Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Artículo científico |
| Sprache: | en |
| Veröffentlicht: |
Universidad Nacional Autónoma de México
2015
|
| Schlagworte: | |
| Online-Zugang: | https://www.redalyc.org/articulo.oa?id=47439895005 |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Inhaltsangabe:
- An image reconstruction algorithm for electrical capacitance tomography based on simulated annealing particle swarm optimization Wang P. Lin J.S. Wang M. Ingeniería particle swarm optimization simulated annealing algorithm Electrical capacitance tomography least squares support vector machines In this paper, we introduce a novel image reconstruction algorithm with Least Squares Support Vector Machines (LS-SVM) and Simulated Annealing Particle Swarm Optimization (APSO), named SAP. This algorithm introduces simulated annealing ideas into Particle Swarm Optimization (PSO), which adopts cooling process functions to replace the inertia weight function and constructs the time variant inertia weight function featured in annealing mechanism. Meanwhile, it employs the APSO procedure to search for the optimized resolution of Electrical Capacitance Tomography (ECT) for image reconstruction. In order to overcome the soft field characteristics of ECT sensitivity field, some image samples with typical flow patterns are chosen for training with LS-SVM. Under the training procedure, the capacitance error caused by the soft field characteristics is predicted, and then is used to construct the fitness function of the particle swarm optimization on basis of the capacitance error. Experimental results demonstrated that the proposed SAP algorithm has a quick convergence rate. Moreover, the proposed SAP outperforms the classic Landweber algorithm and Newton-Raphson algorithm on image reconstruction. 2015 artículo científico 1665-6423 https://www.redalyc.org/articulo.oa?id=47439895005 en http://www.redalyc.org/revista.oa?id=474 Journal of Applied Research and Technology application/pdf Universidad Nacional Autónoma de México Journal of Applied Research and Technology (México) Num.2 Vol.13