dc.contributor.author | Gutiérrez Llorente, José Manuel | es_ES |
dc.contributor.author | San Martín Segura, Daniel | es_ES |
dc.contributor.author | Herrera García, Sixto | es_ES |
dc.contributor.author | Cofiño González, Antonio Santiago | es_ES |
dc.contributor.other | Universidad de Cantabria | es_ES |
dc.date.accessioned | 2019-02-15T17:12:18Z | |
dc.date.available | 2019-02-15T17:12:18Z | |
dc.date.issued | 2016 | es_ES |
dc.identifier.issn | 1029-7006 | es_ES |
dc.identifier.issn | 1607-7962 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10902/15719 | |
dc.format.extent | 1 p. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Copernicus GmbH | es_ES |
dc.rights | Atribución 3.0 España | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.source | Geophysical Research Abstracts - Vol. 18, EGU2016-17561, 2016 | es_ES |
dc.title | Learning Bayesian networks from big meteorological spatial datasets. An
alternative to complex network analysis | es_ES |
dc.type | info:eu-repo/semantics/conferenceObject | es_ES |
dc.rights.accessRights | openAccess | es_ES |
dc.type.version | publishedVersion | es_ES |