| 書目名稱 | Machine Learning Applied to Composite Materials |
| 編輯 | Vinod Kushvaha,M. R. Sanjay,Suchart Siengchin |
| 視頻video | http://file.papertrans.cn/621/620384/620384.mp4 |
| 概述 | Introduces the approach of Machine Learning (ML) based predictive models in the design of composite materials.Presents a design methodology of advanced composite materials based on different applicati |
| 叢書名稱 | Composites Science and Technology |
| 圖書封面 |  |
| 描述 | .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 materialcomposite modelling and design.. |
| 出版日期 | Book 2022 |
| 關鍵詞 | Machine Learning (ML); Materials Modelling; Composite Material Design; Artificial Neural Network; Fractu |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-981-19-6278-3 |
| isbn_softcover | 978-981-19-6280-6 |
| isbn_ebook | 978-981-19-6278-3Series ISSN 2662-1819 Series E-ISSN 2662-1827 |
| issn_series | 2662-1819 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
|Archiver|手機版|小黑屋|
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