Multi-level simulation and numerical optimization of complex engineering designs
Author:
Affiliation:
1. Rutgers Univ., New Brunswick, NJ
Publisher
American Institute of Aeronautics and Astronautics
Link
http://arc.aiaa.org/doi/pdf/10.2514/6.1996-4021
Reference11 articles.
1. TECHNIQUES FOR INTEGRATING QUALITATIVE REASONING AND SYMBOLIC COMPUTATION IN ENGINEERING OPTIMIZATION
2. The application of artificial intelligence technology to aeronautical system design
3. Concepts for a future aircraft design environment
4. G. Cerbone. Machine learning in engineering: Techniques to speed up numerical optimization. Technical Report 92-30-09, Oregon State University Department of Computer Science, 1992. Ph.D. Thesis.
5. T. Ellman and M. Schwabacher. Abstraction and decomposition in hillclimbing design optimization. Technical Report CAP-TR-14, Department of Computer Science, Rutgers University, January 1993.
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