[{"intvolume":"         9","publication_status":"published","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)"},"publisher":"MDPI AG","_id":"3717","title":"Incremental DoE and Modeling Methodology with Gaussian Process Regression: An Industrially Applicable Approach to Incorporate Expert Knowledge","year":"2021","language":[{"iso":"eng"}],"keyword":["Gaussian process regression","design of experiments","static process models","industrial processes","stepwise experimental design"],"status":"public","alternative_id":["1477"],"author":[{"first_name":"Tim","id":"220691","full_name":"Voigt, Tim","last_name":"Voigt"},{"last_name":"Kohlhase","orcid":"0009-0002-9374-0720","full_name":"Kohlhase, Martin","id":"226669","orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0002-9374-0720/work/222606627","first_name":"Martin"},{"first_name":"Oliver","last_name":"Nelles","full_name":"Nelles, Oliver"}],"date_updated":"2026-08-03T15:24:44Z","article_number":"2479","oa":"1","date_created":"2023-11-14T10:52:17Z","publication":"Mathematics","user_id":"256529","main_file_link":[{"open_access":"1","url":"https://www.mdpi.com/2227-7390/9/19/2479"}],"volume":9,"type":"journal_article","doi":"10.3390/math9192479","publication_identifier":{"eissn":["2227-7390"]},"citation":{"ama":"Voigt T, Kohlhase M, Nelles O. 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>.","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","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} }","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>.","short":"T. Voigt, M. Kohlhase, O. Nelles, Mathematics 9 (2021).","apa":"Voigt, T., Kohlhase, M., &#38; Nelles, O. (2021). Incremental DoE and Modeling Methodology with Gaussian Process Regression: An Industrially Applicable Approach to Incorporate Expert Knowledge. <i>Mathematics</i>, <i>9</i>(19). <a href=\"https://doi.org/10.3390/math9192479\">https://doi.org/10.3390/math9192479</a>","ieee":"T. Voigt, M. Kohlhase, and O. Nelles, “Incremental DoE and Modeling Methodology with Gaussian Process Regression: An Industrially Applicable Approach to Incorporate Expert Knowledge,” <i>Mathematics</i>, vol. 9, no. 19, 2021."},"issue":"19"}]