Chapter
Apr 26, 2012
Computationally Efficient Procedures for Uncertainty Assessment of Complex Environmental Models
Publication: World Environmental and Water Resources Congress 2008: Ahupua'A
Abstract
This paper describes some recent developments in uncertainty analysis algorithms. The description focuses on BOARS, a method that uses a mixture of optimization, Bayesian, and function approximation analyses. The BOARS publication shows that Markov Chain Monte Carlo (MCMC) analysis required more than 60 times as many simulations as did BOARS to get very similar results.
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Copyright
© 2008 American Society of Civil Engineers.
History
Published online: Apr 26, 2012
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ASCE Technical Topics:
- Algorithms
- Analysis (by type)
- Approximation methods
- Bayesian analysis
- Computer models
- Continuum mechanics
- Dynamics (solid mechanics)
- Engineering fundamentals
- Engineering mechanics
- Information management
- Materials characterization
- Materials engineering
- Mathematics
- Methodology (by type)
- Mixtures
- Models (by type)
- Motion (dynamics)
- Optimization models
- Publications
- Solid mechanics
- Statistical analysis (by type)
- Uncertainty principles
Authors
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School of Civil and Environmental Engineering, Cornell University, Ithaca, N.Y. 14853. E-mail: [email protected]
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Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.