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Estimation of inverted electrical resistivity and advanced modelling of iron ore using machine learning models based on geophysical array data

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Published in:Near Surface Geophysics
Format: Online Article RSS Article
Published: 2026
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container_title Near Surface Geophysics
description
discipline_display Geophysics
discipline_facet Geophysics
format Online Article
RSS Article
genre Journal Article
id rss_article:70102
institution FRELIP
journal_source_facet Near Surface Geophysics
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Estimation of inverted electrical resistivity and advanced modelling of iron ore using machine learning models based on geophysical array data
Geophysics
General
Geophysics
sub_discipline_display General
sub_discipline_facet General
subject_display Geophysics
General
Geophysics
Geophysics
General
Geophysics
subject_facet Geophysics
General
Geophysics
title Estimation of inverted electrical resistivity and advanced modelling of iron ore using machine learning models based on geophysical array data
title_auth Estimation of inverted electrical resistivity and advanced modelling of iron ore using machine learning models based on geophysical array data
title_full Estimation of inverted electrical resistivity and advanced modelling of iron ore using machine learning models based on geophysical array data
title_fullStr Estimation of inverted electrical resistivity and advanced modelling of iron ore using machine learning models based on geophysical array data
title_full_unstemmed Estimation of inverted electrical resistivity and advanced modelling of iron ore using machine learning models based on geophysical array data
title_short Estimation of inverted electrical resistivity and advanced modelling of iron ore using machine learning models based on geophysical array data
title_sort estimation of inverted electrical resistivity and advanced modelling of iron ore using machine learning models based on geophysical array data
topic Geophysics
General
Geophysics
url https://onlinelibrary.wiley.com/doi/10.1002/nsg.70052?af=R