Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (32): 240-243.DOI: 10.3778/j.issn.1002-8331.2009.32.074

• 工程与应用 • Previous Articles     Next Articles

Research on fermentation process modeling of improved Elman neural network

LIU Yao-meng,MA Yong-jun,YANG Mei-yan   

  1. School of Computer Science and Information Engineering,Tianjin University of Science & Technology,Tianjin 300222,China
  • Received:2009-06-03 Revised:2009-07-28 Online:2009-11-11 Published:2009-11-11
  • Contact: LIU Yao-meng

改进型Elman神经网络发酵过程建模研究

刘尧猛,马永军,杨美艳   

  1. 天津科技大学 计算机科学与信息工程学院,天津 300222
  • 通讯作者: 刘尧猛

Abstract: According to the characteristics of fermentation process and the dynamic modeling theory of modified Elman neural network,a new batch training algorithm for fermentation process modeling is proposed.The training and testing of fermentation process simulation experiments show that modified Elman neural network modeling algorithm has specialties that convergence speed is faster and generalization is better,compared with traditional BP modeling algorithm.Furthermore,the software based on the modeling algorithm can be embedded into fermentation process control system,realizes fermentation process online modeling and state parameter online estimating.

Key words: Elman, neural network, batch training, fermentation process, online modeling, online estimating

摘要: 依据发酵过程的机理和改进的Elman神经网络动态建模原理,提出了一个新的发酵过程建模分批训练算法。通过发酵过程仿真实验,与传统的BP建模算法比较,改进的Elman神经网络建模算法具有收敛速度快、泛化能力强等特点。此外,利用该算法编制的软件可以内嵌到发酵过程监控系统中,实现发酵过程在线建模与状态参量的在线预估。

关键词: Elman, 神经网络, 分批训练, 发酵过程, 在线建模, 在线预估

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