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Z. Zeng & J. Wang (Eds.): Adv. in Neural Network Research & Appli., LNEE 67, pp. 211218. springerlink.com Springer-Verlag Berlin Heidelberg 2010
 

Summary: Z. Zeng & J. Wang (Eds.): Adv. in Neural Network Research & Appli., LNEE 67, pp. 211218.
springerlink.com Springer-Verlag Berlin Heidelberg 2010
Interactive Hybrid Evolutionary Computation for MEMS
Design Synthesis
Ying Zhang1
and Alice M. Agogino2
1
School of Electrical and Computer Engineering, Georgia Institute of Technology, GA, USA
yzhang@gatech.edu
2
Department of Mechanical Engineering, University of California at Berkeley, CA, USA
agogino@berkeley.edu
Abstract. An interactive hybrid evolutionary computation (IHC) process for
MEMS design synthesis is described, which uses both human expertise and
local performance improvement to augment the performance of an evolutionary
process. The human expertise identifies good design patterns, and local
optimization fine-tunes these designs so that they reach their potential at early
stages of the evolutionary process. At the same time, the feedback on local
optimal designs confirms and refines the human assessment. The advantages of
the IHC process are demonstrated with micromachined resonator test cases.

  

Source: Agogino, Alice M. - Department of Mechanical Engineering, University of California at Berkeley

 

Collections: Engineering