A multi-objective Gaussian process approach for optimization and prediction of carbonization process in carbon fiber production under uncertainty Ramezankhani, M, Crawford, B, Khayyam, H, Naebe, Minoo, Seethaler, R and Milani, AS 2019, A multi-objective Gaussian process approach for optimization and prediction of carbonization process in carbon fiber production under uncertainty, Advanced composites and hybrid materials, vol. 2, no. 3, pp. 444-455, doi: 10.1007/s42114-019-00107-6. Title A multi-objective Gaussian process approach for optimization and prediction of carbonization process in carbon fiber production under uncertainty Author(s) Ramezankhani, M Crawford, B Khayyam, H Naebe, Minoo orcid.org/0000-0002-0607-6327 Seethaler, R Milani, AS Journal name Advanced composites and hybrid materials Volume number 2 Issue number 3 Start page 444 End page 455 Total pages 12 Publisher Springer Place of publication Berlin, Germany Publication date 2019 ISSN 2522-0128 2522-0136 Keyword(s) Science & Technology Technology Nanoscience & Nanotechnology Materials Science, Composites Science & Technology - Other Topics Materials Science Carbon fiber Gaussian process Carbonization Optimization Adaptive weighted sum method Machine learning WEIGHTED-SUM METHOD PAN FIBERS MECHANICAL-PROPERTIES PYROLYSIS HETEROSCEDASTICITY OPTIMALITY SQUARES MODELS Language eng DOI 10.1007/s42114-019-00107-6 Indigenous content off HERDC Research category C1.1 Refereed article in a scholarly journal Persistent URL http://hdl.handle.net/10536/DRO/DU:30146842 Document type: Journal Article Collections: Institute for Frontier Materials GTP Research Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Tue, 12 Jan 2021, 14:33:43 EST Wed, 13 Jan 2021, 04:06:09 EST Fri, 29 Jan 2021, 05:05:30 EST Fri, 29 Jan 2021, 13:07:54 EST Fri, 29 Jan 2021, 13:08:45 EST Filtered Full Citation counts:   Cited 3 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 33 Abstract Views  -  Detailed Statistics Created: Tue, 12 Jan 2021, 14:33:43 EST

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