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Volumn 2660, Issue , 2003, Pages 289-298

Tornado detection with support vector machines

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; RADIAL BASIS FUNCTION NETWORKS; SURVEILLANCE RADAR; TORNADOES;

EID: 35248901936     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44864-0_30     Document Type: Article
Times cited : (29)

References (17)
  • 1
    • 27144489164 scopus 로고    scopus 로고
    • A Tutorial on Support Vector Machines for Pattern Classification
    • Burges, C.J.C.: A Tutorial on Support Vector Machines for Pattern Classification. Data Mining and Knowledge Discovery 2(2) (1998) 121-167
    • (1998) Data Mining and Knowledge Discovery , vol.2 , Issue.2 , pp. 121-167
    • Burges, C.J.C.1
  • 2
    • 0000913324 scopus 로고    scopus 로고
    • SVMTorch: Support vector machines for large-scale regression problems
    • Collobert, R., Bengio, S.: SVMTorch: Support vector machines for large-scale regression problems. Journal of Machine Learning Research 1 (2001) 143-160
    • (2001) Journal of Machine Learning Research , vol.1 , pp. 143-160
    • Collobert, R.1    Bengio, S.2
  • 3
    • 34249753618 scopus 로고
    • Support Vector Networks
    • Cortes, C., Vapnik, V.: Support Vector Networks. Machine Learning 20 (1995) 273-297
    • (1995) Machine Learning , vol.20 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 4
    • 0000249788 scopus 로고    scopus 로고
    • An Equivalence between Sparse Approximation and Support Vector Machines
    • Girosi, F.: An Equivalence Between Sparse Approximation and Support Vector Machines. Neural Computation 10(6) (1998) 1455-1480
    • (1998) Neural Computation , vol.10 , Issue.6 , pp. 1455-1480
    • Girosi, F.1
  • 5
    • 0001712213 scopus 로고    scopus 로고
    • A Neural Network for Tornado Prediction Based on Doppler Radar-Derived Attributes
    • Marzban, C., Stumpf, G.J.: A Neural Network for Tornado Prediction Based on Doppler Radar-Derived Attributes. Journal of Applied Meteorology 35(5) (1996) 617-626
    • (1996) Journal of Applied Meteorology , vol.35 , Issue.5 , pp. 617-626
    • Marzban, C.1    Stumpf, G.J.2
  • 7
    • 0003425668 scopus 로고    scopus 로고
    • Technical Report, Massachusetts Institute of Technology, Artificial Intelligence Laboratory
    • Pontil, M., Verri, A.: Properties of Support Vector Machines. Technical Report, Massachusetts Institute of Technology, Artificial Intelligence Laboratory (1997)
    • (1997) Properties of Support Vector Machines
    • Pontil, M.1    Verri, A.2
  • 10
    • 0033924470 scopus 로고    scopus 로고
    • Use of the "Odds Ratio" for Diagnosing Forecast Skill
    • Stephenson, D.B.: Use of the "Odds Ratio" for Diagnosing Forecast Skill. Weather and Forecasting 15(4) (2000) 221-232
    • (2000) Weather and Forecasting , vol.15 , Issue.4 , pp. 221-232
    • Stephenson, D.B.1
  • 13
    • 35248867149 scopus 로고    scopus 로고
    • Data Mining Techniques for Tornadic Pattern Recognition
    • C.H. Dagli, A.L. Buczak, J. Ghosh, M. Embrechts, O. Ersoy, and S. Kercel, editors, ASME
    • Trafalis, T.B., White, A., Fras, A.: Data Mining Techniques for Tornadic Pattern Recognition. In: C.H. Dagli, A.L. Buczak, J. Ghosh, M. Embrechts, O. Ersoy, and S. Kercel, editors, Intelligent Engineering Systems Through Artificial Neural Networks 10 ASME (2000) 455-460
    • (2000) Intelligent Engineering Systems Through Artificial Neural Networks , vol.10 , pp. 455-460
    • Trafalis, T.B.1    White, A.2    Fras, A.3
  • 16
    • 0003241883 scopus 로고
    • Splines Models for Observational Data
    • SIAM
    • Wahba, G.: Splines Models for Observational Data. Series in Applied Mathematics 59 SIAM (1990)
    • (1990) Series in Applied Mathematics , vol.59
    • Wahba, G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.