Mondrian conformal anomaly detection for fault sequence identification in heterogeneous fleets

2021 ◽  
Author(s):  
Shiraz Farouq ◽  
Stefan Byttner ◽  
Mohamed-Rafik Bouguelia ◽  
Henrik Gadd
Keyword(s):  
Anomaly Detection ◽  
Conformal Anomaly ◽  
Sequence Identification

scholarly journals SHNN-CAD+: An Improvement on SHNN-CAD for Adaptive Online Trajectory Anomaly Detection

Sensors ◽  
2018 ◽  
Vol 19 (1) ◽  
pp. 84 ◽  
Author(s):  
Yuejun Guo ◽  
Anton Bardera
Keyword(s):  
Anomaly Detection ◽  
Nearest Neighbor ◽  
Distance Measure ◽  
Synthetic Data ◽  
Conformal Anomaly ◽  
Online Detection ◽  
Trajectory Data ◽  
Practical Applications ◽  
Anomaly Detector ◽  
Modified Hausdorff Distance

To perform anomaly detection for trajectory data, we study the Sequential Hausdorff Nearest-Neighbor Conformal Anomaly Detector (SHNN-CAD) approach, and propose an enhanced version called SHNN-CAD +. SHNN-CAD was introduced based on the theory of conformal prediction dealing with the problem of online detection. Unlike most related approaches requiring several not intuitive parameters, SHNN-CAD has the advantage of being parameter-light which enables the easy reproduction of experiments. We propose to adaptively determine the anomaly threshold during the online detection procedure instead of predefining it without any prior knowledge, which makes the algorithm more usable in practical applications. We present a modified Hausdorff distance measure that takes into account the direction difference and also reduces the computational complexity. In addition, the anomaly detection is more flexible and accurate via a re-do strategy. Extensive experiments on both real-world and synthetic data show that SHNN-CAD + outperforms SHNN-CAD with regard to accuracy and running time.

Conformal Anomaly Detection of Trajectories with a Multi-class Hierarchy

2015 ◽  
pp. 281-290 ◽  
Author(s):  
James Smith ◽  
Ilia Nouretdinov ◽  
Rachel Craddock ◽  
Charles Offer ◽  
Alexander Gammerman
Keyword(s):  
Anomaly Detection ◽  
Conformal Anomaly ◽  
Class Hierarchy

Anomaly Detection in Sensor Data

2018 ◽  
Vol 18 (1) ◽  
pp. 20-32 ◽  
Author(s):  
Jong-Min Kim ◽  
Jaiwook Baik
Keyword(s):  
Anomaly Detection ◽  
Sensor Data

An Anomaly Detection Method with Exemplar Subsequence for Time Series Data

2016 ◽  
Vol 136 (3) ◽  
pp. 363-372
Author(s):  
Takaaki Nakamura ◽  
Makoto Imamura ◽  
Masashi Tatedoko ◽  
Norio Hirai
Keyword(s):  
Time Series ◽  
Anomaly Detection ◽  
Time Series Data ◽  
Detection Method ◽  
Series Data

Proposal of the Anomaly Detection Method of Live-alone by LOF using Multiple Sensors

2015 ◽  
Vol 135 (12) ◽  
pp. 749-755
Author(s):  
Taiyo Matsumura ◽  
Ippei Kamihira ◽  
Katsuma Ito ◽  
Takashi Ono
Keyword(s):  
Anomaly Detection ◽  
Detection Method ◽  
Multiple Sensors
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