Predicting biogas production is important for energy
management in wastewater treatment plants (WWTPs). Biogas production quantity
depends on its production system variables, such as, influent flow rate,
process temperature, alkalinity, volatile fatty acid, sludge retention time,
total suspended solid, etc. WWTPs keep the records of wastewater treatment process
values with supervisory control and data acquisition (SCADA) system on a
regular basis. The relationship between the biogas production and its
production system variables, which are measured continuously with SCADA system,
can be identified with classification and regression tree (CART) algorithm by
using the existing data. In this paper, CART approach is presented for the
prediction of biogas production at WWTPs. Standard CART algorithm is used to
select split predictor. Curvature and interaction tests are also applied in the
model to search for reducing split predictor selection bias and improving the
detection of important interactions among each predictor and response and among
each pair of predictors and response in turn.
Prediction Classification and regression tree Biogas production Wastewater treatment plant
Birincil Dil | İngilizce |
---|---|
Konular | Mühendislik |
Bölüm | Makaleler |
Yazarlar | |
Yayımlanma Tarihi | 4 Aralık 2018 |
Yayımlandığı Sayı | Yıl 2018Sayı: 4 |