Publicación:
ASSESSING MACHINE LEARNING-BASED APPROACHES FOR SILICA CONCENTRATION ESTIMATION IN IRON FROTH FLOTATION

dc.creatorMAURICIO ALEJANDRO MONTANARES SEPÚLVEDA
dc.creatorSEBASTIÁN IGNACIO GUAJARDO HERRERA
dc.creatorMARÍA NATHALIE RISSO SEPÚLVEDA
dc.date2021
dc.date.accessioned2025-01-10T15:22:19Z
dc.date.available2025-01-10T15:22:19Z
dc.date.issued2021
dc.description.abstractIN THE MINING INDUSTRY, SPECIFICALLY IN THE FLOTATION PROCESS, THERE IS A CHALLENGE ASSOCIATED TO NONINVASIVE, REAL-TIME CONTAMINANT AND IMPURITIES ESTIMATION. ACHIEVING PREDICTIONS ON CONTAMINANT LEVELS HAS A HIGH IMPACT ON QUALITY INSURANCE AND IT CAN HELP TECHNICIANS AND ENGINEERS TO MAKE ADJUSTMENTS IN ADVANCE TO IMPROVE THE QUALITY OF THE FINAL PRODUCT, AND THUS PROFITS. IN THIS PAPER, EXPLORATORY RESEARCH IS PERFORMED ON THE PROBLEM OF SILICA CONCENTRATE ESTIMATION FOR IRON ORE FROTH FLOTATION USING MACHINE LEARNING TECHNIQUES, WITH THE GOAL TO IDENTIFY ALGORITHMS THAT MAY BE SUITABLE FOR INDUSTRY SOFT SENSOR DEVELOPMENT. FOR THIS PURPOSE, A PUBLIC, REAL PROCESS DATASET IS USED AND THREE DIFFERENT MACHINE LEARNING TECHNIQUES ARE IMPLEMENTED: RANDOM FOREST (RF), LONG SHORT-TERM MEMORY (LSTM) AND GATED RECURRENT UNIT (GRU). THE TECHNIQUES WERE IMPLEMENTED, TESTED AND COMPARED IN TERMS OF THEIR ERROR PERCENTAGE, MEAN ABSOLUTE ERROR, MEAN SQUARE ERROR, AND ROOT MEAN SQUARE ERROR. OBTAINED RESULTS SHOW ACCEPTABLE PERFORMANCE FOR LTSM AND GRU IMPLEMENTATIONS, BEING LSTM NETWORK THE OUT-PERFORMER WITH ERRORS BELOW 9%.
dc.formatapplication/pdf
dc.identifier.doi10.1109/ICAACCA51523.2021.9465297
dc.identifier.urihttps://repositorio.ubiobio.cl/handle/123456789/11699
dc.languagespa
dc.publisherIEEE INTERNATIONAL CONFERENCE ON AUTOMÁTICA (ICA-ACCA)
dc.relation.uri10.1109/ICAACCA51523.2021.9465297
dc.rightsPUBLICADA
dc.titleASSESSING MACHINE LEARNING-BASED APPROACHES FOR SILICA CONCENTRATION ESTIMATION IN IRON FROTH FLOTATION
dc.typeACTA DE CONFERENCIA
dspace.entity.typePublication
ubb.EstadoPUBLICADA
ubb.Otra ReparticionDEPARTAMENTO DE INGENIERIA ELECTRICA Y ELECTRONICA
ubb.Otra ReparticionDEPARTAMENTO DE INGENIERIA ELECTRICA Y ELECTRONICA
ubb.Otra ReparticionDEPARTAMENTO DE INGENIERIA ELECTRICA Y ELECTRONICA
ubb.SedeCONCEPCIÓN
ubb.SedeCONCEPCIÓN
ubb.SedeCONCEPCIÓN
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