Correction of Ghost in Reduced ODF with Particle Swarm Optimization Algorithm

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The particle swarm optimization (PSO) algorithm is introduced into ghost correction, which is also compared with the NMS algorithm. With linear regression correlation factor as evaluation parameter, it is found that both algorithms have the same quality for model ODF, but when it comes to complicated textures, the PSO algorithm shows high ODF fitting quality. It is also demonstrates that the ghost peaks in the reduced ODF can be excluded out in the true ODF from PSO components with both even and odd terms in the series expansion method.

Info:

Periodical:

Materials Science Forum (Volumes 546-549)

Edited by:

Yafang Han et al.

Pages:

1009-1014

Citation:

J. G. Tang et al., "Correction of Ghost in Reduced ODF with Particle Swarm Optimization Algorithm", Materials Science Forum, Vols. 546-549, pp. 1009-1014, 2007

Online since:

May 2007

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$38.00

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