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Intelligent Engineering Systems through Artificial Neural Networks
ISBN:
9780791802953
No. of Pages:
636
Publisher:
ASME Press
Publication date:
2009
eBook Chapter
1 A Neural Network Approach to Modeling System Integration Sensitivity for Architectural Assessment
By
Jason P. Dauby
Eng Management & Systems Eng Missouri S&T Rolla, MO 65409 ; jpd338@mst.edu
,
Jason P. Dauby
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Cihan H. Dagli
Eng Management & Systems Eng Missouri S&T Rolla, MO 65409 ; dagli@mst.edu
Cihan H. Dagli
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Page Count:
10
-
Published:2009
Citation
Dauby, JP, & Dagli, CH. "A Neural Network Approach to Modeling System Integration Sensitivity for Architectural Assessment." Intelligent Engineering Systems through Artificial Neural Networks. Ed. Dagli, CH, Bryden, KM, Corns, SM, Gen, M, Tumer, K, & Süer, G. ASME Press, 2009.
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Performance sensitivity resulting from system integration is a subject commonly left untreated in the system architecting and early systems engineering phases. Ambiguity in the physical architecture often leads system designers to ignore this emergent behavior even though it can greatly alter the intended system performance. New methods of probing integration sensitivity are being researched. These methods employ computationally intensive methods to produce a set of performance predictions based on design variable iterations. There are two shortcomings with this approach. First, the computational intensity of the process limits the capacity to explore a large number of iterations. Second, a concise and...
Abstract
Introduction
The Integration Sensitivity function
Neural Network Architecture and Results
Future Work
Conclusions
References
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