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Incremental DoE and Modeling Methodology with Gaussian Process Regression: An Industrially Applicable Approach to Incorporate Expert Knowledge. <i>Mathematics</i>. 2021;9(19). doi:<a href=\"https://doi.org/10.3390/math9192479\">10.3390/math9192479</a>","chicago":"Voigt, Tim, Martin Kohlhase, and Oliver Nelles. “Incremental DoE and Modeling Methodology with Gaussian Process Regression: An Industrially Applicable Approach to Incorporate Expert Knowledge.” <i>Mathematics</i> 9, no. 19 (2021). <a href=\"https://doi.org/10.3390/math9192479\">https://doi.org/10.3390/math9192479</a>.","short":"T. Voigt, M. Kohlhase, O. Nelles, Mathematics 9 (2021).","mla":"Voigt, Tim, et al. “Incremental DoE and Modeling Methodology with Gaussian Process Regression: An Industrially Applicable Approach to Incorporate Expert Knowledge.” <i>Mathematics</i>, vol. 9, no. 19, 2479, MDPI AG, 2021, doi:<a href=\"https://doi.org/10.3390/math9192479\">10.3390/math9192479</a>.","bibtex":"@article{Voigt_Kohlhase_Nelles_2021, title={Incremental DoE and Modeling Methodology with Gaussian Process Regression: An Industrially Applicable Approach to Incorporate Expert Knowledge}, volume={9}, DOI={<a href=\"https://doi.org/10.3390/math9192479\">10.3390/math9192479</a>}, number={192479}, journal={Mathematics}, publisher={MDPI AG}, author={Voigt, Tim and Kohlhase, Martin and Nelles, Oliver}, year={2021} }","alphadin":"<span style=\"font-variant:small-caps;\">Voigt, Tim</span> ; <span style=\"font-variant:small-caps;\">Kohlhase, Martin</span> ; <span style=\"font-variant:small-caps;\">Nelles, Oliver</span>: Incremental DoE and Modeling Methodology with Gaussian Process Regression: An Industrially Applicable Approach to Incorporate Expert Knowledge. In: <i>Mathematics</i> Bd. 9, MDPI AG (2021), Nr. 19"},"issue":"19","doi":"10.3390/math9192479","publication_identifier":{"eissn":["2227-7390"]},"_id":"3717","year":"2021","publisher":"MDPI AG","title":"Incremental DoE and Modeling Methodology with Gaussian Process Regression: An Industrially Applicable Approach to Incorporate Expert Knowledge","intvolume":"         9","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"publication_status":"published","keyword":["Gaussian process regression","design of experiments","static process models","industrial processes","stepwise experimental design"],"status":"public","language":[{"iso":"eng"}]}]