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For the problem of monitoring biochemical oxygen demand (BOD) concentration in wastewater treatment process, a case-based reasoning (CBR) prediction model based on support vector regression machine (SVR) is established in this paper. This model is composed of a case retrieval, a case reuse, a SVR revision and a case retention. The SVR revision model is obtained using the SVR training to revise the BOD concentration suggested from the traditional CBR model. The experiment results indicate that the fitting error of this model is lower compared with the support vector machine (SVM), the BP neural network, RBF neural network and the traditional CBR method. The application of SVR can effectively improve the regression performance and the learning ability for a traditional CBR model. © 2017, East China University of Science and Technology. All right reserved.
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Journal of East China University of Science and Technology
ISSN: 1006-3080
Year: 2017
Issue: 2
Volume: 43
Page: 227-233
Cited Count:
SCOPUS Cited Count: 1
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
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30 Days PV: 0