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Economic Viability for Rare Earth Element Mining using Machine Learning

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Bibliographic Details
Main Author: Kamarul Azril, Shamel Daniel
Format: Final Year Project
Published: 2024
Subjects:
T Technology (General)
Online Access:http://utpedia.utp.edu.my/id/eprint/28806/
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id oai:utpedia.utp.edu.my:28806
record_format eprints
spelling oai:utpedia.utp.edu.my:288062024-08-16T04:42:20Z http://utpedia.utp.edu.my/id/eprint/28806/ Economic Viability for Rare Earth Element Mining using Machine Learning Kamarul Azril, Shamel Daniel T Technology (General) 2024-05 Final Year Project NonPeerReviewed Kamarul Azril, Shamel Daniel (2024) Economic Viability for Rare Earth Element Mining using Machine Learning. [Final Year Project] (Submitted)
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
topic T Technology (General)
spellingShingle T Technology (General)
Kamarul Azril, Shamel Daniel
Economic Viability for Rare Earth Element Mining using Machine Learning
format Final Year Project
author Kamarul Azril, Shamel Daniel
author_facet Kamarul Azril, Shamel Daniel
author_sort Kamarul Azril, Shamel Daniel
title Economic Viability for Rare Earth Element Mining using Machine Learning
title_short Economic Viability for Rare Earth Element Mining using Machine Learning
title_full Economic Viability for Rare Earth Element Mining using Machine Learning
title_fullStr Economic Viability for Rare Earth Element Mining using Machine Learning
title_full_unstemmed Economic Viability for Rare Earth Element Mining using Machine Learning
title_sort economic viability for rare earth element mining using machine learning
publishDate 2024
url http://utpedia.utp.edu.my/id/eprint/28806/
_version_ 1808972441601441792
score 13.222552

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