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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.","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. 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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>"},"keyword":["Gaussian process regression","design of experiments","static process models","industrial processes","stepwise experimental design"],"publication_status":"published","issue":"19","publication":"Mathematics","alternative_id":["1477"],"main_file_link":[{"open_access":"1","url":"https://www.mdpi.com/2227-7390/9/19/2479"}],"user_id":"220548","tmp":{"short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png"},"oa":"1","type":"journal_article","publication_identifier":{"eissn":["2227-7390"]},"volume":9,"date_created":"2023-11-14T10:52:17Z","title":"Incremental DoE and Modeling Methodology with Gaussian Process Regression: An Industrially Applicable Approach to Incorporate Expert Knowledge"}]