| 000 | 03097nam a22005055i 4500 | ||
|---|---|---|---|
| 001 | 978-3-642-28085-6 | ||
| 003 | DE-He213 | ||
| 005 | 20140220083310.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 120215s2012 gw | s |||| 0|eng d | ||
| 020 |
_a9783642280856 _9978-3-642-28085-6 |
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| 024 | 7 |
_a10.1007/978-3-642-28085-6 _2doi |
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| 050 | 4 | _aT55.4-60.8 | |
| 072 | 7 |
_aTGXW _2bicssc |
|
| 072 | 7 |
_aTEC040000 _2bisacsh |
|
| 072 | 7 |
_aTEC020000 _2bisacsh |
|
| 082 | 0 | 4 |
_a670 _223 |
| 100 | 1 |
_aQuiza, Ramón. _eauthor. |
|
| 245 | 1 | 0 |
_aHybrid Modeling and Optimization of Manufacturing _h[electronic resource] : _bCombining Artificial Intelligence and Finite Element Method / _cby Ramón Quiza, Omar López-Armas, J. Paulo Davim. |
| 264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2012. |
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| 300 |
_aVIII, 95p. 67 illus. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
||
| 490 | 1 |
_aSpringerBriefs in Applied Sciences and Technology, _x2191-530X |
|
| 505 | 0 | _aRelevance and convenience of hybrid (AI and FEM) modeling and optimization of manufacturing processes -- Approaches for combining AI and FEM -- FEM/AI models -- AI/FEM models -- Other approaches -- Artificial intelligence tools -- AI tools for modeling -- Artificial neural networks -- Fuzzy logic and neuro-fuzzy system -- Bayesian probability -- AI tool for optimization -- Evolutionary algorithms -- Swarm intelligence -- Finite element method for manufacturing modeling -- Plasticity models -- Constitutive equations -- Finite element discretization -- Case of study -- Experimental study -- FEM-based modeling -- AI-based modeling -- Optimization -- Concluding remarks. | |
| 520 | _aArtificial intelligence (AI) techniques and the finite element method (FEM) are both powerful computing tools, which are extensively used for modeling and optimizing manufacturing processes. The combination of these tools has resulted in a new flexible and robust approach as several recent studies have shown. This book aims to review the work already done in this field as well as to expose the new possibilities and foreseen trends. The book is expected to be useful for postgraduate students and researchers, working in the area of modeling and optimization of manufacturing processes. | ||
| 650 | 0 | _aEngineering. | |
| 650 | 0 | _aMaterials. | |
| 650 | 0 | _aStructural control (Engineering). | |
| 650 | 1 | 4 | _aEngineering. |
| 650 | 2 | 4 | _aOperating Procedures, Materials Treatment. |
| 650 | 2 | 4 | _aContinuum Mechanics and Mechanics of Materials. |
| 650 | 2 | 4 | _aComputational Intelligence. |
| 700 | 1 |
_aLópez-Armas, Omar. _eauthor. |
|
| 700 | 1 |
_aDavim, J. Paulo. _eauthor. |
|
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783642280849 |
| 830 | 0 |
_aSpringerBriefs in Applied Sciences and Technology, _x2191-530X |
|
| 856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-642-28085-6 |
| 912 | _aZDB-2-ENG | ||
| 999 |
_c102721 _d102721 |
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