most citedAnomaly Detection for a Water Treatment System Using Unsupervised Machine Learning

335 citations · 335 across the 1 of their papers we have counts for

collaborators

1 paper

cs.LG2017★ 335 cited

Anomaly Detection for a Water Treatment System Using Unsupervised Machine Learning

Jun Inoue, Yoriyuki Yamagata, Yuqi Chen +2

In this paper, we propose and evaluate the application of unsupervised machine learning to anomaly detection for a Cyber-Physical System (CPS). We compare two methods: Deep Neural…