| 000 | 02300nam a22003378i 4500 | ||
|---|---|---|---|
| 001 | CR9780511627217 | ||
| 003 | UkCbUP | ||
| 005 | 20200124160252.0 | ||
| 006 | m|||||o||d|||||||| | ||
| 007 | cr|||||||||||| | ||
| 008 | 090916s2009||||enk o ||1 0|eng|d | ||
| 020 | _a9780511627217 (ebook) | ||
| 020 | _z9780521791922 (hardback) | ||
| 020 | _z9780521796422 (paperback) | ||
| 040 |
_aUkCbUP _beng _erda _cUkCbUP |
||
| 050 | 0 | 0 |
_aGE45.D37 _bH75 2009 |
| 082 | 0 | 0 |
_a006.31 _222 |
| 100 | 1 |
_aHsieh, William Wei, _d1955- _eauthor. |
|
| 245 | 1 | 0 |
_aMachine learning methods in the environmental sciences : _bneural networks and kernels / _cWilliam W. Hsieh. |
| 264 | 1 |
_aCambridge : _bCambridge University Press, _c2009. |
|
| 300 |
_a1 online resource (xiii, 349 pages) : _bdigital, PDF file(s). |
||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
||
| 500 | _aTitle from publisher's bibliographic system (viewed on 05 Oct 2015). | ||
| 520 | _aMachine 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. | ||
| 650 | 0 | _aMachine learning. | |
| 650 | 0 | _aEnvironmental sciences. | |
| 776 | 0 | 8 |
_iPrint version: _z9780521791922 |
| 856 | 4 | 0 | _uhttps://doi.org/10.1017/CBO9780511627217 |
| 999 |
_c519634 _d519632 |
||