Zhang Y(张宇); Xu JL(许敬亮); Yuan ZH(袁振宏); Zhuang XS(庄新姝); Lv PM(吕鹏梅)
Source Publicationchinesejournalofcatalysis
AbstractEnzymatic hydrolysis of cellulose was highly complex because of the unclear enzymatic mechanism and many factors that affect the heterogeneous system. Therefore, it is difficult to build a theoretical model to study cellulose hydrolysis by cellulase. Artificial neural network (ANN) was used to simulate and predict this enzymatic reaction and compared with the response surface model (RSM). The independent variables were cellulase amount X-1, substrate concentration X-2, and reaction time X-3, and the response variables were reducing sugar concentration Y-1 and transformation rate of the raw material Y-2. The experimental results showed that ANN was much more suitable for studying the kinetics of the enzymatic hydrolysis than RSM. During the simulation process, relative errors produced by the ANN model were apparently smaller than that by RSM except one and the central experimental points. During the prediction process, values produced by the ANN model were much closer to the experimental values than that produced by RSM. These showed that ANN is a persuasive tool that can be used for studying the kinetics of cellulose hydrolysis catalyzed by cellulase.
Document Type期刊论文
First Author AffilicationGuangZhou Institute of Energy Conversion,Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zhang Y,Xu JL,Yuan ZH,et al. kineticmodelstudyonenzymatichydrolysisofcelluloseusingartificialneuralnetworks[J]. chinesejournalofcatalysis,2009,30(4):355.
APA 张宇,许敬亮,袁振宏,庄新姝,&吕鹏梅.(2009).kineticmodelstudyonenzymatichydrolysisofcelluloseusingartificialneuralnetworks.chinesejournalofcatalysis,30(4),355.
MLA 张宇,et al."kineticmodelstudyonenzymatichydrolysisofcelluloseusingartificialneuralnetworks".chinesejournalofcatalysis 30.4(2009):355.
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