CIESC Journal

• 化工学报 • 上一篇    下一篇

神经网络过程模型辨识

朱群雄,麻德贤   

  1. 北京化工大学计算机系,北京化工大学计算机系 北京 100029 ,北京 100029
  • 出版日期:1997-10-25 发布日期:1997-10-25

RECOGNITION OF NEURAL NETWORK PROCESS MODEL

Zhu Qunxiong and Ma Dexian(Department of Computer Science, Beijing University of Chemical Technology, Beijing 100029)   

  • Online:1997-10-25 Published:1997-10-25

摘要: 利用修正的反传神经网络(BP)算法分别对稳态过程和动态过程以及两个实际化工生产过程进行模型结构辨识,所确定的最佳神经网络结构经验证表明具有较好的收敛性和稳定性,模拟精度高、适用性强.

Abstract: A novel algorithm of neural network structure optimization is described in this paper. The capabilities of the algorithm are demonstrated by application in steady-state process, dynamic process and industrial process. The recognized results of neural network structure show that the optimal neural network can be widely used for modelling and simulation of chemical processes.

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