Research of Self-Learning of Plate Deformation Resistance Based on Genetic Algorithm
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.
Zhengyi Jiang, Xianghua Liu and Jinglong Bu
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