Abstract
Today’s engineering systems are sophisticated in design and powerful in function. Examples of such systems include airplanes, space shuttles, telecommunication networks, robots, and manufacturing facilities. Critical measures of performance of these systems include reliability, cost, and weight. Optimal system design aims to optimize such performance measures.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Zuo, M.J., Tian, Z., Huang, HZ. (2007). Neural Networks for Reliability-Based Optimal Design. In: Levitin, G. (eds) Computational Intelligence in Reliability Engineering. Studies in Computational Intelligence, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37372-8_7
Download citation
DOI: https://doi.org/10.1007/978-3-540-37372-8_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37371-1
Online ISBN: 978-3-540-37372-8
eBook Packages: EngineeringEngineering (R0)