Research of Self-Learning of Plate Deformation Resistance Based on Genetic Algorithm

Abstract:

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The model parameters value of deformation resistance determines the prediction accuracy of rolling force model during the plate rolling. According to the influencing factors analysis of rolling force calculation error, the genetic algorithm was introduced into the self-learning method of deformation resistance, and searches the optimal value of deformation resistance on the basic of space exploration and optimization ability of genetic algorithm. The decision variable selection, the coding and decoding, the fitness evaluation and the terminal conditions process were implemented during development process of self-learning system. The results show that the optimization speed and accuracy can meet production requirement.

Info:

Periodical:

Advanced Materials Research (Volumes 154-155)

Edited by:

Zhengyi Jiang, Xianghua Liu and Jinglong Bu

Pages:

260-264

DOI:

10.4028/www.scientific.net/AMR.154-155.260

Citation:

C. Y. He et al., "Research of Self-Learning of Plate Deformation Resistance Based on Genetic Algorithm", Advanced Materials Research, Vols. 154-155, pp. 260-264, 2011

Online since:

October 2010

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Price:

$35.00

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