Shenyang, China
Shenyang, China

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Bai J.,Beihua University | Pu T.,Beihua University | Xing J.,Beihua University | Niu G.,Beihua University | And 2 more authors.
Proceedings of 2011 International Conference on Electronic and Mechanical Engineering and Information Technology, EMEIT 2011 | Year: 2011

Because there are many coterminous workshop sections in beer brewing process and the reaction mechanism is very complex, it is difficult to analyze the energy consumption. Aiming at the problem, the analysis method of energy consumption is proposed based on the production data. First, energy consumption of beer brewing process is analyzed using the data envelopment analysis (DEA). The relative efficient productive batches are obtained. Secondly, the less dimensional production data are obtained using the principal component analysis (PCA) which depresses the correlation among the variables. Finally, the energy consumption of brewing process is modeled using radial basis function neural network (RBFNN), and the energy consumption model with the minimum error is also built by adjusting the width of the radial basis function. The simulation result shows that the model can be used to analyze and predict the energy consumption of the beer brewing process effectively. © 2011 IEEE.

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