Abstract
Among the traditional image reconstruction algorithm for ERT (Electrical Resistance Tomography) system, the Landweber algorithm is the most commonly used iterative algorithm, with moderate computation and good reconstruction quality. However, because "soft field" error is usually ignored in reconstruction, there is still much room for improvement in the quality of reconstructed images. Aiming this problem, a combined algorithm is proposed. The Landweber reconstruction results were taken as the initial population position of the particle swarm optimization (PSO). Through the random forest regression model, the "soft field" error prior condition is obtained, and used in the construction of the PSO objective function to eliminate the influence of ignoring the "soft field" error. The simulation experiment results show that the proposed algorithm effectively improves the accuracy of the reconstructed image.
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