000 | 03368nam a22005655i 4500 | ||
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001 | 978-3-319-43871-9 | ||
003 | DE-He213 | ||
005 | 20220801220925.0 | ||
007 | cr nn 008mamaa | ||
008 | 160928s2017 sz | s |||| 0|eng d | ||
020 |
_a9783319438719 _9978-3-319-43871-9 |
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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 _953138 |
|
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. |
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300 |
_aXIX, 199 p. 88 illus., 44 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aStudies in Computational Intelligence, _x1860-9503 ; _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. _97716 |
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650 | 0 |
_aArtificial intelligence. _93407 |
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650 | 0 |
_aNeural networks (Computer science) . _953139 |
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650 | 0 |
_aPattern recognition systems. _93953 |
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650 | 1 | 4 |
_aComputational Intelligence. _97716 |
650 | 2 | 4 |
_aArtificial Intelligence. _93407 |
650 | 2 | 4 |
_aMathematical Models of Cognitive Processes and Neural Networks. _932913 |
650 | 2 | 4 |
_aAutomated Pattern Recognition. _931568 |
710 | 2 |
_aSpringerLink (Online service) _953140 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783319438702 |
776 | 0 | 8 |
_iPrinted edition: _z9783319438726 |
776 | 0 | 8 |
_iPrinted edition: _z9783319829302 |
830 | 0 |
_aStudies in Computational Intelligence, _x1860-9503 ; _v661 _953141 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-319-43871-9 |
912 | _aZDB-2-ENG | ||
912 | _aZDB-2-SXE | ||
942 | _cEBK | ||
999 |
_c79092 _d79092 |