Flexible and Robust Implementations of Multivariate Adaptive Regression Splines Within a Wastewater Treatment Stochastic Dynamic Program

2005 ◽  
Vol 21 (7) ◽  
pp. 689-699 ◽  
Author(s):  
Julia C. C. Tsai ◽  
Victoria C. P. Chen
Keyword(s):  
Wastewater Treatment ◽  
Dynamic Program ◽  
Multivariate Adaptive Regression Splines ◽  
Stochastic Dynamic ◽  
Regression Splines ◽  
Adaptive Regression ◽  
Stochastic Dynamic Program ◽  
Adaptive Regression Splines

scholarly journals Application of Selected Methods of Black Box for Modelling the Settleability Process in Wastewater Treatment Plant

2017 ◽  
Vol 24 (1) ◽  
pp. 119-127
Author(s):  
Bartosz Szeląg ◽  
Alicja Gawdzik ◽  
Andrzej Gawdzik
Keyword(s):  
Wastewater Treatment ◽  
Activated Sludge ◽  
Random Forests ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Black Box ◽  
Multivariate Adaptive Regression Splines ◽  
Regression Splines ◽  
Adaptive Regression ◽  
Adaptive Regression Splines

Abstract The paper described how the results of measurements of inflow wastewater temperature in the chamber, a degree of external and internal recirculation in the biological-mechanical wastewater treatment plant (WWTP) in Cedzyna near Kielce, Poland, were used to make predictions of settleability of activated sludge. Three methods, namely: multivariate adaptive regression splines (MARS), random forests (RF) and modified random forests (RF + SOM) were employed to compute activated sludge settleability. The results of analysis indicate that modified random forests demonstrate the best predictive abilities.

Prediction of transportation energy demand: Multivariate Adaptive Regression Splines

Energy ◽  
2021 ◽  
Vol 224 ◽  
pp. 120090
Author(s):  
Mohammad Ali Sahraei ◽  
Hakan Duman ◽  
Muhammed Yasin Çodur ◽  
Ecevit Eyduran
Keyword(s):  
Energy Demand ◽  
Multivariate Adaptive Regression Splines ◽  
Regression Splines ◽  
Transportation Energy ◽  
Adaptive Regression ◽  
Adaptive Regression Splines
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