An Integrated Approach: A Hybrid Machine Learning Model for the Classification of Unscheduled Stoppages in a Mining Crushing Line Employing Principal Component Analysis and Artificial Neural Networks

This article implements a hybrid Machine Learning (ML) model to classify stoppage events in a copper-crushing equipment, more specifically, a conveyor belt. The model combines Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) with Principal Component Analysis (PCA) to identify the...

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Ngā kaituhi matua:	Pablo Viveros, Cristian Moya, Rodrigo Mena, Fredy Kristjanpoller, David R. Godoy
Hōputu:	Artigo
Reo:	Inglês
I whakaputaina:	MDPI AG 2024-09-01
Rangatū:	Sensors
Ngā marau:	classification stoppages support vector machine artificial neural network principal component analysis copper crushing
Urunga tuihono:	https://www.mdpi.com/1424-8220/24/17/5804
Ngā Tūtohu:	Tāpirihia he Tūtohu Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!

An Integrated Approach: A Hybrid Machine Learning Model for the Classification of Unscheduled Stoppages in a Mining Crushing Line Employing Principal Component Analysis and Artificial Neural Networks

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