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
Date Issued
2024-09
Author(s) USM
DOI
10.3390/s24175804
Abstract
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 Princ
