Empowering Materials Processing and Performance from Data and AI:
Third millennium engineering address new challenges in materials sciences and engineering. In particular, the advances in materials engineering combined with the advances in data acquisition, processing and mining as well as artificial intelligence allow for new ways of thinking in designing new mat...
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| Format: | Elektronisch E-Book |
| Sprache: | English |
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Basel, Switzerland
MDPI
2021
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| Online-Zugang: | Volltext kostenfrei |
| Zusammenfassung: | Third millennium engineering address new challenges in materials sciences and engineering. In particular, the advances in materials engineering combined with the advances in data acquisition, processing and mining as well as artificial intelligence allow for new ways of thinking in designing new materials and products. Additionally, this gives rise to new paradigms in bridging raw material data and processing to the induced properties and performance. This present topical issue is a compilation of contributions on novel ideas and concepts, addressing several key challenges using data and artificial intelligence, such as:- proposing new techniques for data generation and data mining;- proposing new techniques for visualizing, classifying, modeling, extracting knowledge, explaining and certifying data and data-driven models;- processing data to create data-driven models from scratch when other models are absent, too complex or too poor for making valuable predictions;- processing data to enhance existing physic-based models to improve the quality of the prediction capabilities and, at the same time, to enable data to be smarter; and- processing data to create data-driven enrichment of existing models when physics-based models exhibit limits within a hybrid paradigm |
| Beschreibung: | This is a reprint of articles from the Special Issue published online in the open access journal Materials (ISSN 1996-1944) (available at: www.mdpi.com/journal/materials/special issues/empower mat process perform data AI). |
| Beschreibung: | 1 Online-Ressource (172 p.) |
| ISBN: | 9783036518985 |
| DOI: | 10.3390/books978-3-0365-1898-5 |
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| spelling | Chinesta, Francisco 1966- (DE-588)1111897573 edt Empowering Materials Processing and Performance from Data and AI edited by Francisco Chinesta, Elías Cueto and Benjamin Klusemann Basel, Switzerland MDPI 2021 ©2021 1 Online-Ressource (172 p.) txt rdacontent c rdamedia cr rdacarrier This is a reprint of articles from the Special Issue published online in the open access journal Materials (ISSN 1996-1944) (available at: www.mdpi.com/journal/materials/special issues/empower mat process perform data AI). Third millennium engineering address new challenges in materials sciences and engineering. In particular, the advances in materials engineering combined with the advances in data acquisition, processing and mining as well as artificial intelligence allow for new ways of thinking in designing new materials and products. Additionally, this gives rise to new paradigms in bridging raw material data and processing to the induced properties and performance. This present topical issue is a compilation of contributions on novel ideas and concepts, addressing several key challenges using data and artificial intelligence, such as:- proposing new techniques for data generation and data mining;- proposing new techniques for visualizing, classifying, modeling, extracting knowledge, explaining and certifying data and data-driven models;- processing data to create data-driven models from scratch when other models are absent, too complex or too poor for making valuable predictions;- processing data to enhance existing physic-based models to improve the quality of the prediction capabilities and, at the same time, to enable data to be smarter; and- processing data to create data-driven enrichment of existing models when physics-based models exhibit limits within a hybrid paradigm Technology: general issues (DE-588)4143413-4 Aufsatzsammlung gnd-content Cueto, Elías (DE-588)1234030098 edt Klusemann, Benjamin 1984- (DE-588)142865192 edt Erscheint auch als Druck-Ausgabe 978-3-0365-1899-2 https://doi.org/10.3390/books978-3-0365-1898-5 Verlag kostenfrei Volltext X:DOAB https://directory.doabooks.org/handle/20.500.12854/76859 Verlag kostenfrei |
| spellingShingle | Empowering Materials Processing and Performance from Data and AI |
| subject_GND | (DE-588)4143413-4 |
| title | Empowering Materials Processing and Performance from Data and AI |
| title_auth | Empowering Materials Processing and Performance from Data and AI |
| title_exact_search | Empowering Materials Processing and Performance from Data and AI |
| title_exact_search_txtP | Empowering Materials Processing and Performance from Data and AI |
| title_full | Empowering Materials Processing and Performance from Data and AI edited by Francisco Chinesta, Elías Cueto and Benjamin Klusemann |
| title_fullStr | Empowering Materials Processing and Performance from Data and AI edited by Francisco Chinesta, Elías Cueto and Benjamin Klusemann |
| title_full_unstemmed | Empowering Materials Processing and Performance from Data and AI edited by Francisco Chinesta, Elías Cueto and Benjamin Klusemann |
| title_short | Empowering Materials Processing and Performance from Data and AI |
| title_sort | empowering materials processing and performance from data and ai |
| topic_facet | Aufsatzsammlung |
| url | https://doi.org/10.3390/books978-3-0365-1898-5 https://directory.doabooks.org/handle/20.500.12854/76859 |
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