Model-based design of experiments based on local model networks for nonlinear processes with low noise levels

2011 ◽  
Author(s):  
Benjamin Hartmann ◽  
Tobias Ebert ◽  
Oliver Nelles
Keyword(s):  
Design Of Experiments ◽  
Low Noise ◽  
Local Model ◽  
Nonlinear Processes ◽  
Noise Levels ◽  
Model Based ◽  
Local Model Networks ◽  
Model Networks

Fighting the curse of dimensionality with local model networks

2019 ◽  
Vol 67 (10) ◽  
pp. 889-890
Author(s):  
Julian Belz
Keyword(s):  
Design Of Experiments ◽  
Curse Of Dimensionality ◽  
Local Model ◽  
Input Selection ◽  
Local Model Networks ◽  
Model Networks

Abstract This thesis is settled in the field of data-based modeling (identification) and specifically focuses on the weakening of the effects of the curse of dimensionality with local model networks (LMNs). The methods for fighting the curse of dimensionality originate from the fields of input selection and design of experiments (DoE).

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