APPLICATION OF NEURAL NETWORK MODEL IN VITAMIN C FERMEMTATION PROCESS

Hua Qiang; Wang Shuqing（Institute of Industrial Process Control

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APPLICATION OF NEURAL NETWORK MODEL IN VITAMIN C FERMEMTATION PROCESS

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- APPLICATION OF NEURAL NETWORK MODEL IN VITAMIN C FERMEMTATION PROCESS
- CIESC Journal Issue 4, (1996)
- 作者机构：
  
  浙江大学工业控制技术研究所!杭州310027,浙江大学工业控制技术研究所,杭州,310027
- 作者简介：
- 基金信息：
- DOI：
  CLC： Q92
- Online First：25 August 1996，
  
  Published：25 August 1996
- 稿件说明：
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Hua Qiang, Wang Shuqing（Institute of Industrial Process Control. APPLICATION OF NEURAL NETWORK MODEL IN VITAMIN C FERMEMTATION PROCESS[J]. CIESC Journal, 1996, (4).
DOI：

Hua Qiang, Wang Shuqing（Institute of Industrial Process Control. APPLICATION OF NEURAL NETWORK MODEL IN VITAMIN C FERMEMTATION PROCESS[J]. CIESC Journal, 1996, (4). DOI：

摘要

传统的标准“黑箱”型人工神经网络已较为广泛地应用于生化过程中的状态预估等多个方面，然而结合过程先验知识或部分机理模型的混合神经网络建模方法能给出更令人满意的结果.本文将其应用于2-酮基-l-古龙酸（2-KLG）发酵过程的状态估计，并将其结果与传统神经网络模型进行了比较，混合模型明显优于单一神经网络方法.

Abstract

Conventional standard artificial neural network has been applied widely in state estimation of bioprocesses

but hybrid neural network

which combines the prior knowledge or partially known principles of the process

can give more satisfactory results.The hybrid model is used in state estimation of 2-keto-l-gulonic acid fermentation in this paper

and the results are compared with that of standard neural network.

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