Swarm intelligence
Robust Estimation of Camera Rotation, Translation and Focal Length at High Outlier Rates
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
A modified particle swarm optimizer using an adaptive dynamic weight scheme
ICDHM'07 Proceedings of the 1st international conference on Digital human modeling
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Three different variations of Particle Swarm Optimization (PSO) method are used to solve the inverse heat conduction problem, in one, two, and three dimensions. Both steady and transient problems are studied. Experimental results obtained from the thermocouples inside a hot plate in jet impingement problem are used as bench mark.. In this research, PSO is successfully applied to the inverse heat conduction problem, and it has alleviated some of the problems related to the instability of the classical optimization approaches. Some researches have shown that PSO can be an efficient way of solving the inverse heat conduction problem in terms of computational expense. In this research, we are mainly focused on the effect of noise in the domain, and the ability of PSO in dealing with such cases. This is very crucial, because most of the experimental engineering data is prone to some intrinsic errors in the measurements. Some ideas are proposed to make the inverse solution more robust in a noisy domain.