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PAKDD
2005
ACM

An Anomaly Detection Method for Spacecraft Using Relevance Vector Learning

10 years 9 months ago
An Anomaly Detection Method for Spacecraft Using Relevance Vector Learning
This paper proposes a novel anomaly detection system for spacecrafts based on data mining techniques. It constructs a nonlinear probabilistic model w.r.t. behavior of a spacecraft by applying the relevance vector regression and autoregression to massive telemetry data, and then monitors the on-line telemetry data using the model and detects anomalies. A major advantage over conventional anomaly detection methods is that this approach requires little a priori knowledge on the system.
Ryohei Fujimaki, Takehisa Yairi, Kazuo Machida
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where PAKDD
Authors Ryohei Fujimaki, Takehisa Yairi, Kazuo Machida
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