Title :
On the role of machine learning algorithms in developing MEMS components
Author :
Asmar, Daniel ; Moussa, Medhat ; Zelek, John
Author_Institution :
Sch. of Eng., Univ. of Guelph, Canada
Abstract :
This paper provides a review of several significant applications of machine learning tools in the development of MEMS components and devices. Four topics are covered, two represent traditional applications of artificial neural networks, drag reduction and reliability forecasting, and two are non-traditional applications, namely model reduction and MEMS based neurocomputing.
Keywords :
Galerkin method; computer network reliability; drag reduction; flow control; learning (artificial intelligence); microactuators; micromechanical devices; micromechanical resonators; neural nets; pattern recognition; reduced order systems; shear turbulence; MEMS based neurocomputing; MEMS components; MEMS devices; artificial neural networks; drag reduction; machine learning algorithms; model reduction; nontraditional applications; reliability forecasting; Artificial neural networks; Machine learning algorithms; Microactuators; Microelectromechanical devices; Micromechanical devices; Neural networks; Stress control; Stress measurement; Thermal sensors; Thermal stresses;
Conference_Titel :
MEMS, NANO and Smart Systems, 2003. Proceedings. International Conference on
Print_ISBN :
0-7695-1947-4
DOI :
10.1109/ICMENS.2003.1221975
