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Machine learning and data mining approaches to climate science[electronic resource] :proceedings of the 4th International Workshop on Climate Informatics /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	551.6
書名/作者:	Machine learning and data mining approaches to climate science : proceedings of the 4th International Workshop on Climate Informatics // edited by Valliappa Lakshmanan ... [et al.].
其他作者:	Lakshmanan, Valliappa.
團體作者:	Clark Conference
出版者:	Cham : : Springer International Publishing :, 2015.
面頁冊數:	ix, 252 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Climatic changes - Congresses. - Data processng
標題:	Climatology - Congresses. - Data processing
標題:	Environmental sciences - Congresses. - Data processingv
標題:	Earth Sciences.
標題:	Atmospheric Sciences.
標題:	Climatology.
標題:	Climate Change.
ISBN:	9783319172200 (electronic bk.)
ISBN:	9783319172194 (paper)
內容註:	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.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-17220-0

Machine learning and data mining approaches to climate science[electronic resource] :proceedings of the 4th International Workshop on Climate Informatics /
Machine learning and data mining approaches to climate scienceproceedings of the 4th International Workshop on Climate Informatics /[electronic resource] :edited by Valliappa Lakshmanan ... [et al.]. - Cham :Springer International Publishing :2015. - ix, 252 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9783319172200 (electronic bk.)

Standard No.: 10.1007/978-3-319-17220-0doiSubjects--Topical Terms:

627152
Climatic changes
--Data processng--Congresses.

LC Class. No.: QC981

Dewey Class. No.: 551.6

Machine learning and data mining approaches to climate science[electronic resource] :proceedings of the 4th International Workshop on Climate Informatics /
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