Prediction of extreme rainfall event using weather pattern recognition and support vector machine classifier
- Author
- MUNIR AHMAD NAYAK1 2 ; GHOSH, Subimal3
[1] Department of Civil Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400 076, India
[2] Civil and Environmental Engineering, Cornell University, Ithaca, NY 14853, United States
[3] Interdisciplinary Program on Climate Studies, Indian Institute of Technology Bombay, Powai, Mumbai 400 076, India - Source
Theoretical and applied climatology. 2013, Vol 114, Num 3-4, pp 583-603, 21 p ; ref : 1 p.1/4
- ISSN
- 0177-798X
- Scientific domain
- Environment; Climatology, meteorology
- Publisher
- Springer, Wien
- Publication country
- Austria
- Document type
- Article
- Language
- English
- Keyword (fr)
- Algorithme apprentissage Machine vecteur support Modèle prévision Pluie Précipitation atmosphérique Prévision courte échéance Prévision météorologique Prévision très courte échéance Reconnaissance forme Evénement extrême Inde Asie
- Keyword (en)
- Learning algorithm Support vector machine Forecast model rainfall atmospheric precipitation Short range forecast Weather forecast Very short range forecast pattern recognition Extreme event India Asia
- Keyword (es)
- Algoritmo aprendizaje Máquina vector soporte Modelo previsión Lluvia Precipitación atmosférica Predicción corto plazo Predicción meteorológica Predicción muy corto plazo Acontecimiento extremo India Asia
- Classification
- Pascal
- 001 Exact sciences and technology / 001E Earth, ocean, space / 001E02 External geophysics / 001E02D Meteorology / 001E02D14 Weather analysis and prediction
- Discipline
- External geophysics
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 27901097
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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DOI
10.1007/s00704-013-0867-3 
https://dx.doi.org/10.1007/s00704-013-0867-3
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