Engineering Design via Surrogate Modelling: A Practical Guide
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The paper generally requires that all species in the final mechanism be studied with full-accuracy DFT for verification, so the accuracy of the surrogate models does not affect the energetics of the final pathway.
“However, we generally require that all species in the final mechanism be studied with full-accuracy DFT for verification, so the accuracy of the surrogate models does not affect the energetics of the final pathway, inspired by surrogate-model approaches in the systems engineering literature18.”
From To address surface reaction network complexity using scaling relations machine learning and DFT calculations (2017) · cites this paper as [18]
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Ulissi, Z. W., Medford, A. J., Bligaard, T., & Nørskov, J. K. (2017) · Nature Communications · doi:10.1038/ncomms14621 · Cited by 614 · see citing works
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- Authors
- Forrester, A. I. J., Sóbester, A., & Keane, A. J.
- Venue
- Wiley eBooks
- Publisher
- Wiley
- Published
- 2008-07-18
- OpenAlex
- W2478899349
- Cited by
- 2,309
- References
- 37
- Citations by year
- 2026: 290 · 2025: 180 · 2024: 177 · 2023: 139 · 2022: 164 · 2021: 198 · 2020: 172 · 2019: 170 · 2018: 162 · 2017: 126 · 2016: 115 · 2015: 106 · 2014: 82 · 2013: 66 · 2012: 81
- FWCI
- 8.37
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Wiley eBooks (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Advanced Multi-Objective Optimization Algorithms
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Probabilistic and Robust Engineering Design
- Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
- Keywords
- surrogate models, engineering design, design optimization, computational complexity reduction
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