Using a neural network as a function evaluator during GA search for reliability optimization

David Coit, Alice E. Smith

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

This paper demonstrates the use of a neural network as a reliability estimator for calculation of the objective function value during genetic algorithm (GA) search. The GA searches for the lowest cost system design by selecting the appropriate components and levels of redundancy. Using a neural network approximation for system reliability is computationally efficient for optimization problems where calculation of the objective function is impractical.

Original languageEnglish (US)
Pages369-374
Number of pages6
StatePublished - Dec 1 1995
Externally publishedYes
EventProceedings of the 1995 Artificial Neural Networks in Engineering, ANNIE'95 - St.Louis, MO, USA
Duration: Nov 12 1995Nov 15 1995

Other

OtherProceedings of the 1995 Artificial Neural Networks in Engineering, ANNIE'95
CitySt.Louis, MO, USA
Period11/12/9511/15/95

All Science Journal Classification (ASJC) codes

  • Software

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