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An Efficient Approach to Automate the Manual Trial and Error Calibration of Activated Sludge Models by Gürkan Sin; Dirk J.W. De Pauw; Stefan Weijers; Peter A. Vanrolleghem is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.
What is An Efficient Approach to Automate the Manual Trial and Error Calibration of Activated Sludge Models about?
## Abstract An efficient approach is introduced to help automate the rather tedious manual trial and error way of model calibration currently used in activated sludge modeling practice. To this end, we have evaluated a Monte Carlo based calibration approach consisting of four steps: (i) parameter subset selection, (ii) defining parameter space, (iii) parameter sampling for Monte Carlo simulations and (iv) selecting the best Monte Carlo simulation thereby providing the calibrated parameter values. The approach was evaluated on a formerly calibrated full‐scale ASM2d model for a domestic plant (located in The Netherlands), using in total 3 months of dynamic oxygen, ammonia and nitrate sensor data. The Monte Carlo calibrated model was validated successfully using ammonia, oxygen and nitrate data collected at high measurement frequency. Statistical analysis of the residuals using mean absolute error (MAE), root mean square error (RMSE) and Janus coefficient showed that the calibrated model was able to provide statistically accurate and valid predictions for ammonium, oxygen and nitrate. This shows that this pragmatic approach can perform the task of model calibration and therefore be us
Who reads An Efficient Approach to Automate the Manual Trial and Error Calibration of Activated Sludge Models?
It is typically read by researchers, students, and practitioners in Biochemistry, Genetics and Molecular Biology.
- Author
- Gürkan Sin; Dirk J.W. De Pauw; Stefan Weijers; Peter A. Vanrolleghem
- Publisher
- John Wiley and Sons; Wiley (John Wiley & Sons); Wiley - V C H Verlag GmbbH & Co.; Wiley (ISSN 0006-3592)
- Published
- 2007
- Language
- EN
- Field
- Biochemistry, Genetics and Molecular Biology (Life Sciences)