Quantum-Behaved Particle Swarm Optimization with Ring Topology and Its Application in Estimating Temperature-Dependent Thermal Conductivity

2011 ◽  
Vol 60 (2) ◽  
pp. 73-95 ◽  
Author(s):  
Na Tian ◽  
Jun Sun ◽  
Wenbo Xu ◽  
Choi-Hong Lai
2021 ◽  
Author(s):  
Hongmei Xu ◽  
Juan Liu ◽  
Kun Wang ◽  
Songtao Kong ◽  
Yong Shi

Abstract A hybrid fuzzy inference-quantum particle swarm optimization (FI-QPSO) algorithm is developed to estimate the temperature-dependent thermal properties of grain. The fuzzy inference scheme is established to determine the contraction-expansion coefficient according to the aggregation degree of particles. The heat transfer process in the grain bulk is solved using the finite element method (FEM), and the estimation task is formulated as an inverse problem. Numerical experiments are performed to study the effects of the surface heat flux, number of measurement points, measurement errors and the individual space on the estimation results. Comparison with the quantum particle swarm optimization (QPSO) algorithm and conjugate gradient method (CGM) is also conducted, and it shows the validity of the estimation method established in this paper.


IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 78453-78470 ◽  
Author(s):  
Guangzhi Xu ◽  
Xinchao Zhao ◽  
Tong Wu ◽  
Rui Li ◽  
Xingmei Li

Sign in / Sign up

Export Citation Format

Share Document