Machine learning methods in the environmental sciences: neural networks and kernels
Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of machine learning methods and their applications in the environmental sciences. Due to their...
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2009
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| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 URL des Erstveröffentlichers |
| Zusammenfassung: | Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of machine learning methods and their applications in the environmental sciences. Due to their powerful nonlinear modelling capability, machine learning methods today are used in satellite data processing, general circulation models(GCM), weather and climate prediction, air quality forecasting, analysis and modelling of environmental data, oceanographic and hydrological forecasting, ecological modelling, and monitoring of snow, ice and forests. The book includes end-of-chapter review questions and an appendix listing web sites for downloading computer code and data sources. A resources website containing datasets for exercises, and password-protected solutions are available. The book is suitable for first-year graduate students and advanced undergraduates. It is also valuable for researchers and practitioners in environmental sciences interested in applying these new methods to their own work |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 05 Oct 2015) |
| Beschreibung: | 1 online resource (xiii, 349 pages) |
| ISBN: | 9780511627217 |
| DOI: | 10.1017/CBO9780511627217 |
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Datensatz im Suchindex
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| dewey-full | 006.31 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.31 |
| dewey-search | 006.31 |
| dewey-sort | 16.31 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| doi_str_mv | 10.1017/CBO9780511627217 |
| format | Electronic eBook |
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| id | DE-604.BV043943263 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:39:19Z |
| institution | BVB |
| isbn | 9780511627217 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029352233 |
| oclc_num | 851100427 |
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| owner_facet | DE-12 DE-92 |
| physical | 1 online resource (xiii, 349 pages) |
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| publishDate | 2009 |
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| publisher | Cambridge University Press |
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| spelling | Hsieh, William Wei 1955- Verfasser aut Machine learning methods in the environmental sciences neural networks and kernels William W. Hsieh Cambridge Cambridge University Press 2009 1 online resource (xiii, 349 pages) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 05 Oct 2015) Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of machine learning methods and their applications in the environmental sciences. Due to their powerful nonlinear modelling capability, machine learning methods today are used in satellite data processing, general circulation models(GCM), weather and climate prediction, air quality forecasting, analysis and modelling of environmental data, oceanographic and hydrological forecasting, ecological modelling, and monitoring of snow, ice and forests. The book includes end-of-chapter review questions and an appendix listing web sites for downloading computer code and data sources. A resources website containing datasets for exercises, and password-protected solutions are available. The book is suitable for first-year graduate students and advanced undergraduates. It is also valuable for researchers and practitioners in environmental sciences interested in applying these new methods to their own work Machine learning Environmental sciences Umweltwissenschaften (DE-588)4137364-9 gnd rswk-swf Methode (DE-588)4038971-6 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Umweltwissenschaften (DE-588)4137364-9 s Maschinelles Lernen (DE-588)4193754-5 s Methode (DE-588)4038971-6 s 1\p DE-604 Erscheint auch als Druckausgabe 978-0-521-79192-2 Erscheint auch als Druckausgabe 978-0-521-79642-2 https://doi.org/10.1017/CBO9780511627217 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Hsieh, William Wei 1955- Machine learning methods in the environmental sciences neural networks and kernels Machine learning Environmental sciences Umweltwissenschaften (DE-588)4137364-9 gnd Methode (DE-588)4038971-6 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| subject_GND | (DE-588)4137364-9 (DE-588)4038971-6 (DE-588)4193754-5 |
| title | Machine learning methods in the environmental sciences neural networks and kernels |
| title_auth | Machine learning methods in the environmental sciences neural networks and kernels |
| title_exact_search | Machine learning methods in the environmental sciences neural networks and kernels |
| title_full | Machine learning methods in the environmental sciences neural networks and kernels William W. Hsieh |
| title_fullStr | Machine learning methods in the environmental sciences neural networks and kernels William W. Hsieh |
| title_full_unstemmed | Machine learning methods in the environmental sciences neural networks and kernels William W. Hsieh |
| title_short | Machine learning methods in the environmental sciences |
| title_sort | machine learning methods in the environmental sciences neural networks and kernels |
| title_sub | neural networks and kernels |
| topic | Machine learning Environmental sciences Umweltwissenschaften (DE-588)4137364-9 gnd Methode (DE-588)4038971-6 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| topic_facet | Machine learning Environmental sciences Umweltwissenschaften Methode Maschinelles Lernen |
| url | https://doi.org/10.1017/CBO9780511627217 |
| work_keys_str_mv | AT hsiehwilliamwei machinelearningmethodsintheenvironmentalsciencesneuralnetworksandkernels |