9783319172194-3319172190-Machine Learning and Data Mining Approaches to Climate Science: Proceedings of the 4th International Workshop on Climate Informatics

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

ISBN-13: 9783319172194
ISBN-10: 3319172190
Edition: 2015
Author: Valliappa Lakshmanan, Eric Gilleland, Amy McGovern, Martin Tingley
Publication date: 2015
Publisher: Springer
Format: Hardcover 261 pages
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ISBN-13: 9783319172194
ISBN-10: 3319172190
Edition: 2015
Author: Valliappa Lakshmanan, Eric Gilleland, Amy McGovern, Martin Tingley
Publication date: 2015
Publisher: Springer
Format: Hardcover 261 pages

Summary

Machine Learning and Data Mining Approaches to Climate Science: Proceedings of the 4th International Workshop on Climate Informatics (ISBN-13: 9783319172194 and ISBN-10: 3319172190), written by authors Valliappa Lakshmanan, Eric Gilleland, Amy McGovern, Martin Tingley, was published by Springer in 2015. With an overall rating of 4.1 stars, it's a notable title among other Climatology (Earth Sciences, Rivers, Nature & Ecology) books. You can easily purchase or rent Machine Learning and Data Mining Approaches to Climate Science: Proceedings of the 4th International Workshop on Climate Informatics (Hardcover) from BooksRun, along with many other new and used Climatology books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

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.

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