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Particle swarm optimisation [electronic resource] : classical and quantum perspectives / Jun Sun, Choi-Hong Lai, Xiao-Jun Wu.

By: Contributor(s): Material type: TextTextSeries: Chapman & Hall/CRC numerical analysis and scientific computingPublication details: Boca Raton, Fla. : CRC Press, c2012.Description: xxii, 397 p. : illISBN:
  • 9781439835777 (ebook : PDF)
Subject(s): Genre/Form: Additional physical formats: No titleOnline resources: Available additional physical forms:
  • Also available in print edition.
Contents:
ch. 1. Introduction -- ch. 2. Particle swarm optimisation -- ch. 3. Some variants of particle swarm optimisation -- ch. 4. Quantum-behaved particle swarm optimisation -- ch. 5. Advanced topics -- ch. 6. Industrial applications.
Summary: "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"--Provided by publisher.
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"A Chapman & Hall book."

Includes bibliographical references and index.

ch. 1. Introduction -- ch. 2. Particle swarm optimisation -- ch. 3. Some variants of particle swarm optimisation -- ch. 4. Quantum-behaved particle swarm optimisation -- ch. 5. Advanced topics -- ch. 6. Industrial applications.

"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"--Provided by publisher.

Also available in print edition.

Mode of access: World Wide Web.

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