Abstract：
:In monitoring and controlling wastewater treatment processes, on-line information of nutrient dynamics is very important. However, these variables are determined with a significant time delay. Although the final effluent quality can be analyzed after this delay, it is often too late to make proper adjustments. In this paper, a neural network approach, a software sensor, was proposed to overcome this problem. Software sensor refers to a modeling approach inferring hard-to-measure process variables from other on-line measurable process variables. A bench-scale sequentially-operated batch reactor (SBR) used for advanced wastewater treatment (BOD plus nutrient removal) was employed to develop the neural network model. In order to improve the network performance, the structure of neural network was arranged in such a way of reflecting the change of operational conditions within a cycle. Real-time estimation of PO3-(4), NO-3, and NH+4 concentrations was successfully carried out with the on-line information of the SBR system only.
journal_name
J Biotechnoljournal_title
Journal of biotechnologyauthors
Lee DS,Park JMdoi
10.1016/s0168-1656(99)00171-6subject
Has Abstractpub_date
1999-10-08 00:00:00pages
229-39issue
2-3eissn
0168-1656issn
1873-4863pii
S0168-1656(99)00171-6journal_volume
75pub_type
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