000			03663nam a22006735i 4500
001			978-3-319-46257-8
003			DE-He213
005			20200421111703.0
007			cr nn 008mamaa
008			160912s2016 gw | s |||| 0|eng d
020			_a9783319462578 _9978-3-319-46257-8
024	7		_a10.1007/978-3-319-46257-8 _2doi
050		4	_aQA76.9.D343
072		7	_aUNF _2bicssc
072		7	_aUYQE _2bicssc
072		7	_aCOM021030 _2bisacsh
082	0	4	_a006.312 _223
245	1	0	_aIntelligent Data Engineering and Automated Learning - IDEAL 2016 _h[electronic resource] : _b17th International Conference, Yangzhou, China, October 12-14, 2016, Proceedings / _cedited by Hujun Yin, Yang Gao, Bin Li, Daoqiang Zhang, Ming Yang, Yun Li, Frank Klawonn, Antonio J. Tall�on-Ballesteros.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016.
300			_aXVI, 647 p. 209 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aLecture Notes in Computer Science, _x0302-9743 ; _v9937
505	0		_aResearch outcomes in data engineering and automated learning -- Methodologies, frameworks, and techniques -- Applications including various topics such as evolutionary algorithms; deep learning; neural networks; probabilistic modeling; particle swarm intelligence; big data analysis -- Applications in regression, classification, clustering, medical and biological modeling and predication -- Text processing and image analysis.
520			_aThis book constitutes the refereed proceedings of the 17 International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2016, held in Yangzhou, China, in October 2016. The 68 full papers presented were carefully reviewed and selected from 115 submissions. They provide a valuable and timely sample of latest research outcomes in data engineering and automated learning ranging from methodologies, frameworks, and techniques to applications including various topics such as evolutionary algorithms; deep learning; neural networks; probabilistic modeling; particle swarm intelligence; big data analysis; applications in regression, classification, clustering, medical and biological modeling and predication; text processing and image analysis. .
650		0	_aComputer science.
650		0	_aComputers.
650		0	_aAlgorithms.
650		0	_aData mining.
650		0	_aInformation storage and retrieval.
650		0	_aArtificial intelligence.
650		0	_aPattern recognition.
650	1	4	_aComputer Science.
650	2	4	_aData Mining and Knowledge Discovery.
650	2	4	_aPattern Recognition.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aAlgorithm Analysis and Problem Complexity.
650	2	4	_aInformation Storage and Retrieval.
650	2	4	_aComputation by Abstract Devices.
700	1		_aYin, Hujun. _eeditor.
700	1		_aGao, Yang. _eeditor.
700	1		_aLi, Bin. _eeditor.
700	1		_aZhang, Daoqiang. _eeditor.
700	1		_aYang, Ming. _eeditor.
700	1		_aLi, Yun. _eeditor.
700	1		_aKlawonn, Frank. _eeditor.
700	1		_aTall�on-Ballesteros, Antonio J. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783319462561
830		0	_aLecture Notes in Computer Science, _x0302-9743 ; _v9937
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-319-46257-8
912			_aZDB-2-SCS
912			_aZDB-2-LNC
942			_cEBK
999			_c55078 _d55078