Nominal elastic modulus assessment in 3D-printed components under varying printing parameters using Bayesian methods and random forest surrogate modeling.

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Bibliographic Details
Title: Nominal elastic modulus assessment in 3D-printed components under varying printing parameters using Bayesian methods and random forest surrogate modeling.
Authors: Zhang J; College of Art Design, The College of Post and Telecommunication of WIT, Wuhan, Hubei, China., Lu L; Wuhan Huaxia University of Technology, Wuhan, China., Feng P; Wuhan Police Vocational College, Wuhan, China., Zhu T; College of Art Design, The College of Post and Telecommunication of WIT, Wuhan, Hubei, China.
Source: PloS one [PLoS One] 2025 Dec 05; Vol. 20 (12), pp. e0338204. Date of Electronic Publication: 2025 Dec 05 (Print Publication: 2025).
Publication Type: Journal Article
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:1932-6203
DOI:10.1371/journal.pone.0338204