000			02019nam a22004333i 4500
001			EBC5157319
003			MiAaPQ
005			20240729131619.0
006			m o d |
007			cr cnu||||||||
008			240724s2017 xx o ||||0 eng d
020			_a9783110520651 _q(electronic bk.)
020			_z9783110518702
035			_a(MiAaPQ)EBC5157319
035			_a(Au-PeEL)EBL5157319
035			_a(CaPaEBR)ebr11497577
035			_a(OCoLC)1020026051
040			_aMiAaPQ _beng _erda _epn _cMiAaPQ _dMiAaPQ
050		4	_aQA9.64 .F369 2018
100	1		_aLi, Fanzhang.
245	1	0	_aDynamic Fuzzy Machine Learning.
250			_a1st ed.
264		1	_aBerlin/Boston : _bWalter de Gruyter GmbH, _c2017.
264		4	_c©2018.
300			_a1 online resource (338 pages)
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
505	0		_aIntro -- Preface -- Contents -- 1. Dynamic fuzzy machine learning model -- 2. Dynamic fuzzy autonomic learning subspace algorithm -- 3. Dynamic fuzzy decision tree learning -- 4. Concept learning based on dynamic fuzzy sets -- 5. Semi-supervised multi-task learning based on dynamic fuzzy sets -- 6. Dynamic fuzzy hierarchical relationships -- 7. Multi-agent learning model based on dynamic fuzzy logic -- 8. Appendix -- Index.
588			_aDescription based on publisher supplied metadata and other sources.
590			_aElectronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
650		0	_aFuzzy logic.
655		4	_aElectronic books.
700	1		_aZhang, Li.
700	1		_aZhang, Zhao.
776	0	8	_iPrint version: _aLi, Fanzhang _tDynamic Fuzzy Machine Learning _dBerlin/Boston : Walter de Gruyter GmbH,c2017 _z9783110518702
797	2		_aProQuest (Firm)
856	4	0	_uhttps://ebookcentral.proquest.com/lib/orpp/detail.action?docID=5157319 _zClick to View
999			_c133195 _d133195