Machine Learning and Data Mining Approaches to Climate Science
Springer International Publishing
Title |
Machine Learning and Data Mining Approaches to Climate Science
|
---|---|
Published by |
Springer International Publishing, January 2015
|
DOI | 10.1007/978-3-319-17220-0 |
ISBNs |
978-3-31-917219-4, 978-3-31-917220-0
|
Editors |
Valliappa Lakshmanan, Eric Gilleland, Amy McGovern, Martin Tingley |
Country | Count | As % |
---|---|---|
United States | 2 | 67% |
Unknown | 1 | 33% |
Type | Count | As % |
---|---|---|
Members of the public | 3 | 100% |
Country | Count | As % |
---|---|---|
Malaysia | 1 | <1% |
United States | 1 | <1% |
Russia | 1 | <1% |
Germany | 1 | <1% |
Unknown | 139 | 97% |
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 29 | 20% |
Student > Ph. D. Student | 25 | 17% |
Researcher | 23 | 16% |
Student > Doctoral Student | 13 | 9% |
Professor > Associate Professor | 8 | 6% |
Other | 20 | 14% |
Unknown | 25 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Earth and Planetary Sciences | 34 | 24% |
Engineering | 21 | 15% |
Computer Science | 15 | 10% |
Environmental Science | 13 | 9% |
Physics and Astronomy | 9 | 6% |
Other | 20 | 14% |
Unknown | 31 | 22% |