000			02928nam a22003735i 4500
001			387196
003			ES-MaUEC
005			20230102122321.0
007			cr nn 008mamaa
008			220601s2008 sz | s |||| 0|eng d
020			_a9783031017049
024	7		_a10.1007/978-3-031-01704-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
050		4	_aQC20.7.M27 _b2008
100	1		_aMikki, Said _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aParticle Swarm Optimizaton _bA Physics-Based Approach _cby Said Mikki, Ahmed Kishk.
250			_a1st edition 2008
264		1	_aCham _bSpringer International Publishing _c2008
300			_a1 recurso en línea (IX, 93 páginas) _b
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Computational Electromagnetics _x1932-1716
505	0		_aIntroduction -- The Classical Particle Swarm Optimization Method -- Boundary Conditions for the PSO Method -- The Quantum Particle Swarm Optimization -- Bibliography.-Index.
520			_aThis work aims to provide new introduction to the particle swarm optimization methods using a formal analogy with physical systems. By postulating that the swarm motion behaves similar to both classical and quantum particles, we establish a direct connection between what are usually assumed to be separate fields of study, optimization and physics. Within this framework, it becomes quite natural to derive the recently introduced quantum PSO algorithm from the Hamiltonian or the Lagrangian of the dynamical system. The physical theory of the PSO is used to suggest some improvements in the algorithm itself, like temperature acceleration techniques and the periodic boundary condition. At the end, we provide a panorama of applications demonstrating the power of the PSO, classical and quantum, in handling difficult engineering problems. The goal of this work is to provide a general multi-disciplinary view on various topics in physics, mathematics, and engineering by illustrating their interdependence within the unified framework of the swarm dynamics. Table of Contents: Introduction / The Classical Particle Swarm Optimization Method / Boundary Conditions for the PSO Method / The Quantum Particle Swarm Optimization / Bibliography /Index.
700	1		_aKishk, Ahmed _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
776	0	8	_iPrinted edition: _z9783031005763
776	0	8	_iPrinted edition: _z9783031028328
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01704-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSynthesis Collection of Technology_2008
999			_c387196 _d387196