Prediction of bending force in the hot strip rolling process using artificial neural network and genetic algorithm (ANN-GA)
作者: Zhen-Hua WangDian-Yao GongXu LiGuang-Tao LiDian-Hua Zhang
作者单位: 1Northeastern University
刊名: The International Journal of Advanced Manufacturing Technology, 2017, Vol.93 (9-12), pp.3325-3338
来源数据库: Springer Nature Journal
DOI: 10.1007/s00170-017-0711-5
关键词: Hot strip rollingArtificial neural network (ANN)Genetic algorithm (GA)Bending force
原始语种摘要: An artificial neural network (ANN) optimized by genetic algorithm (GA) is an established prediction model of bending force in hot strip rolling. The data are collected from factory of steel manufacture. Entrance temperature and thickness, exit thickness, strip width, rolling force, rolling speed, roll shifting, target profile, and yield strength of strip are selected to be independent variables as network inputs. MATLAB software is utilized for establishing GA-ANN model and achieving the purpose of obtaining the bending force as results of setup model, as well as the GA method is used to optimize the initial weights and biases of the backpropagation neural network. Mean absolute error (MAE), mean absolute percentage error (MAPE), root mean squared error (RMSE), and correlation coefficient...
全文获取路径: Springer Nature  (合作)

  • ANN All Numeral Numbering
  • algorithm 算法
  • neural 神经系统的
  • force 
  • genetic 遗传的
  • rolling 
  • process 过程
  • bending 弯曲
  • network 网络
  • strip