Predictive Model of the Percentage of Copper in the Matte of the Teniente Converter Through an Artificial Neural Network
Crossref DOI link: https://doi.org/10.1007/s11837-021-05052-8
Published Online: 2022-01-14
Published Print: 2022-02
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Riffo, Vladimir https://orcid.org/0000-0003-1274-6224
Pulgar, Alejandro
Text and Data Mining valid from 2022-01-14
Version of Record valid from 2022-01-14
Article History
Received: 5 June 2021
Accepted: 16 November 2021
First Online: 14 January 2022
Conflict of interest
: The authors declare that they have no conflict of interest.