000			01881nam a22003615i 4500
001			320687
003			MX-SnUAN
005			20160429161431.0
007			cr nn 008mamaa
008			160111s2015 gw | s |||| 0|eng d
020			_a9783319172200 _9978-3-319-17220-0
035			_avtls000420634
039		9	_y201601110949 _zstaff
050		4	_aQC851-999
245	1	0	_aMachine learning and data mining approaches to climate science : _bproceedings of the 4th international workshop on climate informatics / _cedited by Valliappa Lakshmanan, Eric Gilleland, Amy McGovern, Martin Tingley.
264		1	_aCham : _bSpringer International Publishing : _bSpringer, _c2015.
300			_aix, 252 páginas : _b89 ilustraciones, 73 ilustraciones en color.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
500			_aSpringer eBooks
505	0		_aFrom the Contents: Machine learning, statistics, or data mining, applied to climate science -- Management and processing of large climate datasets -- Long and short-term climate prediction -- Ensemble characterization of climate model projections -- Past (paleo) climate reconstruction.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aLakshmanan, Valliappa, _eeditor. _9353452
700	1		_aGilleland, Eric, _eeditor. _9365460
700	1		_aMcGovern, Amy, _eeditor. _9365461
700	1		_aTingley, Martin, _eeditor. _9365462
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783319172194
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-319-17220-0 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942			_c14
999			_c320687 _d320687