Machine Learning and Data Mining Approaches to Climate Science Proceedings of the 4th International Workshop on Climate Informatics /

This book presents innovative work in Climate Informatics, a new field that reflects the application of data mining methods to climate science, and shows where this new and fast growing field is headed. Given its interdisciplinary nature, Climate Informatics offers insights, tools and methods that a...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Lakshmanan, Valliappa (Editor ), Gilleland, Eric (Editor ), McGovern, Amy (Editor ), Tingley, Martin (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edición:1st ed. 2015.
Temas:
Atmospheric science.
Climatology.
Environment.
Atmospheric Science.
Climate Sciences.
Environmental Sciences.
Acceso en línea:Texto Completo

MARC

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245 1 0 |a Machine Learning and Data Mining Approaches to Climate Science  |h [electronic resource] :  |b Proceedings of the 4th International Workshop on Climate Informatics /  |c edited by Valliappa Lakshmanan, Eric Gilleland, Amy McGovern, Martin Tingley. 
250 |a 1st ed. 2015. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2015. 
300 |a IX, 252 p. 89 illus., 73 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
505 0 |a From the Contents: Machine learning, statistics, or data mining, applied to climate science -- Management and processing of large climate datasets -- Long and short-term climate prediction -- Ensemble characterization of climate model projections -- Past (paleo) climate reconstruction. 
520 |a This book presents innovative work in Climate Informatics, a new field that reflects the application of data mining methods to climate science, and shows where this new and fast growing field is headed. Given its interdisciplinary nature, Climate Informatics offers insights, tools and methods that are increasingly needed in order to understand the climate system, an aspect which in turn has become crucial because of the threat of climate change. There has been a veritable explosion in the amount of data produced by satellites, environmental sensors and climate models that monitor, measure and forecast the earth system. In order to meaningfully pursue knowledge discovery on the basis of such voluminous and diverse datasets, it is necessary to apply machine learning methods, and Climate Informatics lies at the intersection of machine learning and climate science. This book grew out of the fourth workshop on Climate Informatics held in Boulder, Colorado in Sep. 2014. 
650 0 |a Atmospheric science. 
650 0 |a Climatology. 
650 0 |a Environment. 
650 1 4 |a Atmospheric Science. 
650 2 4 |a Climate Sciences. 
650 2 4 |a Environmental Sciences. 
700 1 |a Lakshmanan, Valliappa.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a Gilleland, Eric.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a McGovern, Amy.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
700 1 |a Tingley, Martin.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783319172217 
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950 |a Earth and Environmental Science (SpringerNature-11646) 
950 |a Earth and Environmental Science (R0) (SpringerNature-43711) 

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