Optimizing the Quality Assessment of Digital Twins: A Machine Learning Exploration of Product Characteristics and Process Complexity

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Keywords	Digital Twins, Machine Learning, Quality Assessment, Automation, Random Forest, Gradient Boosting, XGBoost
Thesis Advisor	Kusterer, David Jakob, Szymanowski, Maciej
Persistent URL	hdl.handle.net/2105/71948
Series	Business Analytics & Management
Organisation	Rotterdam School of Management
Citation APA Style AAA Style APA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Jacobs, Max. (2024, July 2). Optimizing the Quality Assessment of Digital Twins: A Machine Learning Exploration of Product Characteristics and Process Complexity. Business Analytics & Management. Retrieved from http://hdl.handle.net/2105/71948

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