Abstract
In this paper, the measurement of biochemical oxygen demand (BOD) in wastewater treatment process is analyzed and an intelligent integrated prediction method based on case-based reasoning (CBR) is proposed in order to overcome the difficulty. Due to the fact that there are many factors influence the accuracy of prediction model, the radial basis function, which is a neural network with 3 layers feedforward network, is employed to reduce the dimension of input values. Under this circumstance, the back propagation neural network combining with nearest neighbor retrieval strategy is adopted to match case. Then, the measurement of BOD in wastewater treatment process is analyzed. Finally, the validity of the improved CBR in sewage treatment is demonstrated by using numerical results.
- case-based reasoning (CBR)
- intelligent integrated prediction
- sewage treatment
- soft-sensing
- First received 15 March 2017.
- Accepted in revised form 27 June 2017.
- © 2017 The Authors
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY-NC-ND 4.0), which permits copying and redistribution for non-commercial purposes with no derivatives, provided the original work is properly cited (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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