000 | 02909nam a22005055i 4500 | ||
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001 | 978-3-319-19635-0 | ||
003 | DE-He213 | ||
005 | 20200420221248.0 | ||
007 | cr nn 008mamaa | ||
008 | 150616s2016 gw | s |||| 0|eng d | ||
020 |
_a9783319196350 _9978-3-319-19635-0 |
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024 | 7 |
_a10.1007/978-3-319-19635-0 _2doi |
|
050 | 4 | _aQ342 | |
072 | 7 |
_aUYQ _2bicssc |
|
072 | 7 |
_aCOM004000 _2bisacsh |
|
082 | 0 | 4 |
_a006.3 _223 |
100 | 1 |
_aCouceiro, Micael. _eauthor. |
|
245 | 1 | 0 |
_aFractional Order Darwinian Particle Swarm Optimization _h[electronic resource] : _bApplications and Evaluation of an Evolutionary Algorithm / _cby Micael Couceiro, Pedram Ghamisi. |
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016. |
|
300 |
_aX, 75 p. 27 illus., 24 illus. in color. _bonline resource. |
||
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 |
_aSpringerBriefs in Applied Sciences and Technology, _x2191-530X |
|
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 | _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. | ||
650 | 0 | _aEngineering. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aSystem theory. | |
650 | 0 | _aComputational intelligence. | |
650 | 1 | 4 | _aEngineering. |
650 | 2 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
650 | 2 | 4 | _aSystems Theory, Control. |
700 | 1 |
_aGhamisi, Pedram. _eauthor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783319196343 |
830 | 0 |
_aSpringerBriefs in Applied Sciences and Technology, _x2191-530X |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-319-19635-0 |
912 | _aZDB-2-ENG | ||
942 | _cEBK | ||
999 |
_c52451 _d52451 |