| Title: | Machine learning for spatial environmental data : Theory, applications and software |
| Authors: | Mikhail Kanevski ; Alexei Pozdnoukhov ; Vadim Timonin |
| Material Type: | Books |
| Publisher: | Boca Raton : CRC, 2009 |
| Article on page: | 1 vol. (VII, 377 p.) |
| ISBN (or other code): | 978-2-940222-24-7 |
| Languages: | English |
| Class number: | 550 (Sciences de la Terre) |
| Descriptors: | |
| Tags: | Geographic information systems ; Machine learning |
| Abstract: | The book presents the state of the art in machine learning algorithms (artificial neural networks of different architectures, support vector machines, etc.) as applied to the classification and mapping of spatially distributed environmental data. Basic geostatistical algorithms are presented as well. New trends in machine learning and their application to spatial data are given, and real case studies based on environmental and pollution data are carried out. The book provides a CD-ROM with the Machine Learning Office software, including sample sets of data, that will allow both students and researchers to put the concepts rapidly to practice |
Copies (1)
| Barcode | Call number | Media type | Location | Section | Status |
|---|---|---|---|---|---|
| 111922R | 550 KAN M | Book | Royal Military Academy | Bibliothèque ERM | Available |
