1st Edition

Particle Swarm Optimisation Classical and Quantum Perspectives

By Jun Sun, Choi-Hong Lai, Xiao-Jun Wu Copyright 2012
419 Pages
by CRC Press

419 Pages
by CRC Press

419 Pages
by CRC Press

Although the particle swarm optimisation (PSO) algorithm requires relatively few parameters and is computationally simple and easy to implement, it is not a globally convergent algorithm. In Particle Swarm Optimisation: Classical and Quantum Perspectives , the authors introduce their concept of quantum-behaved particles inspired by quantum mechanics, which leads to the quantum-behaved particle... Read more

Introduction. Particle Swarm Optimisation. Some Variants of Particle Swarm Optimisation. Quantum-Behaved Particle Swarm Optimisation. Advanced Topics. Industrial Applications. Index.

Biography

Jun Sun is an associate professor in the Department of Computer Science and Technology at Jiangnan University. He is also a researcher at the Key Laboratory of Advanced Process Control for Light Industry in China. He has a Ph.D. in control theory and control engineering. His research interests include computational intelligence, numerical optimisation, and machine learning.





Choi-Hong Lai is a professor of numerical mathematics in the Department of Mathematical Sciences at the University of Greenwich. He has a Ph.D. in computational aerodynamics and PDEs. His research interests include numerical PDEs, numerical algorithms, and parallel algorithms for industrial applications, such as aeroacoustics, inverse problems, computational finance, and image processing.





Xiao-Jun Wu is a professor at Jiangnan University. He has a Ph.D. in pattern recognition and intelligent systems. He has published more than 150 papers on pattern recognition, computer vision, fuzzy systems, neural networks, and intelligent systems.