Paper Title:

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

Periodical Advanced Materials Research (Volumes 154 - 155)
Main Theme Materials Processing Technologies
Edited by Zhengyi Jiang, Xianghua Liu and Jinglong Bu
Pages 260-264
DOI 10.4028/www.scientific.net/AMR.154-155.260
Citation Chun Yu He et al., 2010, Advanced Materials Research, 154-155, 260
Online since October, 2010
Authors Chun Yu He, Zhi Jie Jiao, Di Wu
Keywords Deformation Resistance, Genetic Algorithm (GA), Plate, Self-Learning
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Abstract

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.