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| 003 | ES-MaUEC | ||
| 005 | 20230102121536.0 | ||
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| 007 | cr nn 008mamaa | ||
| 008 | 210517s2021 si | s |||| 0|eng d | ||
| 020 | _a9789811606625 | ||
| 024 | 7 |
_a10.1007/978-981-16-0662-5 _2doi |
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| 040 |
_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC |
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| 050 | 4 |
_aQ337.3 _b2021 EB |
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| 245 | 1 | 0 |
_aApplied Optimization and Swarm Intelligence _cedited by Eneko Osaba, Xin-She Yang. |
| 250 | _aFirst edition 2021 | ||
| 264 | 1 |
_aSingapore _bSpringer International Pulishing _c2021 |
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| 300 |
_a1 recurso en línea (XI, 229 páginas) _b47 ilustraciones, 26 ilustraciones a color |
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| 336 |
_2rdacontent _aTexto _btxt |
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| 337 |
_2rdamedia _aelectrónico _bc |
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| 338 |
_2rdacarrier _arecurso electrónico _bcr |
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| 347 |
_aarchivo de texto _bPDF |
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| 490 | 0 |
_aSpringer Tracts in Nature-Inspired Computing _x2524-5538 |
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| 490 | 0 | _aIntelligent Technologies and Robotics (SpringerNature-42732) | |
| 490 | 0 | _aIntelligent Technologies and Robotics (R0) (SpringerNature-43728) | |
| 505 | 0 | _aApplied Optimization and Swarm Intelligence: A Systematic Review and Prospect Opportunities -- A Review on Ensemble Methods and their Applications to Optimization Problems -- A Brief Overview of Swarm Intelligence-Based Algorithms for Numerical Association Rule Mining -- Review of Swarm Intelligence for Improving Time Series Forecasting -- Soccer-Inspired Metaheuristics: Systematic Review of Recent Research and Applications -- Formal Cognitive Modeling of Swarm Intelligence for Decision-Making Optimization Problems -- Nature-Inspired Optimization Algorithms for Path Planning and Fuzzy Tracking Control of Mobile Robots -- A Hardware Architecture and Physical Prototype for General-Purpose Swarm Minirobotics: Proteus II -- Evolving a Multi-Objective Optimization Framework -- Swarm Intelligence Based Optimum Design of Deep Excavation System. | |
| 520 | 3 | _aThis book gravitates on the prominent theories and recent developments of swarm intelligence methods, and their application in both synthetic and real-world optimization problems. The special interest will be placed in those algorithmic variants where biological processes observed in nature have underpinned the core operators underlying their search mechanisms. In other words, the book centers its attention on swarm intelligence and nature-inspired methods for efficient optimization and problem solving. The content of this book unleashes a great opportunity for researchers, lecturers and practitioners interested in swarm intelligence, optimization problems and artificial intelligence. | |
| 988 | _aSpringer_Robotics_2021 | ||
| 650 | 7 |
_2embne _9145705 _aOptimización matemática |
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| 700 | 1 |
_aOsaba, Eneko _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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| 700 |
_aYang, Xin-She. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _997941 |
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| 776 | 0 | 8 |
_iPrinted edition: _z9789811606618 |
| 776 | 0 | 8 |
_iPrinted edition: _z9789811606632 |
| 776 | 0 | 8 |
_iPrinted edition: _z9789811606649 |
| 856 | 4 | 0 |
_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-16-0662-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
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_2lcc _cLE |
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