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portada Empowering Materials Processing and Performance from Data and AI
Type
Physical Book
Publisher
Author
Language
English
Pages
172
Format
Hardcover
Dimensions
24.4 x 17.0 x 1.6 cm
Weight
0.57 kg.
ISBN13
9783036518992
Categories

Empowering Materials Processing and Performance from Data and AI

Chinesta, Francisco ; Cueto, El´ıAs ; Klusemann, Benjamin (Author) · Mdpi AG · Hardcover

Empowering Materials Processing and Performance from Data and AI - Chinesta, Francisco ; Cueto, El´ıas ; Klusemann, Benjamin

New Book Imported to Austria *
Delivery: 27 Mar - 31 Mar Shipping: 3 to 4 business days.
50,81 €
* Import costs and 10% VAT included in the price ✅
50,81 €
Delivery to any Austria address between Friday, March 27 and Tuesday, March 31
Origin: United Kingdom Import costs included in the price ✅
Delivery to any Austria address between Friday, March 27 and Tuesday, March 31.

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Synopsis "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 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 physicsbased models exhibit limits within a hybrid paradigm.

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