Applications of BPNN in Analyzing LHM Elemental Basic Structure

Abstract:

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Based on the back propagation multi-layer forward feed neural network, the neural network model is built for the dielectric sensitive structural parameters between the equivalent permittivity and the equivalent permeability, which is used to analyze the basic left-hand materials(LHMS) structural. The experimental results show that the analysis time is 145.535648 seconds and the training mean error is 0.000113426 while adopting the scaled conjugate gradient method. The results are coincident with these ones by the full wave method, satisfying the engineering demand, reducing the faults caused by thickness resonance in the traditional numerical analysis method, realizing the coexistence between the high analysis precision and the high efficiency of the left-hand materials.

Info:

Periodical:

Edited by:

Kai Cheng, Yongxian Liu, Xipeng Xu and Hualong Xie

Pages:

466-470

DOI:

10.4028/www.scientific.net/AMM.16-19.466

Citation:

J. Yu et al., "Applications of BPNN in Analyzing LHM Elemental Basic Structure", Applied Mechanics and Materials, Vols. 16-19, pp. 466-470, 2009

Online since:

October 2009

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Price:

$35.00

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