Machine Learning Applied to Composite Materials (Hardcover, 1st ed. 2022)

This book introduces the approach of Machine Learning (ML) based predictive models in the design of composite materials to achieve the required properties for certain applications. ML can learn from existing experimental data obtained from very limited number of experiments and subsequently can be trained to find solutions of the complex non-linear, multi-dimensional functional relationships without any prior assumptions about their nature. In this case the ML models can learn from existing experimental data obtained from (1) composite design based on various properties of the matrix material and fillers/reinforcements (2) material processing during fabrication (3) property relationships. Modelling of these relationships using ML methods significantly reduce the experimental work involved in designing new composites, and therefore offer a new avenue for material design and properties. The book caters to students, academics and researchers who are interested in the field of material composite modelling and design.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Composites Science and Technology
Release date:	December 2022
First published:	2022
Editors:	Vinod Kushvaha • M.R. Sanjay • Priyanka Madhushri • Suchart Siengchin
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	198
Edition:	1st ed. 2022
ISBN-13:	978-981-19-6277-6
Categories:	Books > Professional & Technical > Mechanical engineering & materials > Materials science > General Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	981-19-6277-4
Barcode:	9789811962776

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