Multi-Dimensional Global Approximation Method Based Improved MARS

2013 ◽  
Vol 655-657 ◽  
pp. 1005-1008
Author(s):  
Xiao Ling Luo ◽  
He Ru Xue

Global approximation for a complex “black-box” model (like a simulation model) with large domain or multi-dimensions can be applied in many fields such as parameter experiment, sensibility analysis, real-time simulation, and design/control optimization. For multi-dimensional global approximation, MARS (multi-variant adaptive regression splines) has unquestionable predominance over other common-used metamodel techniques. However, MARS has its own inevitable drawbacks which limit the range of its applications. This paper proposes a multi-dimensional global approximation method based improved MARS .Some tests and applications are given to prove the performance of the method.

2017 ◽  
Vol 24 (1) ◽  
pp. 119-127
Author(s):  
Bartosz Szeląg ◽  
Alicja Gawdzik ◽  
Andrzej Gawdzik

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.


Energy ◽  
2021 ◽  
Vol 224 ◽  
pp. 120090
Author(s):  
Mohammad Ali Sahraei ◽  
Hakan Duman ◽  
Muhammed Yasin Çodur ◽  
Ecevit Eyduran

Sign in / Sign up

Export Citation Format

Share Document