Artificial Neural Network Model Prediction of Glucose by Enzymatic Hydrolysis of Rice Straw
The aim of this paper is to predict the production of glucose using artificial neural network (ANN) and validation with the experimental values for hydrolysis process. The ANN consists of three layers which are input, hidden and output layer. The input layer is the manipulated variables in the ca...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor's University
2014
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| Subjects: | |
| Online Access: | http://eprints.usm.my/42732/1/JES_Vol._10_2014-Art._9-%2885-94%29.pdf http://eprints.usm.my/42732/ http://web.usm.my/jes/10_2014/JES%20Vol.%2010%202014-Art.%209-(85-94).pdf |
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| Summary: | The aim of this paper is to predict the production of glucose using artificial
neural network (ANN) and validation with the experimental values for hydrolysis process.
The ANN consists of three layers which are input, hidden and output layer. The input
layer is the manipulated variables in the case study, which are the activity of added
cellulose, substrate initial concentration and hydrolysis time on the production of glucose
while the output layer is the concentration of glucose. The performances of the model
were evaluated using the coefficient of determination, mean square error and average
relative deviation. The predictive model shows a good result as the coefficient of
determination, 0.8361 was obtained with a small value of mean square error, 0.1947 and
5.644 as the average relative deviation. It clearly shows that ANN gives a good
prediction on the enzymatic hydrolysis for the production of glucose |
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