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Particle Swarm Optimisation: Classical and Quantum Perspectives
This book focuses on the fundamental principles and applications of PSO and QPSO algorithms, and covers advanced topics that establish the groundwork for understanding state-of-the-art research in the field.
A Novel and More Efficient Search Strategy of Quantum-Behaved Particle Swarm Optimization
A novel and more efficient search strategy with a selection operation is introduced into Q PSO to improve the search ability of QPSO and the experiment results show that MQPSO has stronger global search ability.
Convergence analysis and improvements of quantum-behaved particle swarm optimization
Numerical Techniques for Direct and Large-Eddy Simulations
[Publisher's description] Compared to the traditional modeling of computational fluid dynamics, direct numerical simulation (DNS) and large-eddy simulation (LES) provide a very detailed solution of…
Parallel quantum-behaved particle swarm optimization
The master–slave and static subpopulation parallel QPSO models are investigated and applied to solve the inverse heat conduction problem of identifying the unknown boundary shape and the performance of all these parallel models is compared.
An improved quantum-behaved particle swarm optimization and its application to medical image registration
- Di Zhou, Jun Sun, Choi-Hong Lai, Wenbo Xu, Xiaoguang Lee
- Computer ScienceInt. J. Comput. Math.
- 1 April 2011
This paper investigates the quantum-behaved particle swarm optimization (QPSO) algorithm from the perspective of estimation of distribution algorithm (EDA) which reveals the reason of QPSO's superiority and presents a diversity-controlled RZPSO (DRQPSo) algorithm, which helps prevent the evolutionary algorithms’ tendency to be easily trapped into local optima as a result of rapid decline in diversity.
Simultaneous estimation of nonlinear parameters in parabolic partial differential equation using quantum-behaved particle swarm optimization with Gaussian mutation
An improved quantum-behaved particle swarm optimization with Gaussian mutation with Tikhonov regularization technique is proposed to simultaneously estimate nonlinear parameters in a one-dimensional parabolic partial differential equation (PDE).
Solving the multi-stage portfolio optimization problem with a novel particle swarm optimization
On the coupling of Navier–Stokes and linearised Euler equations for aeroacoustic simulation
Abstract.Aerodynamic generation of sound is governed by the Navier–Stokes equations while acoustic propagation in a non-uniform medium is effectively described by the linearised Euler equations.…
A Concise Introduction to Image Processing using C
A Concise Intro to Image Processing using C++ presents state-of-the-art image processing methodology, including current industrial practices for image compression, image de-noising methods based on…