Full Text Available

Note: Clicking the button above will open the full text document at the original institutional repository in a new window.

Nondestructive quantitative model for predicting the residual tensile strength of silk textile cultural heritage based on machine learning

Saved in:
Bibliographic Details
Published in:Fashion and Textiles
Format: Online Article RSS Article
Published: 2026
Subjects:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1868552290660515841
collection WordPress RSS
FRELIP Feed Integration
container_title Fashion and Textiles
description
discipline_display Textile Industries and Fabrics
discipline_facet Textile Industries and Fabrics
format Online Article
RSS Article
genre Journal Article
id rss_article:57545
institution FRELIP
journal_source_facet Fashion and Textiles
last_indexed 2026-06-20T21:17:54.275Z
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Nondestructive quantitative model for predicting the residual tensile strength of silk textile cultural heritage based on machine learning
Textile Industries and Fabrics
General
Textile Industries and Fabrics
sub_discipline_display General
sub_discipline_facet General
subject_display Textile Industries and Fabrics
General
Textile Industries and Fabrics
subject_facet Textile Industries and Fabrics
General
Textile Industries and Fabrics
title Nondestructive quantitative model for predicting the residual tensile strength of silk textile cultural heritage based on machine learning
title_alt Modelo cuantitativo no destructivo para predecir la resistencia a la tracción residual del patrimonio cultural textil de seda basado en aprendizaje automático
Modèle quantitatif non destructif pour prédire la résistance à la traction résiduelle du patrimoine culturel textile en soie basé sur l'apprentissage automatique
Modelo quantitativo não destrutivo para prever a resistência à tração residual do patrimônio cultural têxtil de seda baseado em aprendizado de máquina
title_auth Nondestructive quantitative model for predicting the residual tensile strength of silk textile cultural heritage based on machine learning
title_es_txt Modelo cuantitativo no destructivo para predecir la resistencia a la tracción residual del patrimonio cultural textil de seda basado en aprendizaje automático
title_fr_txt Modèle quantitatif non destructif pour prédire la résistance à la traction résiduelle du patrimoine culturel textile en soie basé sur l'apprentissage automatique
title_full Nondestructive quantitative model for predicting the residual tensile strength of silk textile cultural heritage based on machine learning
title_fullStr Nondestructive quantitative model for predicting the residual tensile strength of silk textile cultural heritage based on machine learning
title_full_unstemmed Nondestructive quantitative model for predicting the residual tensile strength of silk textile cultural heritage based on machine learning
title_pt_txt Modelo quantitativo não destrutivo para prever a resistência à tração residual do patrimônio cultural têxtil de seda baseado em aprendizado de máquina
title_short Nondestructive quantitative model for predicting the residual tensile strength of silk textile cultural heritage based on machine learning
title_sort nondestructive quantitative model for predicting the residual tensile strength of silk textile cultural heritage based on machine learning
topic Textile Industries and Fabrics
General
Textile Industries and Fabrics
url https://link.springer.com/article/10.1186/s40691-026-00472-z