblowski, M.W.2    Urroz, G.3    McKee, M.4    Khalil, A.5
  • 6
    • 0003485656 scopus 로고    scopus 로고
    • Introduction to Time Series and Forecasting
    • first ed Springer Berlin
    • P.J. Brockwell, and R.A. Davis Introduction to Time Series and Forecasting first ed Springer Texts in Statistics 1996 Springer Berlin
    • (1996) Springer Texts in Statistics
    • Brockwell, P.J.1    Davis, R.A.2
  • 7
    • 34249753618 scopus 로고
    • Support vector networks
    • C. Cortes, and V. Vapnik Support vector networks Mach. Learn. 20 1995 273 297
    • (1995) Mach. Learn. , vol.20 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 9
    • 0035398081 scopus 로고    scopus 로고
    • Model induction with support vector machines: Introduction and applications
    • B.Y. Dibike, S. Velickov, D. Solomatine, and M.B. Abbott Model induction with support vector machines: introduction and applications J. Comput. Civil Eng. 15 3 2001 208 216
    • (2001) J. Comput. Civil Eng. , vol.15 , Issue.3 , pp. 208-216
    • Dibike, B.Y.1    Velickov, S.2    Solomatine, D.3    Abbott, M.B.4
  • 11
    • 0000249788 scopus 로고    scopus 로고
    • An equivalence between sparse approximation and support vector machines
    • Girosi, F. (1998), An equivalence between sparse approximation and support vector machines, Neural Computation, 10(6):1455-1480.
    • (1998) Neural Computation , vol.10 , Issue.6 , pp. 1455-1480
    • Girosi, F.1
  • 12
    • 0005396750 scopus 로고
    • Automatic capacity tuning of very large VC-dimension classifiers
    • S. José Hanson J.D. Cowan C. Lee Giles Morgan Kaufmann San Mateo, CA
    • I. Guyon, B. Boser, and V. Vapnik Automatic capacity tuning of very large VC-dimension classifiers S. José Hanson J.D. Cowan C. Lee Giles Advances in Neural Information Processing Systems vol. 5 1993 Morgan Kaufmann San Mateo, CA 147 155
    • (1993) Advances in Neural Information Processing Systems , vol.5 , pp. 147-155
    • Guyon, I.1    Boser, B.2    Vapnik, V.3
  • 13
    • 0031390898 scopus 로고    scopus 로고
    • Reduced space optimal analysis for historical datasets: 136 years of Atlantic sea surface temperatures
    • A. Kaplan, Y. Kushnir, M. Cane, and M. Blumenthal Reduced space optimal analysis for historical datasets: 136 years of Atlantic sea surface temperatures J. Geophys. Res. 102 1997 27835 27860
    • (1997) J. Geophys. Res. , vol.102 , pp. 27835-27860
    • Kaplan, A.1    Kushnir, Y.2    Cane, M.3    Blumenthal, M.4
  • 16
    • 31044447571 scopus 로고    scopus 로고
    • Flood stage forecasting with SVM
    • S.Y. Liong, and C. Sivapragasam Flood stage forecasting with SVM AWRA 38 1 2002 118 173
    • (2002) AWRA , vol.38 , Issue.1 , pp. 118-173
    • Liong, S.Y.1    Sivapragasam, C.2
  • 17
    • 0002941010 scopus 로고    scopus 로고
    • Support vector machines for dynamic reconstruction of a chaotic system
    • C.J.C. Burges A.J. Smola MIT Press Cambridge, MA
    • D. Mattera, and S. Haykin Support vector machines for dynamic reconstruction of a chaotic system C.J.C. Burges A.J. Smola Advances in Kernel Methods: Support Vector Learning 1999 MIT Press Cambridge, MA 211 242
    • (1999) Advances in Kernel Methods: Support Vector Learning , pp. 211-242
    • Mattera, D.1    Haykin, S.2
  • 18
    • 0030112417 scopus 로고    scopus 로고
    • Large scale atmospheric indices and the Great Salt Lake: Interannual and interdecadal variability
    • Y.-I. Moon, and U. Lall Large scale atmospheric indices and the Great Salt Lake: interannual and interdecadal variability ASCE J. Hydrol. Eng. 1 2 1996
    • (1996) ASCE J. Hydrol. Eng. , vol.1 , Issue.2
    • Moon, Y.-I.1    Lall, U.2
  • 24
    • 84887252594 scopus 로고    scopus 로고
    • Support vector method for function approximation, regression estimation, and signal processing
    • M. Mozer M. Jordan T. Petsche MIT Press Cambridge, MA
    • V. Vapnik, S. Golowich, and A. Smola Support vector method for function approximation, regression estimation, and signal processing M. Mozer M. Jordan T. Petsche Advances in Neural Information Processing Systems vol. 9 1997 MIT Press Cambridge, MA 281 287
    • (1997) Advances in Neural Information Processing Systems , vol.9 , pp. 281-287
    • Vapnik, V.1    Golowich, S.2    Smola, A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.