Application of Improved Back-Propagation Neural Network and Genetic Algorithm to the Preparation Processing of the Mg,Al-Hydrotalcite/Polymer Nanocomposite

Abstract:

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The three-layer structure back-propagation network model based on the non-linear relationship between the break percentage elongation of the Mg,Al-hydrotalcite/PE nanocomposites and the technological factors was established. And in order to accelerate the converging rate and avoid the local minimum, dimensionality reduction and pre-whitening methods were used. Moreover, the optimum technological process parameters were optimized with genetic algorithm. And the results show that using both the back propagation neural networks and genetic algorithm is very efficient for the prediction of the break percentage elongation of the Mg,Al-hydrotalcite/PE nanocomposite.

Info:

Periodical:

Key Engineering Materials (Volumes 368-372)

Edited by:

Wei Pan and Jianghong Gong

Pages:

1680-1682

DOI:

10.4028/www.scientific.net/KEM.368-372.1680

Citation:

Q. Luo and Q. L. Ren, "Application of Improved Back-Propagation Neural Network and Genetic Algorithm to the Preparation Processing of the Mg,Al-Hydrotalcite/Polymer Nanocomposite", Key Engineering Materials, Vols. 368-372, pp. 1680-1682, 2008

Online since:

February 2008

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Price:

$35.00

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