Lidia Auret
Lidia Auret
Stone Three & Stellenbosch University
Verified email at - Homepage
Cited by
Cited by
Unsupervised process monitoring and fault diagnosis with machine learning methods
C Aldrich, L Auret
Springer 16 (3), 593-606, 2013
Empirical comparison of tree ensemble variable importance measures
L Auret, C Aldrich
Chemometrics and Intelligent Laboratory Systems 105 (2), 157-170, 2011
Interpretation of nonlinear relationships between process variables by use of random forests
L Auret, C Aldrich
Minerals Engineering 35, 27-42, 2012
Machine learning applications in minerals processing: A review
JT McCoy, L Auret
Minerals Engineering 132, 95-109, 2019
Using apparent activation energy as a reactivity criterion for biomass pyrolysis
M Carrier, L Auret, A Bridgwater, JH Knoetze
Energy & Fuels 30 (10), 7834-7841, 2016
Performance of convolutional neural networks for feature extraction in froth flotation sensing
ZC Horn, L Auret, JT McCoy, C Aldrich, BM Herbst
IFAC-PapersOnLine 50 (2), 13-18, 2017
Change point detection in time series data with random forests
L Auret, C Aldrich
Control Engineering Practice 18 (8), 990-1002, 2010
Variational autoencoders for missing data imputation with application to a simulated milling circuit
JT McCoy, S Kroon, L Auret
IFAC-PapersOnLine 51 (21), 141-146, 2018
Unsupervised process fault detection with random forests
L Auret, C Aldrich
Industrial & engineering chemistry research 49 (19), 9184-9194, 2010
Detecting changes in the operational states of hydrocyclones
MJJ van Vuuren, C Aldrich, L Auret
Minerals Engineering 24 (14), 1532-1544, 2011
Monitoring of a simulated milling circuit: Fault diagnosis and economic impact
BJ Wakefield, BS Lindner, JT McCoy, L Auret
Minerals Engineering 120, 132-151, 2018
Fault detection and diagnosis with random forest feature extraction and variable importance methods
C Aldrich, L Auret
IFAC Proceedings Volumes 43 (9), 79-86, 2010
Data-driven fault detection with process topology for fault identification
BS Lindner, L Auret
IFAC Proceedings Volumes 47 (3), 8903-8908, 2014
Comparative analysis of Granger causality and transfer entropy to present a decision flow for the application of oscillation diagnosis
B Lindner, L Auret, M Bauer, JWD Groenewald
Journal of Process Control 79, 72-84, 2019
A systematic workflow for oscillation diagnosis using transfer entropy
B Lindner, L Auret, M Bauer
IEEE Transactions on Control Systems Technology 28 (3), 908-919, 2019
Observations on the separation of iron ore in a prototype batch jig
N Naudé, L Lorenzen, AV Kolesnikov, C Aldrich, L Auret
International Journal of Mineral Processing 120, 43-47, 2013
Process monitoring and fault diagnosis using random forests
L Auret
Stellenbosch: University of Stellenbosch, 2010
Early detection of risk of autism spectrum disorder based on recurrence quantification analysis of electroencephalographic signals
T Pistorius, C Aldrich, L Auret, J Pineda
2013 6th International IEEE/EMBS Conference on Neural Engineering (NER), 198-201, 2013
Fault diagnosis and economic performance evaluation for a simulated base metal leaching operation
JJ Strydom, JJ Miskin, JT McCoy, L Auret, C Dorfling
Minerals Engineering 123, 128-143, 2018
Diagnosis of oscillations in an industrial mineral process using transfer entropy and nonlinearity index
B Lindner, M Chioua, JWD Groenewald, L Auret, M Bauer
IFAC-PapersOnLine 51 (24), 1409-1416, 2018
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