Sun, Jun, 1971-
Particle swarm optimisation classical and quantum perspectives / [electronic resource] : Jun Sun, Choi-Hong Lai, Xiao-Jun Wu. - Boca Raton [Fla.] : CRC Press, 2012. - xxii, 393 p. : ill. - Chapman and Hall/CRC numerical analysis and scientific computing . - Chapman & Hall/CRC numerical analysis and scientific computing. .
"A Chapman & Hall book."
Includes bibliographical references and index.
"This volume provides a detailed description of the state of the art of particle swarm optimization (PSO) and quantum-behaved particle swarm optimization (QPSO) algorithms. The authors present the motivation, principles, and theoretical analysis of the algorithms. They discuss advanced topics such as the behavior of individual particles, global convergence, time complexity, and rate of convergence. The authors also present various examples and applications to show the applicability of QPSO algorithms. In addition, the book includes the source code of the algorithm"--
Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.
Mathematical optimization.
Particles (Nuclear physics)
Swarm intelligence.
Electronic books.
QC20.7.M27 / S86 2012
531/.16
Particle swarm optimisation classical and quantum perspectives / [electronic resource] : Jun Sun, Choi-Hong Lai, Xiao-Jun Wu. - Boca Raton [Fla.] : CRC Press, 2012. - xxii, 393 p. : ill. - Chapman and Hall/CRC numerical analysis and scientific computing . - Chapman & Hall/CRC numerical analysis and scientific computing. .
"A Chapman & Hall book."
Includes bibliographical references and index.
"This volume provides a detailed description of the state of the art of particle swarm optimization (PSO) and quantum-behaved particle swarm optimization (QPSO) algorithms. The authors present the motivation, principles, and theoretical analysis of the algorithms. They discuss advanced topics such as the behavior of individual particles, global convergence, time complexity, and rate of convergence. The authors also present various examples and applications to show the applicability of QPSO algorithms. In addition, the book includes the source code of the algorithm"--
Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.
Mathematical optimization.
Particles (Nuclear physics)
Swarm intelligence.
Electronic books.
QC20.7.M27 / S86 2012
531/.16