Journal
APPLIED SOFT COMPUTING
Volume 27, Issue -, Pages 1-10Publisher
ELSEVIER
DOI: 10.1016/j.asoc.2014.10.034
Keywords
Anoxic/oxic process; Neural fuzzy system; Genetic algorithm; Online monitoring
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Funding
- National Natural Science Foundation of China [51208206, 51210013]
- Guangdong Provincial Department of Science [2012A032300015]
- High-level Personnel Foundation of Guangdong Higher Education Institutions
- Pearl River Nova Program of Guangzhou
- State key laboratory of Pulp and Paper Engineering in China [201213]
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In this paper, a software sensor based on a genetic algorithm-based neural fuzzy system (GA-NFS) was proposed for real-time estimation of nutrient concentrations in a biological wastewater treatment process. In order to improve the network performance, self-adapted fuzzy c-means clustering algorithm and genetic algorithm were employed to extract and optimize the structure of the network. The GA-NFS was applied to a biological wastewater treatment process for nutrient removal. The simulative results indicate that the learning and generalization ability of the model performed well and also worked well for normal batch i.e., two data points. Real-time estimation of COD, NO3- and PO43- concentration based on GA-NFS functioned effectively with the simple on-line information on the anoxic/oxic system. (C) 2014 Elsevier B.V. All rights reserved.
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