催化学报

催化学报 ›› 2009, Vol. 30 ›› Issue (4): 355-358.

• 研究论文 • 上一篇    下一篇

纤维素酶水解动力学的人工神经网络模型研究

张宇 1,2, 许敬亮 1, 袁振宏 1, 庄新姝 1, 吕鹏梅 1   

  1. 1 中国科学院广州能源研究所, 中国科学院可再生能源与天然气水合物重点实验室, 广东广州 510640; 2 中国科学院研究生院, 北京 100049
  • 收稿日期:2009-04-25 出版日期:2009-04-25 发布日期:2013-01-21

Kinetic Model Study on Enzymatic Hydrolysis of Cellulose Using Artificial Neural Networks

ZHANG Yu1, 2, XU Jingliang1, YUAN Zhenhong1,*, ZHUANG Xinshu1, LVPengmei1   

  1. 1Key Laboratory of Renewable Energy and Gas Hydrate, Guangzhou Institute of Energy Conversion, Chinese Academy of Sci-ences,Guangzhou 510640, Guangdong, China; 2Graduate University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2009-04-25 Online:2009-04-25 Published:2013-01-21

PDF

889

被引次数

20

摘要： Enzymatic hydrolysis of cellulose in a heterogeneous system is highly complex, rendering it difficult to build a theoretical model for confident prediction. Artificial neural network model is not conditioned by the need to assume a mechanistic dependency and can simulate and predict enzymatic hydrolysis of cellulose as a result of its advanced non-linear data analysis.

关键词: 酶催化动力学, 纤维素酶水解, 人工神经网络, 响应面模型, 异相催化

Abstract: Enzymatic hydrolysis of cellulose in a heterogeneous system is highly complex, rendering it difficult to build a theoretical model for confident prediction. Artificial neural network model is not conditioned by the need to assume a mechanistic dependency and can simulate and predict enzymatic hydrolysis of cellulose as a result of its advanced non-linear data analysis.

Key words: enzymatic kinetics, enzymatic hydrolysis of cellulose, artificial neural network, response surface model, heterogeneous catalysis