Uporaba odločitvenih dreves pri modeliranju čistilne naprave za odpadno vodo - Atanasova, Nataša (Acta hydrotechnica, 2002)
Wastewater treatment plants (WWTP) are dynamic and complex systems, the management of which can be improved by different approaches to modelling and predicting their operation. Machine learning tools (decision trees) were used to build useful prediction models for wastewater treatment plant operation. The data base used for building the models is composed of measured quantitative as well as qualitative data on the WWTP. We were also provided with a microbiological analysis. The data are presented as a one-day situationof the plant operation. So far, classification of the data was made using the Linneo+ methodology. We extended the knowledge gained by classification by analyzing the classified data and constructing useful modelsthat predict WWTP operation from inflow data. The WEKA program package, which includes most of the popular machine learning algorithms, was used for constructing the models.
Keywords: čistilne naprave; decision trees; machine learning; modeliranje; modelling; odločitvena drevesa; odpadne vode; strojno učenje; wastewater; wastewater treatment plant