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Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools

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Published in:Journal of Mechanical Engineering and Sciences
Format: Online Article RSS Article
Published: 2025
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container_title Journal of Mechanical Engineering and Sciences
description
discipline_display Mechanical Engineering
discipline_facet Mechanical Engineering
format Online Article
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genre Journal Article
id rss_article:62572
institution FRELIP
journal_source_facet Journal of Mechanical Engineering and Sciences
last_indexed 2026-06-20T21:27:21.959Z
publishDate 2025
publishDateSort 2025
record_format rss_article
spellingShingle Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools
Mechanical Engineering
General
Mechanical Engineering
sub_discipline_display General
sub_discipline_facet General
subject_display Mechanical Engineering
General
Mechanical Engineering
subject_facet Mechanical Engineering
General
Mechanical Engineering
title Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools
title_alt Enfoques híbridos para la predicción de la conformabilidad de chapa metálica: una sinergia de herramientas experimentales, numéricas y de aprendizaje automático
Approches hybrides pour la prédiction de la formabilité des tôles : une synergie d'outils expérimentaux, numériques et d'apprentissage automatique
Abordagens Híbridas para Previsão de Conformabilidade de Chapas Metálicas: Uma Sinergia de Ferramentas Experimentais, Numéricas e de Aprendizado de Máquina
title_auth Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools
title_es_txt Enfoques híbridos para la predicción de la conformabilidad de chapa metálica: una sinergia de herramientas experimentales, numéricas y de aprendizaje automático
title_fr_txt Approches hybrides pour la prédiction de la formabilité des tôles : une synergie d'outils expérimentaux, numériques et d'apprentissage automatique
title_full Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools
title_fullStr Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools
title_full_unstemmed Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools
title_pt_txt Abordagens Híbridas para Previsão de Conformabilidade de Chapas Metálicas: Uma Sinergia de Ferramentas Experimentais, Numéricas e de Aprendizado de Máquina
title_short Hybrid approaches for sheet metal formability prediction: A synergy of experimental, numerical and machine learning tools
title_sort hybrid approaches for sheet metal formability prediction: a synergy of experimental, numerical and machine learning tools
topic Mechanical Engineering
General
Mechanical Engineering
url https://journal.ump.edu.my/index.php/jmes/article/view/12371