Abstract
In this study some black-box models are employed to model various indicators of the wastewater quality (characterized by biochemical oxygen demand, chemical oxygen demand, the content of total and ammoniacal nitrogen, suspended solids and total phosphorus) at the inflow to a sewage treatment plant using as the predictors the sewage inflow and temperature as well as the indicators measured in the previous time steps. Considering all tested methods one can see that in most cases the best predictions have been obtained by the method of multivariate adaptive regression splines. Moreover the models based only on inflow and temperature inputs have got a noticeably lower errors than those once conditioned by indicators.
| Original language | English |
|---|---|
| Title of host publication | 31st Annual European Simulation and Modelling Conference 2017, ESM 2017 |
| Editors | Paulo J.S. Goncalves |
| Publisher | EUROSIS |
| Pages | 301-307 |
| Number of pages | 7 |
| ISBN (Electronic) | 9789492859006 |
| Publication status | Published - 2017 |
| Event | 31st Annual European Simulation and Modelling Conference, ESM 2017 - Lisbon, Portugal Duration: 25 Oct 2017 → 27 Oct 2017 |
Publication series
| Name | 31st Annual European Simulation and Modelling Conference 2017, ESM 2017 |
|---|
Conference
| Conference | 31st Annual European Simulation and Modelling Conference, ESM 2017 |
|---|---|
| Country/Territory | Portugal |
| City | Lisbon |
| Period | 25/10/17 → 27/10/17 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 6 Clean Water and Sanitation
Keywords
- Black-box
- Boosted tree
- MARS
- Support vector machines
- Wastewater modelling
ASJC Scopus subject areas
- Modeling and Simulation
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