A random forest model for inflow prediction at wastewater treatment plants

Influent flow of wastewater treatment plants (WWTPs) is a crucial variable for plant operation and management. In this study, a random forest (RF) model was applied for daily wastewater inflow prediction, and a new probabilistic prediction approach was, for the first time, applied for quantifying th...

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Veröffentlicht in:	Stochastic environmental research and risk assessment 2019-10, Vol.33 (10), p.1781-1792
Hauptverfasser:	Zhou, Pengxiao, Li, Zhong, Snowling, Spencer, Baetz, Brian W., Na, Dain, Boyd, Gavin
Format:	Artikel
Sprache:	eng
Schlagworte:	Aquatic Pollution Autoregressive models Chemistry and Earth Sciences Computational Intelligence Computer Science Decision trees Domestic water Earth and Environmental Science Earth Sciences Environment Inflow Math. Appl. in Environmental Science Multilayer perceptrons Neural networks Optimization Original Paper Performance prediction Physics Probability Theory and Stochastic Processes Regression analysis Regression models Statistical analysis Statistics for Engineering Training Waste Water Technology Wastewater treatment Wastewater treatment plants Water consumption Water Management Water Pollution Control Water treatment Water use Weather
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