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_aCouceiro, Micael _0Local _996999 |
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_aFractional Order Darwinian Particle Swarm Optimization : _bApplications and Evaluation of an Evolutionary Algorithm _cby Micael Couceiro, Pedram Ghamisi |
| 260 |
_aCham _bSpringer International Publishing _c2016 |
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| 300 |
_a1 recurso en línea (X, 75 páginas) _b27 ilustraciones, 24 ilustraciones en color |
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_aTexto _btxt _2rdacontent |
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_aelectrónico _bc _2rdamedia |
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_arecurso electrónico _bcr _2rdacarrier |
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_aSpringerBriefs in Applied Sciences and Technology _x2191-530X |
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| 505 | 0 | _aParticle Swarm Optimization (PSO) -- Fractional Order Darwinian PSO (FODPSO) -- Case Study I: Curve Fitting -- Case Study II: Image Segmentation -- Case Study III: Swarm Robotics -- Conclusions. | |
| 520 | 3 | _aThis book examines the bottom-up applicability of swarm intelligence to solving multiple problems, such as curve fitting, image segmentation, and swarm robotics. It compares the capabilities of some of the better-known bio-inspired optimization approaches, especially Particle Swarm Optimization (PSO), Darwinian Particle Swarm Optimization (DPSO) and the recently proposed Fractional Order Darwinian Particle Swarm Optimization (FODPSO), and comprehensively discusses their advantages and disadvantages. Further, it demonstrates the superiority and key advantages of using the FODPSO algorithm, such as its ability to provide an improved convergence towards a solution, while avoiding sub-optimality. This book offers a valuable resource for researchers in the fields of robotics, sports science, pattern recognition and machine learning, as well as for students of electrical engineering and computer science. | |
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_aSistemas, Teoría de _0 _2embne _9141328 |
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_aGhamisi, Pedram _0Local _997000 |
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_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-19635-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
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