Development of support vector machine learning algorithm for real time update of resource estimation and grade classification

Development of support vector machine learning algorithm for real time update of resource estimation and grade classification

This paper presents the development and implementation of a theoretical mathematical-statistical framework for sequential updating of the grade control model, based on a support vector machine learning algorithm. Utilising the Zambujal orebody within the Neves-Corvo Cu deposit in Portugal, parameter...

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Bibliographic Details
Main Authors: Si, Guangyao, Govindan, Rajesh, Cao, Wenzhuo, Korre, Anna, Durucan, Sevket, Neves, João, de Oliveira Soares, Amilcar, João Pereira, Maria
Other Authors: TU Bergakademie Freiberg, Geowissenschaften, Geotechnik und Bergbau
Format: Others
Language:English
Published: Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola" 2018
Subjects:
Real-Time Mining
Konferenz
Conference
ddc:624
Bergbau
Bergwerk
Markscheidekunde
Geoinformation
Prospektion
Online Access:http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-231313
http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-231313
http://www.qucosa.de/fileadmin/data/qucosa/documents/23131/21.Development%20of%20Support%20Vector%20Machine_RTM2017-21_1b.pdf

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