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spack.io : dakota
The Dakota toolkit provides a flexible, extensible interface between analysis codes and iterative systems analysis methods. Dakota contains algorithms for: - optimization with gradient and non gradient-based methods; - uncertainty quantification with sampling, reliability, stochastic - expansion, and epistemic methods; - parameter estimation with nonlinear least squares methods; - sensitivity/variance analysis with design of experiments and - parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as hybrid optimization, surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty.
Registry
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Source
- JSON
purl: pkg:spack/dakota
License: Other
Latest release: about 2 years ago
First release: about 2 years ago
Last synced: 9 days ago