000			04060nam a22006135i 4500
001			978-3-319-43871-9
003			DE-He213
005			20210118141209.0
007			cr nn 008mamaa
008			160928s2017 gw | s |||| 0|eng d
020			_a9783319438719 _9978-3-319-43871-9
024	7		_a10.1007/978-3-319-43871-9 _2doi
050		4	_aQ342
072		7	_aUYQ _2bicssc
072		7	_aTEC009000 _2bisacsh
072		7	_aUYQ _2thema
082	0	4	_a006.3 _223
100	1		_aIatan, Iuliana F. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aIssues in the Use of Neural Networks in Information Retrieval _h[electronic resource] / _cby Iuliana F. Iatan.
250			_a1st ed. 2017.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2017.
300			_aXIX, 199 p. 88 illus., 44 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aStudies in Computational Intelligence, _x1860-949X ; _v661
505	0		_aMathematical Aspects of Using Neural Approaches for Information Retrieval -- A Fuzzy Kwan- Cai Neural Network for Determining Image Similarity and for the Face Recognition -- Predicting Human Personality from Social Media using a Fuzzy Neural Network -- Modern Neural Methods for Function Approximation -- A Fuzzy Gaussian Clifford Neural Network -- Concurrent Fuzzy Neural Networks -- A New Interval Arithmetic Based Neural Network -- A Recurrent Neural Fuzzy Network.
520			_aThis book highlights the ability of neural networks (NNs) to be excellent pattern matchers and their importance in information retrieval (IR), which is based on index term matching. The book defines a new NN-based method for learning image similarity and describes how to use fuzzy Gaussian neural networks to predict personality. It introduces the fuzzy Clifford Gaussian network, and two concurrent neural models: (1) concurrent fuzzy nonlinear perceptron modules, and (2) concurrent fuzzy Gaussian neural network modules. Furthermore, it explains the design of a new model of fuzzy nonlinear perceptron based on alpha level sets and describes a recurrent fuzzy neural network model with a learning algorithm based on the improved particle swarm optimization method.
650		0	_aComputational intelligence.
650		0	_aArtificial intelligence.
650		0	_aNeural networks (Computer science) .
650		0	_aPattern recognition.
650	1	4	_aComputational Intelligence. _0http://scigraph.springernature.com/things/product-market-codes/T11014
650	2	4	_aArtificial Intelligence. _0http://scigraph.springernature.com/things/product-market-codes/I21000
650	2	4	_aMathematical Models of Cognitive Processes and Neural Networks. _0http://scigraph.springernature.com/things/product-market-codes/M13100
650	2	4	_aPattern Recognition. _0http://scigraph.springernature.com/things/product-market-codes/I2203X
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783319438702
776	0	8	_iPrinted edition: _z9783319438726
776	0	8	_iPrinted edition: _z9783319829302
830		0	_aStudies in Computational Intelligence, _x1860-949X ; _v661
856	4	0	_uhttps://doi.org/10.1007/978-3-319-43871-9
912			_aZDB-2-ENG
999			_c450119 _d450119
942			_cEB
506			_aAvailable to subscribing member institutions only. Доступно лише організаціям членам підписки.
506			_fOnline access from local network of NaUOA.
506			_fOnline access with authorization at https://link.springer.com/
506			_fОнлайн-доступ з локальної мережі НаУОА.
506			_fОнлайн доступ з авторизацією на https://link.springer.com/