田纳西伊斯曼过程数据的深度异常检测
机器学习
2023-03-13 v1
摘要
本文首次对现代（深度学习）无监督异常检测方法在化工过程数据上的表现进行了全面评估与分析。我们聚焦于田纳西伊斯曼过程数据集，该数据集近三十年来一直是异常检测方法基准测试的标准试金石。我们的广泛研究将有助于在工业应用中选择合适的异常检测方法。
引用
@article{arxiv.2303.05904,
title = {Deep Anomaly Detection on Tennessee Eastman Process Data},
author = {Fabian Hartung and Billy Joe Franks and Tobias Michels and Dennis Wagner and Philipp Liznerski and Steffen Reithermann and Sophie Fellenz and Fabian Jirasek and Maja Rudolph and Daniel Neider and Heike Leitte and Chen Song and Benjamin Kloepper and Stephan Mandt and Michael Bortz and Jakob Burger and Hans Hasse and Marius Kloft},
journal= {arXiv preprint arXiv:2303.05904},
year = {2023}
}