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Inductive learning for engineering design optimization
Published online by Cambridge University Press: 27 February 2009
Extract
We are working on using machine learning to make the numerical optimization of complex engineering designs faster and more reliable. We envision a system that learns from previous design sessions knowledge that enables it to assist the engineer in setting up and carrying out a new design optimization. We have performed initial experiments for two aspects of setting up an optimization: selecting a prototype to serve as a starting point for the optimization and selecting a reformulation of the search space. Both choices can dramatically affect the speed and the reliability of design optimization.
- Type
- Research Abstracts
- Information
- AI EDAM , Volume 10 , Issue 2: Special Issue: Machine learning in design , April 1996 , pp. 179 - 180
- Copyright
- Copyright © Cambridge University Press 1996