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We adopted an approach based on an LSTM neural network to monitor and detect faults in industrial multivariate time series data.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Fault detection and diagnosis in industrial systems
L H Chiang, E L Russell, and R D Braatz · 2001
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Experiencing sax: a novel symbolic representation of time series
Jessica Lin, Eamonn Keogh, Li Wei, and Stefano Lonardi · 2007
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Networks for Machine Learning (lecture 6.5) , 2012
T Tieleman and G Hinton · 2012
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A nonparametric approach for multiple change point analysis of multivariate data
David S. Matteson and Nicholas A. James · 2013
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URL https://securelist.com/analysis/publications/67483/stuxnet-zero-victims/
Stuxnet: Zero victims, 2014 · 2014
Cited alongside, same era.
Dropout: A simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
Cited alongside, same era.
Long short term memory networks for anomaly detection in time series
Pankaj Malhotra, Lovekesh Vig, Gautam Shroff, and Puneet Agarwal · 2015
Cited alongside, same era.
Anomaly detection based on sensor data in petroleum industry applications
Luis MartГ, Nayat Sanchez-Pi, JosГ© Manuel Molina, and Ana Cristina Bicharra Garcia · 2015
Cited alongside, same era.
Tennessee eastman challenge archive
N Lawrence Ricker
Cited in the paper.
URL https://kas.pr/ics-research/dataset_ghl_1
Gasoil heating loop dataset, 2016 · 2016
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Lstm-based encoder-decoder for multi-sensor anomaly detection
Pankaj Malhotra, Anusha Ramakrishnan, Gaurangi Anand, Lovekesh Vig, Puneet Agarwal, and Gautam Shroff · 2016
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ODE - augmented training improves anomaly detection in sensor data from machines
Mohit Yadav, Pankaj Malhotra, Lovekesh Vig, K. Sriram, and Gautam Shroff · 2016
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Anomaly detection in aircraft data using recurrent neural networks (rnn)
Anvardh Nanduri, M S Candidate, and Lance Sherry · 2016
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