Machine learning for polymer composites process simulation – a review-Reference-Cited by-同舟云学术

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Machine learning for polymer composites process simulation – a review

Published:2022-11 Issue: Volume:246 Page:110208
ISSN:1359-8368
Container-title:Composites Part B: Engineering
language:en
Short-container-title:Composites Part B: Engineering

Author:

Cassola Stefano,Duhovic Miro^ORCID,Schmidt Tim^ORCID,May David^ORCID

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering,Mechanics of Materials,Ceramics and Composites

Reference168 articles.

1. Hands-on machine learning with Scikit-learn, Keras & TensorFlow;Géron,2019

2. A survey on semi-supervised learning;van Engelen;Mach Learn,2020

3. Data-driven aerospace engineering: reframing the industry with machine learning;Brunton;AIAA J,2021

4. TensorFlow: a system for large-scale machine learning;Martín Abadi;Proc 12th USENIX Symp Oper Syst Des Implement (OSDI '16),2016

5. Automatic differentiation in PyTorch;Adam Paszke;NIPS 2017 Work Autodiff,2017

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2. From processing to properties: Enhancing machine learning models with microstructural information in polymer nanocomposites;Composites Communications;2024-11

3. Harvesting tacit knowledge for composites workforce development;Composites Part A: Applied Science and Manufacturing;2024-10

4. Machine learning to enhance sustainable plastics: A review;Journal of Cleaner Production;2024-10

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