A Bayesian approach for continuous improvement of kinetic parameter estimates

Rätze, Karsten; McBride, Kevin; Sundmacher, Kai

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A Bayesian approach for continuous improvement of kinetic parameter estimates

Rätze, K., McBride, K., & Sundmacher, K. (2019). A Bayesian approach for continuous improvement of kinetic parameter estimates. Talk presented at 12th European Congress of Chemical Engineering – ECCE 12. Florence, Italy. 2019-09-15 - 2019-09-19.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0005-6596-0 Version Permalink: https://hdl.handle.net/21.11116/0000-0005-6597-F

Genre: Talk

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Creators:
Rätze, Karsten^{1, 2}, Author
McBride, Kevin³, Author
Sundmacher, Kai^{2, 3}, Author

Affiliations:
1International Max Planck Research School (IMPRS), Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738143
2Otto-von-Guericke-Universität Magdeburg, External Organizations, ou_1738156
3Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738151

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Language(s): eng - English

Dates: Created: 2019

Publication Status: Not specified

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Rev. Type: Peer

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Title: 12th European Congress of Chemical Engineering – ECCE 12

Place of Event: Florence, Italy

Start-/End Date: 2019-09-15 - 2019-09-19

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