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020 _a9783319196350
_9978-3-319-19635-0
024 7 _a10.1007/978-3-319-19635-0
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
100 1 _aCouceiro, Micael.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_960208
245 1 0 _aFractional Order Darwinian Particle Swarm Optimization
_h[electronic resource] :
_bApplications and Evaluation of an Evolutionary Algorithm /
_cby Micael Couceiro, Pedram Ghamisi.
250 _a1st ed. 2016.
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
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Applied Sciences and Technology,
_x2191-5318
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 _aComputational intelligence.
_97716
650 0 _aArtificial intelligence.
_93407
650 0 _aSystem theory.
_93409
650 0 _aControl theory.
_93950
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aSystems Theory, Control .
_931597
700 1 _aGhamisi, Pedram.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_960209
710 2 _aSpringerLink (Online service)
_960210
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319196367
776 0 8 _iPrinted edition:
_z9783319196343
830 0 _aSpringerBriefs in Applied Sciences and Technology,
_x2191-5318
_960211
856 4 0 _uhttps://doi.org/10.1007/978-3-319-19635-0
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c80499
_d80499